mapping the local galactic halo and an image motion ... · mapping the local galactic halo and an...

Mapping the Local Galactic Halo and An

Image Motion Compensation System for the

Multi-Object Double Spectrograph

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the

Graduate School of The Ohio State University

By

Jennifer L. Marshall

*****

The Ohio State University

2006

Dissertation Committee: Approved by

Professor Darren L. DePoy, Adviser

Professor Andrew Gould Adviser

Professor Jennifer JohnsonAstronomy Graduate Program

ABSTRACT

In the first part of this dissertation I describe the results of a photometric

and spectroscopic survey of a sample of cool, metal-poor subdwarfs in the solar

neighborhood. These metal-poor stars are of interest because, as members of the

Galactic halo, they give clues about the history of the Galaxy and its formation

mechanisms, and may enable us to study satellites of the Milky Way and the Galactic

merger history. A sample of halo subdwarfs have been selected using a reduced

proper motion (RPM) diagram. Accurate and precise photometric measurements of

635 stars selected in this manner allow better definition of the RPM diagram and

determination of its usefulness as a selection method. Accurate spectrophotometry

yields radial velocities of the candidates as well as metallicity and temperature

estimates for 288 subdwarfs. Of special interest in this sample are the ten newly

discovered extremely metal-poor stars, as well as four carbon-enhanced metal-poor

stars. I use these new observations to search the local Galactic halo for structure

due to merger remnants and moving groups; there is some evidence for both. I also

discuss the metallicity distribution function of the sample and compare it to previous

work on this subject.

ii

No astronomical observations of any sort are possible without appropriate,

well-calibrated instrumentation with which to perform the measurements. In the

second part of this dissertation, I describe the Image Motion Compensation System

(IMCS) for the Multi-Object Double Spectrograph (MODS), an optical spectrograph

for the Large Binocular Telescope. The system performs closed-loop image motion

compensation, actively correcting for image motion in the spectrograph’s focal plane

caused by large scale structural bending due to gravity as well as other effects such as

temperature fluctuation and mechanism flexure within the instrument. The system

is currently installed in the MODS instrument and controls instrumental flexure to

within specifications. I describe the initial development efforts of this system, results

from the preliminary laboratory tests, and the final performance of the system as

deployed in the MODS spectrograph.

iii

Dedicated to S. P.

iv

ACKNOWLEDGMENTS

Several people at Ohio State have been instrumental to my development and

success as an instrument builder and a scientist.

Darren DePoy has been a wonderful thesis adviser, providing me with rich and

numerous opportunities to experience science, observing, and instrument building

in so many ways. He has been incredibly supportive and helpful at every stage of

my tenure as a graduate student, and has also been a great role model and my best

friend. My hope for the future is to continue to follow in his footsteps; I will value

his advice and lessons throughout my career.

Andy Gould has inspired me with his dedication to producing excellent science

as well as through his role as a leader in the department. Every graduate student

at Ohio State owes him a huge debt of gratitude for his commitment to providing

excellent training in becoming a scientist. The department would not be the same

without him.

Tom O’Brien has taught me an enormous amount about how to think about,

develop, build, and test an instrument. My future career is built in part upon the

v

foundation that Tom has helped me to establish. He is an skilled instrument builder

and talented engineer, and I will miss our lunch chats greatly.

Juna Kollmeier has been a great inspiration to me scientifically. Her dedication

to science and to the department, and her unwillingness to accept anything but the

best, has made the department a better place while she has been here.

Tim Beers helped immensely in determining metallicities and effective

temperatures from the spectrophotometric measurements.

Several graduate students also deserve thanks. Juna Kollmeier, Chris Morgan,

and the 2003 Astro830 class assisted in obtaining some of the photometric

observations for this work. Jason Eastman has provided invaluable graphical and

programming expertise over the past year.

David Price has supported the work on the IMCS by establishing a graduate

fellowship provided by the David G. Price Foundation. Work on the IMCS is also

supported by NSF grant AST-9987045 and through an award from the Telescope

System Instrumentation Program (TSIP). TSIP is funded by the National Science

Foundation and is administered by the National Optical Astronomy Observatory

(NOAO). NOAO is operated by the Association of Universities for Research in

Astronomy (AURA), Inc. under cooperative agreement with the National Science

Foundation. Work on cool subdwarfs has been supported in part by NSF Grant

AST-0205789.

vi

VITA

January 12, 1978 . . . . . . . . . . . . . . . Born – Pierre, S.D., USA

2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . B. A. Integrated Sciences and Physics,

Northwestern University

2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . M. S. Astronomy, The Ohio State University

2000 – 2001 . . . . . . . . . . . . . . . . . . . . . Presidential Fellow, The Ohio State University

2001 – 2003 . . . . . . . . . . . . . . . . . . . . . David G. Price Fellow, The Ohio State University

2003 – 2006 . . . . . . . . . . . . . . . . . . . . Research Associate, The Ohio State University

PUBLICATIONS

Research Publications

J. L. Marshall, C. J. Burke, D. L. DePoy, A. Gould, and J. A. Kollmeier,

“Survey for Transiting Extrasolar Planets in Stellar Systems. II. Spectrophotometry

and Metallicities of Open Clusters”, AJ, 130, 1916, (2005).

C. M. Hamilton, W. Herbst, F. J. Vrba, M. A. Ibrahimov, R. Mundt, C. A.

L. Bailer-Jones, A. V. Filippenko, W. Li, V. J. S. Bejar, P. Abraham, M. Kun, A.

Moor, J. Benko, S. Csizmadia, D. L. DePoy, R. W. Pogge, and J. L. Marshall, “The

Disappearing Act of KH 15D: Photometric Results from 1995 to 2004”, AJ, 130,

1896, (2005).

C. J. Morgan, P. L. Byard, D. L. DePoy, M. Derwent, C. S. Kochanek, J. L.

Marshall, T. P. O’Brien, and R. W. Pogge, “RETROCAM: A Versatile Optical

Imager for Synoptic Studies”, AJ, 129, 2504, (2005).

vii

T. Renbarger, D. T. Chuss, J. L. Dotson, G. S. Griffin, J. L. Hanna, R. F.

Loewenstein, P. S. Malhotra, J. L. Marshall, G. Novak, and R. J. Pernic, “Early

Results from SPARO: Instrument Characterization and Polarimetry of NGC 6334”,

PASP, 116, 415, (2004).

FIELDS OF STUDY

Major Field: Astronomy

viii

Table of Contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Vita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi

Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Mapping the Local Galactic Halo . . . . . . . . . . . . . . . . . . . . 1

1.2 An Image Motion Compensation System for the Multi-Object Double

Spectrograph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.3 Scope of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . 9

Chapter 2 Mapping the Local Galactic Halo. I. Optical Photometry

of Cool Subdwarf Candidates . . . . . . . . . . . . . . . . . . . . . . . 10

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.2 Sample Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.3 Observations and Data Reduction . . . . . . . . . . . . . . . . . . . . 15

2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.4.1 BV RI Photometry . . . . . . . . . . . . . . . . . . . . . . . . 21

ix

2.4.2 Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2.4.3 Comparison with rNLTT Photometry . . . . . . . . . . . . . . 26

2.4.4 An Improved RPM Diagram . . . . . . . . . . . . . . . . . . . 28

2.4.5 Color-Color Diagram . . . . . . . . . . . . . . . . . . . . . . . 29

2.5 Summary and Future Work . . . . . . . . . . . . . . . . . . . . . . . 30

Chapter 3 Mapping the Local Galactic Halo. II. Optical

Spectrophotometry of Cool Subdwarf Candidates . . . . . . . . . . 112

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

3.2 Observations and Data Reduction . . . . . . . . . . . . . . . . . . . . 113

3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

3.3.1 Radial Velocities . . . . . . . . . . . . . . . . . . . . . . . . . 118

3.3.2 Simulated Photometry . . . . . . . . . . . . . . . . . . . . . . 122

3.3.3 Spectral Types . . . . . . . . . . . . . . . . . . . . . . . . . . 123

3.3.4 Metallicity Estimates . . . . . . . . . . . . . . . . . . . . . . . 123

3.3.5 Distance Estimates . . . . . . . . . . . . . . . . . . . . . . . . 131

3.3.6 Derivation of Effective Temperatures . . . . . . . . . . . . . . 134

3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

3.4.1 Radial Velocities and Proper Motions . . . . . . . . . . . . . . 135

3.4.2 Metallicity Distribution . . . . . . . . . . . . . . . . . . . . . 136

3.4.3 Fraction of Subdwarfs . . . . . . . . . . . . . . . . . . . . . . 136

3.4.4 The “Effective Yield” of Metal-Poor Stars . . . . . . . . . . . 137

3.4.5 Carbon-Enhanced Metal-Poor Stars . . . . . . . . . . . . . . . 139

3.4.6 Hipparcos Stars in the Sample . . . . . . . . . . . . . . . . . . 142

x

3.4.7 Color-Color Plot . . . . . . . . . . . . . . . . . . . . . . . . . 143

3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144

Chapter 4 Mapping the Local Galactic Halo. III. Kinematics of Halo

Subdwarfs and a Search for Moving Groups . . . . . . . . . . . . . . 249

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

4.2 Calculation of Space Motions . . . . . . . . . . . . . . . . . . . . . . 252

4.3 Velocity Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 253

4.4 A Search for Moving Groups . . . . . . . . . . . . . . . . . . . . . . . 255

4.5 A Search for Merger Remnants . . . . . . . . . . . . . . . . . . . . . 258

4.6 Individual Stars of Interest . . . . . . . . . . . . . . . . . . . . . . . . 262

4.6.1 NLTT 9437, a Candidate HVS . . . . . . . . . . . . . . . . . . 263

4.6.2 NLTT 39456/7, a Fast-Moving Halo Binaries . . . . . . . . . . 264

4.6.3 Other Fast-Moving Stars . . . . . . . . . . . . . . . . . . . . . 265

4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268

Chapter 5 Mapping the Local Galactic Halo. IV. The Metallicity

Distribution Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295

5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295

5.2 Metallicity Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . 298

5.3 Metallicity Distribution Function . . . . . . . . . . . . . . . . . . . . 299

5.4 Comparison to Models . . . . . . . . . . . . . . . . . . . . . . . . . . 300

5.5 The Metal-Weak Tail . . . . . . . . . . . . . . . . . . . . . . . . . . . 302

5.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303

xi

Chapter 6 An Image Motion Compensation System for the Multi-

Object Double Spectrograph . . . . . . . . . . . . . . . . . . . . . . . 311

6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311

6.2 System Design, Specifications, and Operations . . . . . . . . . . . . . 314

6.2.1 System Design . . . . . . . . . . . . . . . . . . . . . . . . . . 314

6.2.2 Optical Layout . . . . . . . . . . . . . . . . . . . . . . . . . . 315

6.2.3 Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . 316

6.2.4 Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317

6.2.5 System Component Selection . . . . . . . . . . . . . . . . . . 318

6.3 Description of Lab IMCS Tests . . . . . . . . . . . . . . . . . . . . . 325

6.3.1 Components of Lab Setup . . . . . . . . . . . . . . . . . . . . 326

6.3.2 System Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . 330

6.3.3 Results of Lab Tests . . . . . . . . . . . . . . . . . . . . . . . 333

6.4 On-Instrument IMCS and the IMCS as a Diagnostic Tool . . . . . . . 335

6.4.1 IMCS On-Instrument Performance . . . . . . . . . . . . . . . 335

6.4.2 The IMCS as a Diagnostic Tool . . . . . . . . . . . . . . . . . 338

6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340

Appendix A Spectra of 319 Candidate Subdwarfs . . . . . . . . . . . . 358

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439

xii

List of Tables

2.1 Nightly Photometric Solutions for B and V . . . . . . . . . . . . . . 42

2.2 Nightly Photometric Solutions for R and I . . . . . . . . . . . . . . 45

2.3 BV RI Photometry of Candidate Subdwarfs . . . . . . . . . . . . . . 48

2.4 Photometric Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

3.1 Observing Log . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166

3.2 Final radial velocities for 298 stars . . . . . . . . . . . . . . . . . . . 170

3.3 Line indices from Beers et al. (1999) . . . . . . . . . . . . . . . . . . 189

3.4 Measured line indices . . . . . . . . . . . . . . . . . . . . . . . . . . 190

3.5 Derived metallicities . . . . . . . . . . . . . . . . . . . . . . . . . . . 209

3.6 Line indices from Gizis (1997) . . . . . . . . . . . . . . . . . . . . . . 225

3.7 Gizis (1997) Indices measured for stars with (B − V )0 >1.2 . . . . . 226

3.8 De-reddened color indices, distance estimates, and effective

temperatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228

3.9 “Effective yield” of the present sample . . . . . . . . . . . . . . . . . 247

3.10 Carbon-enhanced metal-poor stars . . . . . . . . . . . . . . . . . . . 248

4.1 Galactocentric Velocity Components . . . . . . . . . . . . . . . . . . 277

4.2 Comparison between the present sample and that of Chiba & Beers

(2000) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292

4.3 Velocity components for subsets of the sample. . . . . . . . . . . . . 294

xiii

List of Figures

2.1 Reduced proper motion diagram of the complete rNLTT. . . . . . . . 32

2.2 Reduced proper motion diagram of the candidate subdwarfs. . . . . . 33

2.3 Histogram of rNLTT magnitudes. . . . . . . . . . . . . . . . . . . . . 34

2.4 Positions of the candidate subdwarfs. . . . . . . . . . . . . . . . . . . 35

2.5 Histogram of the number of observations of the candidate subdwarfs. 36

2.6 Comparison of multiple photometric measurements of a star. . . . . . 37

2.7 Comparison of the photometry presented in this work to that of the

rNLTT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

2.8 Comparison of the photometry of rNLTT stars with USNO-A

photometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.9 Reduced proper motion diagram of the sample using improved

photometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

2.10 BV I color-color diagram for the sample. . . . . . . . . . . . . . . . . 41

3.1 Representative sample of spectra of the sample stars. . . . . . . . . . 146

3.2 Comparison of the two methods used to derive low-precision radial

velocities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

3.3 Comparison of the high-precision radial velocities with the low-

precision radial velocities. . . . . . . . . . . . . . . . . . . . . . . . . 148

3.4 Comparison of radial velocities derived in this work with those

measured by Carney et al. (1996). . . . . . . . . . . . . . . . . . . . . 149

xiv

3.5 Comparison of B-V and V-R photometry measured in Chapter 2 and

that measured by integrating over the spectra presented in this work. 150

3.6 Histogram of the first-pass estimates of spectral types. . . . . . . . . 151

3.7 Comparison of the metallicities derived here to those measured with

high-resolution spectroscopy by Cayrel de Strobel et al. (2001). . . . . 152

3.8 Comparison of the metallicities derived here to those determined

previously with moderate-resolution spectroscopy by Carney et al. (1996).153

3.9 Comparison of the Beers et al. (2000) method of determining distances

and that of Gould (2003). . . . . . . . . . . . . . . . . . . . . . . . . 154

3.10 Comparison of the two distance methods as a function of (B − V )0. . 155

3.11 Comparison of the final distance estimates to distances measured by

Hipparcos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

3.12 Teff as a function of (B − V )0 and (J − K)0. . . . . . . . . . . . . . 157

3.13 Determination of luminosity class for the red stars in the sample based

on Gizis (1997) indices. . . . . . . . . . . . . . . . . . . . . . . . . . . 158

3.14 Radial velocities and proper motions as a function of metallicity. . . . 159

3.15 Metallicity distribution of the sample. . . . . . . . . . . . . . . . . . . 160

3.16 Spectra of the five carbon-enhanced metal-poor stars in the sample. . 161

3.17 [C/Fe] vs. [Fe/H] for all stars with derived metallicities. . . . . . . . . 162

3.18 CMD for the Hipparcos stars in the survey. . . . . . . . . . . . . . . . 163

3.19 (B − V )0—(J − K)0 color-color plot with metallicities. . . . . . . . . 164

3.20 (B − V )0—(J − K)0 color-color plot for four metallicity bins. . . . . . 165

4.1 (U, V, W ) of the entire sample of 295 stars. . . . . . . . . . . . . . . . 269

4.2 (U, V, W ) of 290 subdwarfs. . . . . . . . . . . . . . . . . . . . . . . . 270

4.3 (U, V, W ) vs. [Fe/H] . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

xv

4.4 (U, V, W ) of the two moving groups found in the sample. . . . . . . . 272

4.5 Reproduction of Figure 9 from Chapter 2. . . . . . . . . . . . . . . . 273

4.6 Reduced proper motion diagram of the sample with stars in the

proposed merger remnant indicated. . . . . . . . . . . . . . . . . . . . 274

4.7 (U, V, W ) of the stars in the proposed merger remnant. . . . . . . . . 275

4.8 (U, V, W ) vs. [Fe/H] for the proposed merger remnant. . . . . . . . . 276

5.1 Metallicities of 254 stars with metallicity estimates. . . . . . . . . . . 305

5.2 Rest-frame space velocities for the stars with metallicity estimates. . . 306

5.3 The MDF for only the halo stars in the sample. . . . . . . . . . . . . 307

5.4 Metallicity distribution function for the sample. . . . . . . . . . . . . 308

5.5 Metallicity distribution function of the sample compared to the best-fit

simple model of Laird et al. (1988). . . . . . . . . . . . . . . . . . . . 309

5.6 Comparing the low-metallicity tail of this work to that of the HK Survey.310

6.1 Schematic drawing of the IMCS system. . . . . . . . . . . . . . . . . 341

6.2 Temperature dependence of reference laser wavelength. . . . . . . . . 342

6.3 Beam profile of the IMCS reference laser beam measured at the bypass

grating. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343

6.4 Peak intensity vs. order number for the bypass grating. . . . . . . . . 344

6.5 Collimator mount and actuator schematic. . . . . . . . . . . . . . . . 345

6.6 Lab test setup for tip/tilt/focus tests. . . . . . . . . . . . . . . . . . . 346

6.7 Actuator hysteresis test data. . . . . . . . . . . . . . . . . . . . . . . 347

6.8 Photograph of prototype IMCS setup in the lab. . . . . . . . . . . . . 348

6.9 Photograph of the laser combination block. . . . . . . . . . . . . . . . 349

6.10 Photograph of MODS collimator structure. . . . . . . . . . . . . . . . 350

xvi

6.11 Photograph of lab setup detectors. . . . . . . . . . . . . . . . . . . . 351

6.12 Output of quad cell channel voltages. . . . . . . . . . . . . . . . . . . 352

6.13 Performance of IMCS for small-scale fluctuations. . . . . . . . . . . . 353

6.14 Performance of IMCS for large-scale fluctuations. . . . . . . . . . . . 354

6.15 Photograph of the MODS1 instrument on its handling cart. . . . . . . 355

6.16 Results of an IMCS rotation test. . . . . . . . . . . . . . . . . . . . . 356

6.17 “Seeing disk” of the IMCS in the MODS instrument. . . . . . . . . . 357

xvii

Chapter 1

Introduction

As a graduate student at Ohio State I have studied both Astronomy and

Astronomical Instrumentation, and I have completed projects involving both

development of telescope instrumentation and observational astronomy. Hence, this

is a dissertation in two parts. First I discuss an observational campaign to study

metal-poor subdwarf stars in the nearby halo of the Milky Way Galaxy. I then

describe an instrumentation project that produced a flexure compensation system

for the MODS spectrograph, which Ohio State is currently building for the Large

Binocular Telescope.

1.1. Mapping the Local Galactic Halo

Some of the first observations made in modern astronomy were of stars near the

sun. These stars are nearby, and are generally brighter than more distant stars. Early

in the Twentieth Century it was noticed that some of the stars exhibit strong lines in

their spectra while others have much weaker absorption features. Furthermore, these

weak-lined stars were often bluer and fainter than their strong-lined counterparts.

1

It was not long before astronomers noticed that these stars share spectral

characteristics with globular clusters, known to be the oldest objects in the Galaxy.

It was conjectured that the stars near the Sun comprise two distinct groups.

Population I stars, like the sun, are young and inhabit the space defined by the

spiral arms of the Galaxy, i.e., the disk. Population II stars are much older, and are

found in a larger volume of space, the halo. Hence, the halo must have been formed

long ago, while the disk is a more recent addition to the Galaxy.

Theorists postulated about how the Galaxy came to be. In the seminal work

of the time, Eggen, Lynden-Bell, & Sandage (1962) proposed that the Galaxy was

formed via monolithic collapse of a gas cloud. Using kinematically-selected stars

and information about the proposed halo stars’ abundances, it was concluded that

the halo must have been created by a rapid collapse of gas as the Galaxy was

being born. Since then the Eggen, Lynden-Bell, & Sandage (1962) theory has been

challenged by many authors, although some of its conclusions still hold today. The

main counterpoint to the Eggen, Lynden-Bell, & Sandage (1962) theory is that of

Searle & Zinn (1978), which states that the halo was formed by accretion of galaxies

and groups of stars that ventured too close to the Milky Way. This theory has

been gaining credence in recent years as more and more groups of stars are found

in the halo that appear to be relics of these merger events. The Searle & Zinn

(1978) theory also agrees with the hierarchical merging scenario thought to be the

formation mechanism for distant elliptical galaxies. Although these theories have

2

existed for a long time, the puzzle has certainly not fully been solved. In particular,

the question of why the oldest stars in the Galaxy are composed of the particular

elements we observe in their atmospheres has not yet been answered. Work is still

needed to find and observe these relics of the early Galaxy.

To this end, I have selected a sample of local halo stars in order to study their

abundances and kinematics. Many of the stars uncovered in this study have never

been observed before spectroscopically. I show that this technique very efficiently

finds metal-poor halo stars and I discover several interesting groups of stars.

In this work I apply a technique recently improved upon in the literature to

forming a sample of candidate halo stars. The sample is selected from the revised

NLTT catalog of Gould & Salim (2003) and Salim & Gould (2003) via a reduced

proper motion diagram. I present accurate and precise (i.e., generally good to 0.015

mag) optical photometric observations for 635 stars in this sample. These data,

combined with existing 2MASS infrared photometry, represent the most complete

and accurate set of data for a sample of stars of this type.

Arguably the most interesting objects in the halo are the most metal-poor

stars. These ancient objects are relics of the early Galaxy, and are thought to have

been formed before the gas from which they were born was heavily polluted by

elements formed in earlier generations of stars. These most metal-poor stars provide

information about the chemical abundances in the early Galaxy that is difficult to

3

obtain in any other way. Indeed, in recent years there has been much work done on

searching for the most metal-poor stars in the Galaxy. While the present study was

not conceived with the intention of finding very metal-poor stars, I report discovery

of 28 stars with [Fe/H]< −2, a fraction of metal-poor stars comparable to other

surveys constructed for just this purpose. I present the metallicities of these stars

and discuss the distribution of metallicities in more detail.

Of recent interest to stellar astrophysicists are so-called carbon-enhanced

metal-poor stars. It has been noticed that at lower metal abundances the fraction of

carbon-enhanced stars rises, although the reason for this remains unclear. Only of

order 100 of these stars are currently known; more stars of this type need to be found

and studied to understand the physics of these anomalous objects. In the present

work I discover four new carbon-enhanced metal-poor stars to add to this group.

One of the biggest problems encountered when studying metal-poor stars is

that the theoretical models are not well-calibrated for stars very different from

the sun. One of the motivations of this work from the beginning was to compare

the new, accurate observational data to the theoretical models in order to better

understand how to develop the models in the future. To this end I compare the

photometric data to theoretical isochrones, and carry the comparison further by

grouping the stars by metallicity and then comparing with the models. I find overall

good agreement with the models; future work with theoretical astrophysicists will

result in refinement of the models based on these data.

4

Since the theory of halo formation via accretion of satellites was put forward

nearly three decades ago by Searle & Zinn (1978), astronomers have been searching

for signs of accretion events lingering in the Galactic halo. Several groups have

been successful, and it is now established that at least part of the mass of today’s

halo comes from these merger events. Merger remnants of all different sizes are

observed in the halo today, from the Sagittarius dwarf spheroidal galaxy which

is just now beginning the process of merging with the Milky Way and shows the

beginning signs of tidal disruption to small groups of five to tens of stars moving

with common velocities in the halo. The present dataset is ideally suited to search

for such structures. The subdwarfs are kinematically selected; each has a measured

proper motion. In combination with distances, estimated from the spectroscopy

and photometry, and measured radial velocities, three-dimensional space velocities

may be calculated. In this work, I search the kinematic data for structures of stars.

I find two small moving groups composed of three stars each. These groups are

likely remnants of merger events in the history of the Galaxy. I also report on an

anomalous structure discovered in the reduced proper motion diagrams produced

with the new photometry, and discover another, larger, possible group of stars

moving through the local halo. As pointed out by several authors recently, the

existence of such groups confirm that at least part of the Galactic halo has been

formed through accretion of stars not formed in the Galaxy.

5

1.2. An Image Motion Compensation System for the


Astronomy is a purely observational science: we are unable to conduct

experiments on our subject because they are too far away (and too hot) to approach.

Hence we must rely on passive observations of the very distant and foreign objects

that are the subject of the study of Astronomy.

Progress in this field is intimately linked to technological advances in the tools

used to make observations. From the time Galileo turned the first telescope to the

sky, astronomers have used technology and instrumentation to aid their observations.

Over the history of astronomy each new development and discovery has relied, at

least in part, on the work of astronomers and engineers to develop larger, more

advanced, or more innovative tools with which to study the sky.

Optical astronomy continues in this tradition today, building ever larger

telescopes to peer ever deeper into space. As the size of telescopes grows larger

and larger, up to the world’s largest telescope, The Large Binocular Telescope,

the accompanying suite of instrumentation grows in size as well. Today’s cameras

and spectrographs are as large themselves as the telescopes built thirty years

ago. As such, new and different problems are encountered with each generation of

instrumentation.

6

One problem encountered with large instruments on large telescopes is the issue

of flexure in the instrument, or structural bending due to gravity. As instruments

become larger, and especially longer, their structure is prone to distortion as the

telescope is pointed at different locations in the sky. This is a problem especially in

large spectrographs, which generally have very long light paths over which flexure

could distort the science light. In a spectrograph, the light on a specific place on

the detector is associated with a wavelength; bending of the instrument during an

integration could cause the incoming light to move, implying a shift or blurring out

in wavelength that is not caused by the astronomical object.

The problem of flexure is especially relevant to the Multi-Object Double

Spectrograph (MODS), a pair of two-channel optical spectrographs that the Ohio

State Department of Astronomy Instrument Sciences Lab is currently building for

the Large Binocular Telescope (LBT). MODS is a Cassegrain-mounted spectrograph

measuring nearly 4 meters long, creating a very long lever arm that protrudes from

behind the primary mirror of LBT. Its long length and lack of other support make

it especially prone to structural bending from gravity. Despite careful engineering

and design work, the uncorrected instrument flexes 500 microns in the lab as the

telescope is pointed across the sky; this amount of flexure is unacceptable if the

spectrograph is to fulfill its scientific goals.

An innovative solution to the problem of gravitational flexure in MODS has

been developed and is described in this work. The Image Motion Compensation

7

System (IMCS) is a closed-loop compensator for image motion, and in fact corrects

for motion in the focal plane due to not only gravity, but also temperature

fluctuations, mechanism flexure within the instrument, mechanical “ticking”—any

source of possible image motion. The IMCS has been designed, developed, and is

currently operational inside the MODS instrument in the instrument assembly area

in the Department of Astronomy laboratories. It performs to within its specifications

and will permit the types of observations planned with MODS on the LBT telescope.

This method of correcting for flexure compensation is one of the most complete

and thorough techniques currently implemented in any large spectrograph. Other

solutions are possible but often do not function as well the IMCS. The methodology

developed in the IMCS will make MODS function very well, but this system will

also be important to consider when developing future instrumentation for the

next generations of even larger telescopes. In particular, the success of the IMCS

implies that even incredibly large and seemingly unsupportable instruments may

be constructed for large telescopes, and if outfitted with a system like the IMCS

will be able to perform as required as the telescope moves across the sky. Including

systems similar to the IMCS in next-generation instruments will enable astronomers

to continue to build large instruments to use with the next generation of extrmely

large (30 meter) telescopes being planned for the future.

8

1.3. Scope of the Dissertation

The dissertation is composed of two subjects: observational astronomy and

instrumentation. In Chapter 2 I describe the photometric survey of candidate halo

subdwarfs. Chapter 3 presents the spectrophotometric results, including measured

metallicities, radial velocities, spectral types, and effective temperatures of a subset

of the sample. In Chapter 4 I discuss the kinematic properties of the sample,

including the discovery of two moving groups of stars and a larger proposed merger

remnant in the solar neighborhood. Chapter 5 discusses the metallicity distribution

of the stars in the sample. Finally, in Chapter 6 I discuss the design, lab-testing,

and on-instrument performance of the Image Motion Compensation System for the

Multi-Object Double Spectrograph.

9

Chapter 2

Mapping the Local Galactic Halo. I. Optical

Photometry of Cool Subdwarf Candidates

2.1. Introduction

Cool subdwarfs are metal-poor main sequence stars that lie “below” the

solar-metallicity main sequence. First discovered as stars with high proper motions

residing between white dwarfs and main sequence stars on local color-magnitude

diagrams (Adams 1915), these objects were originally known as “intermediate white

dwarfs” and were later termed “subdwarfs” by Kuiper (1939). These low-mass stars

have lifetimes longer than the age of the Universe and offer key insights into the

history of the Galaxy. Rather than being less massive than their dwarf counterparts

of the same temperature, they are in fact bluer at a given luminosity as a result of

their reduced metal opacity (Roman 1954). Generally presumed to be members of

the Galactic halo population, these metal-poor stars provide detailed information

on the halo population and thereby about Galactic chemical enrichment history,

Galactic formation mechanisms, and the Galactic merger history. Furthermore, they

enable the study of more distant Population II objects, such as the distances and

10

ages of Galactic globular clusters (Roman 1954; Reid 1997; Gratton et al. 1997; Reid

& Gizis 1998; Carretta et al. 2000).

As members of the halo, cool subdwarfs are generally moving relatively faster

than local thin and thick disk populations. Their high proper motion makes it

straightforward to select candidate subdwarfs from a proper motion survey. The past

few decades have yielded several notable efforts to compose large-scale proper motion

surveys. The New Luyten Two-Tenths (NLTT) Catalog (Luyten 1979, 1980), along

with its better known counterpart, the Luyten Half-Second Catalog (LHS; Luyten

1979) is one of the first attempts to compile an all-sky high proper motion survey.

The NLTT contains stars with proper motions > 0.′′018. A significant disadvantage

of the original NLTT is the large errors in the catalog’s absolute astrometry, as well

as its highly inaccurate photographic photometry. Nonetheless, the LHS and the

NLTT have been the basis of numerous subdwarf studies (Ryan 1989; Gizis 1997;

Gizis & Reid 1997; Yong & Lambert 2003).

With the release of more modern all-sky surveys (e.g., the Two Micron All

Sky Survey (2MASS), Skrutskie et al. 1997, and the Digitized Sky Survey), high

proper motion stars from the NLTT can be matched with improved datasets to

obtain better astrometry and photometry. The revised NLTT (rNLTT, Gould &

Salim 2003; Salim & Gould 2003) is an example of such work. The rNLTT matches

∼36,000 of the ∼ 59,000 original NLTT objects to more modern optical astrometry

and photometry as well as to 2MASS infrared photometry. More recently, Lepine &

11

Shara (2005) have composed an even more complete proper motion catalog, LSPM,

which searches for high proper motion stars in two epochs of the Digitized Sky

Survey. These works present improved astrometry compared to the original NLTT

catalog, as well as, in the case of LSPM, superior proper motion measurements

based on modern astrometric data. Unfortunately, however, modern studies of cool

subdwarf populations still rely on the inaccurate optical photographic photometry

of existing all-sky surveys. Moreover, most of these surveys simply assume halo

membership based on a star’s proper motion. Few accurate photometric studies of

large samples of confirmed subdwarfs have been completed.

Despite these shortcomings, proper motion catalogs may successfully be used

to study distinct populations of high proper motion stars. Samples of stars may be

divided by luminosity class using a reduced proper motion (RPM) diagram, which

combines proper motion and observed brightness to serve as a proxy for luminosity,

and thereby separates stars into main sequence dwarf, subdwarf, and white

dwarf populations. A RPM diagram makes it straightforward to select candidate

metal-poor subdwarf stars with which to study the Galactic halo population.

This paper introduces a detailed analysis of the properties of a statistically

significant sample of metal-poor subdwarfs. To this end, accurate optical photometry

is obtained and a new RPM diagram for this sample of candidate halo subdwarfs

in the nearby halo is derived. Finally, a color-color diagram of these objects is

presented, which may provide a calibration source for isochrones of old metal-poor

12

populations. In forthcoming papers, spectroscopic confirmation of these stars’

spectral types, as well as measured metallicities and kinematics, will be presented.

2.2. Sample Selection

A major contribution of the original NLTT, in addition to the impressive proper

motion catalog, is the use of an optical RPM diagram to sort the catalog’s stars

by luminosity class. Reduced proper motion is effectively a proxy for luminosity; a

RPM diagram can therefore be thought of as a rough Hertsprung-Russell diagram.

The reduced proper motion, HM , is defined as

HM = m + 5logµ + 5, (2.1)

where m is the apparent magnitude and µ is the proper motion of the star in seconds

of arc per year.

Subdwarfs are distinguishable from solar-metallicity dwarfs in a RPM diagram

because they are moving faster and are more metal-poor (and therefore bluer) at

a given luminosity than main sequence stars. White dwarfs are further separated

from halo and disk populations due to their extremely small size at the same color.

Unfortunately, the RPM diagram constructed by Luyten is based on photographic

photometry and so has a very short color baseline (B − R) and highly inaccurate

photometry, making selecting anything but white dwarfs from the sample rather

13

difficult. Salim & Gould (2002) solve this problem by plotting a much longer

optical-infrared (V − J) baseline and thereby construct a RPM diagram that is more

effective at sorting these objects; in particular, a sample of subdwarfs selected via a

V − J RPM diagram should have very little contamination by non-subdwarf stars.

The stars for this study were selected from the rNLTT catalog. The RPM

diagram of all the stars in the rNLTT is shown in Figure 2.1. Main sequence dwarfs,

subdwarfs, and white dwarfs are readily separated from each other in this diagram.

As in Salim & Gould (2003), the discriminator lines separating the luminosity classes

are drawn at η = 0 and η = 5.15, where η is defined as

η(HV , V − J, sin(b)) = HV − 3.1(V − J) − 1.47| sin(b)| − 7.73, (2.2)

and b is the galactic latitude of the targets. The discriminator lines presented here

are drawn for a sample of low Galactic latitude b = ±30.

In selecting candidate subdwarfs for this study, the constraints on subdwarf

membership are tightened by restricting the sample to 1 < η < 4.15 to minimize

contamination from non-subdwarf stars. The sample is further limited to stars

with V < 16 mag to enable spectroscopic follow-up observations with reasonable

integration times at 2-m class telescopes. The sample is relatively uniformly

distributed in right ascension about the sky, with declinations of −20o < δ < +20o.

The candidates were chosen to be equatorial in order to simplify observational

14

techniques for the spectroscopic portion of this survey (i.e., obviating the need

to rotate the spectrograph and align the slit with the parallactic angle at each

observation, when the observations were made as the candidate transits the meridian

and a north-south slit was used for all observations). These criteria yielded 738

subdwarf candidates, observable from both the northern and southern hemispheres.

The RPM diagram of the selected candidate subdwarfs using rNLTT

photometry is presented in Figure 2.2. It should be noted that very little work has

been done to date on confirming the spectral types of candidate subdwarfs culled

from a RPM diagram; in the present work the stars falling in the subdwarf region of

the RPM diagram are simply assumed to be metal-poor stars. In Chapter 3, these

stars will be spectroscopically confirmed to be subdwarfs.

A histogram of the rNLTT magnitudes of the selected candidates is shown in

Figure 2.3. Figure 2.4 plots the equatorial positions of the candidate subdwarfs.

Some regions within the declination limits contain no candidates; this is due to the

sky coverage of the 2MASS second incremental data release, from which the rNLTT

is drawn.

2.3. Observations and Data Reduction

Optical photometric measurements of 635 of the 738 candidates in the sample

were obtained. For many of these, in particular the brighter candidates, multiple

15

observations were obtained as a check of the photometry as well as to look for

possible variability.

Photometric observations were obtained at the Cerro-Tololo Inter-American

Observatory (CTIO) on the 0.9m telescope during 2003 and on the 1.0m telescope

in 2004, and at the MDM Observatory 1.3m telescope during 2003 and 2004. See

Table 2.1 for a list of the specific nights photometric data were obtained. The

2048x2046 CCD detector (0.′′396 pixels) with the standard Johnson/Kron-Cousins

filter set was used at the CTIO 0.9m telescope. The observations obtained at the

CTIO 1.0m telescope were part of an engineering run for a new filter wheel with

Johnson/Kron-Cousins filters. A 512x512 Apogee camera with 0.′′469 pixels was

used for this run. The first two runs at the MDM 1.3m telescope used one set of

Johnson/Kron-Cousins filters, while the remaining runs used a different set of filters

identical to those at the CTIO 1.0m. The 1024x1024 “Templeton” CCD detector

(0.′′50 pixels) was used for all MDM observations.

Observations in BV RI filters were obtained for each candidate; integration

times were selected to achieve a formal signal-to-noise ratio (S/N) �100 for the

brighter (12 < V < 14) targets (without saturating the detector), and a S/N ∼ 100

for the fainter (14 < V < 16) targets. Candidates with V < 12 were generally too

bright to observe with these telescopes; several nights were dedicated to observe

these targets (as well as associated standard fields, flat fields, etc.) using a neutral

density filter (ND 2.0) placed in the beam.

16

Landolt standard fields (Landolt 1992) were used to calibrate the photometry.

A Landolt field was observed approximately once per hour on each of these nights.

Care was taken to ensure the standard fields were observed at a wide range of

airmass. Standard fields were selected to contain stars with a wide range of colors;

in particular, many standards were observed with very red colors in order to better

calibrate the red colors of the candidate subdwarfs.

The flat fields were constructed carefully on every night. The CTIO 0.9m and

1.0m telescopes have very nice dome flat field systems that produce excellent flat

fields. Each afternoon dome flat fields were obtained; twilight sky flat fields were

obtained at the beginning of each night. Several nights of data were reduced with

both dome and sky flat fields and the residuals of the standard star photometry were

compared. On each of these nights, the data reduced using the dome flat fields were

fit to the standard star photometry and had a standard deviation in the fit to the

standard stars of generally about 0.009 mag in the V -band, while the data reduced

with the twilight sky flat fields had a scatter in the fit of generally about 0.015 mag.

This result was also obtained for the other color indices. Since the dome flat fields

slightly outperformed the sky flat fields at CTIO, all of the data were reduced using

only dome flat fields.

MDM Observatory did not have a dome flat field system when observations

for this project commenced. During the course of the observations a dome flat field

screen was installed (see Marshall & DePoy 2005); thereafter, dome flat fields were

17

also obtained. Due to difficulties in using the dome flat field system (the dome had

significant light leaks that prevented dome flat fields from being taken during the

day), only one set of dome flat fields was obtained on each observing run. Twilight

sky flat fields were obtained on every photometric night. For consistency, only the

twilight sky flat fields were used to flatten the MDM data. This may account for the

slightly less accurate photometry obtained at MDM (see § 2.4.2).

The data were reduced in IRAF1 using standard CCD data reduction

techniques: each frame was bias subtracted and corrected with a flat field. Exposures

shorter than 10 seconds at both MDM and CTIO were corrected for shutter timing

effects with a shutter-correction frame, which was carefully constructed once per

observing run.

Aperture photometry was performed on the standard star observations. Since

the platescale was similar at all three telescopes (≈0.4-0.5 arcsec/pixel), the same

aperture size (15 pixel radius) was used for all photometric data reduction. This

aperture was selected to be similar to that used by Landolt (1992) to derive the

original photometric measurements (14 arcsec diameter).

The measurements of all standard stars observed during each night were fit

with IRAF utilities to produce a photometric solution for each night composed of

1IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the

Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the

National Science Foundation.

18

a photometric zeropoint, a first-order extinction coefficient, and a color coefficient.

On every night there were insufficient data to detect a second-order extinction

coefficient; this term was held constant at zero. Following the suggestions of Harris

et al. (1981) to solve for a photometric solution over multiple nights at one telescope,

the zeropoint, extinction coefficient, and color coefficient were all fit for each night’s

data, then the color coefficients were averaged over each run. These averaged values

were fed back into the IRAF utility to fit for a new photometric zeropoint and

extinction coefficient. These data formed the final photometric solution to be applied

to the targets. The photometric solutions for each night are shown in Tables 2.1 and

2.2.

Photometry of the candidate subdwarfs was measured on each of these nights.

Photometric measurements of a given candidate were often obtained multiple

times and on different telescopes. This allowed the data to be cross-calibrated

and the candidates to be checked for variability. Figure 2.5 shows a histogram of

the number of observations made of the candidates. Photometric measurements

of the target stars were obtained using an approximately 4 arcsec diameter which

was then corrected to a 25 arcsec diameter aperture. A bright star on each frame

was used as a template for the aperture correction. This procedure was especially

important to obtain accurate photometry for the fainter stars in the sample, to avoid

contamination of the large aperture by background stars in longer exposures.

19

The above procedure was tested on several nights using standard star

observations. For several nights of photometric observations, the photometric

solution was checked by holding some of the standard star observations (the

“standard test field”) out of the fit to the rest of the night’s standard stars. A

photometric solution was derived using the remaining standard fields and applied to

the standard test field. The measured photometry of the stars in the standard test

field was compared to the known Landolt magnitudes of these stars. The difference

between the standard deviation of this difference for all the test stars compared with

the standard deviation of the fit to the remaining standard stars (or equivalently,

to the photometric accuracy quoted in this paper) in all cases was negligible (<

0.005 mag). Since the standard star observations sample nearly the same range of

exposure lengths and stellar magnitudes as the target stars, this test implies that

the aperture photometry described above does not introduce any errors into the

photometry of the program stars.

The photometric solution derived from the standard stars on each night was

then applied to the candidate subdwarfs.

20

2.4. Results

2.4.1. BV RI Photometry

Photometric measurements were obtained for 635 of the 748 candidate

subdwarfs. Table 2.3 presents the photometry of the candidate subdwarfs. Column

1 gives the NLTT name of each candidate subdwarf, columns 2-3 give the epoch

2000 position of each object. Columns 4-7 give the BV RI photometry measured in

this program. Columns 8-10 give the V − J , V − H, V − K photometry, where the

V -band magnitude is that given in column 4 and the infrared photometry is taken

from the 2MASS catalog. Column 11 gives the number of measurements of each

star, while column 12 contains notes on whether the star is a suspected variable.

The V -band photometry is accurate to 0.014 mag for the brighter stars and

0.024 mag for the fainter stars; similar analysis of the remaining color indices show

that B − V is accurate to 0.015 and 0.019, V −R is accurate to 0.012 and 0.014, and

V − I is accurate to 0.014 and 0.019 in the two magnitude bins, respectively. The

2MASS infrared photometry has associated errors of ∼ 0.03 mag for these stars.

A total of 1167 photometric measurements of the 635 candidate subdwarfs

were made. A histogram of the number of observations of a star is shown in

Figure 2.5. When only one measurement of a target was obtained that value is

reported. Photometry of stars with multiple measurements is determined by taking

21

the average of the photometric measurements for that star on every night and from

every telescope.

2.4.2. Errors

There are several possible sources of error in any photometric measurement.

Cosmic rays or bad pixels may contaminate the measurement on the detector. There

may be scatter in the fit to the standard stars in the derivation of the photometric

solution. Finally, the stars themselves may be variable which will cause multiple

measurements to disagree.

IRAF computes errors for each photometric measurement made using the

“phot” package. These errors are based on the number of electrons recorded by

the detector, and for the stars measured here was almost always much less than

other sources of error (< 0.005 mag), as a result of the high formal S/N of the

measurements. These errors were not used except in the rare cases that the IRAF

reported error was > 0.015 mag; in this case these measurements were discarded

from the averaged photometric values because they contained a bad pixel or cosmic

ray. Only 6 measurements were discarded for this reason. This implies about a

0.5% chance that any given single measurement of the 325 stars with only one

measurement will be similarly affected.

22

Photometric errors were computed by comparing stars with multiple

measurements. About half of the sample (310 stars) have two or more measurements.

Figure 2.6 plots, for the V -band magnitude and each color index, the standard

deviation of the multiple measurements for a given star as a function of that star’s

measured V -band magnitude. The scatter is similar for each of the colors, and is

close to 0.015 mag. There is almost no increase in scatter with magnitude in any of

the colors.

The photometric errors are calculated by comparing multiple photometric

measurements of each star with more than one measurement. The standard deviation

of all of the measurements for each star with more than one measurement are

calculated. The only stars not used in this determination are those with standard

deviations > 0.08 mag; these stars are considered to be probable variables or to have

spurious measurements and are not included in the assessment of the photometric

accuracy. The average of these standard deviations is computed. The data are

divided into two magnitude bins, V < 13.5 mag and V > 13.5 mag; these results are

presented in Table 2.4, which contains the number of multiple measurements and

the average standard deviation of these measurements from which the photometric

error is derived. For example, the first four rows of Table 2.4 give information on

the multiple measurements in the V -band. The first two rows give the number and

standard deviation of the measurements obtained at each site (and show that the

photometry obtained at CTIO is more accurate by 0.007 mag in the V -band). The

23

third row gives information on the stars that were measured at both sites, while the

fourth row gives information on all measurements of the targets, whether at both

sites or at only one or the other. That the “All” row generally has smaller standard

deviation than the “Both” row is simply due to the fact that there were generally

more stars measured at CTIO, from which is obtained more accurate photometry.

A similar process was used to compute the accuracy of the remaining three color

indices.

The difference in accuracy between the different color indices may be due to a

number of factors; for example, the B − V color index may be influenced by lower

S/N in the B-band observations. The I-band observations have slightly higher

errors, perhaps due to slight fringing in the CCD chip at long wavelengths. The

V − R color index does not suffer from either of these problems and so is the most

accurate. The V -band magnitudes have higher standard deviations simply because

with the techniques used here it is easier to measure a differential color than to

measure an absolute flux.

In order to ascertain that these errors are a valid representation of the accuracy

and precision of the data, the standard star fitting technique used to derive a

photometric solution on each night was tested on several nights using standard

stars. As discussed above, several Landolt fields were reduced as target stars and

used to check the photometric solution and in particular to measure how well the

photometric solution derived on each night fit the data. Since the standard stars

24

reproduced the known Landolt magnitudes with the same accuracy as the fit to

the standards, the fitting of the standard star measurements is not introducing

errors into the photometric solution, and therefore the photometric data reduction

technique is appropriate. This implies that the photometric solutions derived on each

night fit the data well, and that the standard deviations of the fit to the photometric

solutions reliably reflect how well the derived photometric solutions fit the data.

Finally, errors may be introduced by variability in the candidate stars. While

it is not expected that these late-type, metal-poor halo stars would be variable,

it is not impossible that a few stars in the sample will exhibit a small amount of

variability. As can be seen in the top panel of Figure 2.6, nine candidate subdwarfs

have standard deviations in the V -band magnitude significantly larger than the

rest of the sample, which could plausibly be due to variability. All of these stars

had only two measurements each; the apparent variability may be due in some

cases to a spurious measurement. However, there is no reason to expect that these

measurements are less accurate than the rest of the measurements. It may be

concluded that up to ∼ 3% of the sample may be variable at the 10-20% level.

Further photometric measurements are required to confirm this variability.

25

2.4.3. Comparison with rNLTT Photometry

The photometric measurements contained in the rNLTT are derived from

several photometric catalogs: photometry of brighter stars is drawn from the

Hipparcos (ESA 1997) and the Tycho-2 (Høg et al. 2000) (see Gould & Salim 2003)

and is reported for most stars brighter than V =12 mag, the remaining photometry

is taken from the USNO-A catalog (Monet 1996, 1998; Salim & Gould 2003).

Figure 2.7 compares the V -band photometry of the entire sample of 635

candidate subdwarfs to the photometry presented in the rNLTT. The inset in

Figure 2.7 is a blow-up of the same figure, but plots only the stars contained in

the Hipparcos and Tycho-2 catalogs. The errors associated with the Hipparcos

photometry are about 0.002 mag, while the Tycho-2 photometric errors are

about 0.10 mag. There are three obvious outliers in the Hipparcos subsample.

In one of the three cases, the outlier is a member of a binary (NLTT18347, at

V = 10.2, V -VHipp = −0.19), which almost certainly is responsible for the discrepant

photometric measurements. This star has 3 measurements that agree to 0.016 mag,

and so is unlikely to be a spurious measurement. The remaining two outliers have

only one measurement each, and so could plausibly be erroneous measurements,

although this seems unlikely given the precision of the current work described above.

These outliers might be due to misidentification in the rNLTT catalog or very long

period variability. The standard deviation of the photometric difference between

26

the V -band magnitudes measured here and those reported by Hipparcos is about

0.025 mag (when the three obvious outliers are not included in the fit), roughly

consistent with the photometric errors in this sample. Furthermore, there is almost

no photometric error in the color coefficients between Hipparcos and the present

work. However, the difference between the Tycho-2 magnitudes and those measured

here is higher than expected (about 0.25 mag).

Figure 2.8 compares the photometry of the sample of the 534 rNLTT stars

with only photometric measurements from USNO-A stars to the present work. The

rNLTT reports photometric accuracy for these stars of about 0.25 mag. The points

are fit to a line and outliers are recursively discarded until the largest outlier is less

than 3 σ from the line. This process rejects 19 points. The remaining 515 points are

described by

Vthiswork − VUSNO−A = 0.011 + 0.085(Vthiswork − 14). (2.3)

The remaining standard deviation from this fit is 0.27 mag, roughly consistent

with the errors given for the USNO-A photometry. This discrepancy between

USNO-A photometry and other photometric systems is also noted by Gould et al.

(2005). They derive a similar trend when comparing rNLTT photometry to SDSS

photometry.

27

2.4.4. An Improved RPM Diagram

The improved RPM diagram based on the new observations is presented

in Figure 2.9. There was apparently very little contamination of the original

sample by white dwarfs; only three stars in this diagram appear to the left of the

subdwarf sequence. There are also 12 stars that have scattered to lie on or near

the main sequence boundary, but overall there appears to be little contamination

due to the poor photometry of the rNLTT. Furthermore, there appears to be little

contamination by other stars (such as giants) in this sample, however, this will be

confirmed more concretely by spectroscopic measurements of the spectral types of

the candidate subdwarfs.

The distribution of points in the improved RPM diagram is expected to be

homogeneous; regions of higher density points, such as that seen in the blue half

of the subdwarf sequence in Figure 2.9 are not expected. In fact, a collection of

points in the RPM diagram could be due to a large group of stars having a common

proper motion, i.e., they could be members of a moving group in the nearby Galaxy.

This possibility was investigated by attempting to fit the stars in this apparent

group to a common space velocity given their measured proper motion and distances

estimated using the color-magnitude relation of Gould (2003). No common proper

motion could be found to explain the distribution observed in Figure 2.9; this result

is consistent with the conclusion of Gould (2003) regarding the paucity of large

28

local streams. The possibility that this overdensity of stars is in fact a moving

group will be investigated in more detail with radial velocities measured from the

spectrophotometry of these stars.

2.4.5. Color-Color Diagram

Finally, to demonstrate that these stars are all drawn from a common

population, a color-color diagram is constructed. Figure 2.10 shows the BV I

color-color diagram for the sample. The stars in this study generally form a tight

sequence, consistent with them being from one population. Overplotted on this

figure are Yonsei-Yale (Y2; Kim et al. 2002) isochrones for a 10 Gyr population with

[α/Fe] = 0. Note that the photometry presented in this work agrees most closely

with a metal-poor population, i.e., it is not consistent with the [Fe/H]=0 isochrones.

No attempt was made to fit these isochrones to the data, rather, this figure is

included to illustrate that the sample stars most likely represent an old, metal-poor

population. Note that these data are not inconsistent with the metal-poor Y2

isochrones, but neither are they perfectly consistent with them. A dataset of high

photometric accuracy and precision, such as that presented here, may be useful for

calibration of these old, metal-poor isochrones.

29

2.5. Summary and Future Work

Improved BV RI photometry for a large sample of halo subdwarf candidates

selected from a RPM diagram has been presented. These measurements are precise

and are generally accurate to 0.015 mag, representing a significant improvement on

photometry currently existing for these stars.

A revised RPM diagram for these candidate subdwarfs has been presented.

The lack of apparent contamination in the subdwarf region by white dwarf and

solar-metallicity dwarf stars suggests that even the less accurate photometry of

the rNLTT is adequate to select samples of subdwarfs from a RPM catalog. In

Chapter 3, spectrophotometric measurements of the spectral types of these candidate

subdwarfs will confirm this conjecture.

A color-color diagram of these objects is derived that may prove useful in

calibrating theoretical models of these types of stars. Future work on this subject

includes a more detailed comparison with the model isochrones to inform future

theoretical models.

Forthcoming spectroscopic measurements of these candidate subdwarfs will

provide kinematic and metallicity information that will allow detailed studies of the

halo subdwarf population. This sample of halo stars will be useful for future studies

30

of the Galactic halo population, Galactic formation mechanisms, and Galactic

chemical enrichment history.

Finally, these photometric measurements along with spectroscopic confirmation

of these candidate subdwarfs, when combined with distance measurements from

a future astrometric mission such as SIM, will provide an excellent dataset from

which to calibrate Galactic globular cluster color-magnitude diagrams and will

provide more accurate distance and age measurements of globular clusters than has

previously been possible.

31

Fig. 2.1.— Reduced proper motion diagram of the complete rNLTT. Solar-metallicity

dwarfs, metal-poor subdwarfs, and white dwarfs are well separated. Discriminator

lines separate the populations and are drawn at η = 0 and 5.15. The sample presented

in this work was drawn from the central “subdwarfs” region.

32

Fig. 2.2.— Reduced proper motion diagram of the candidate subdwarfs selected for

this work. Candidates were selected between η=1 and 4.15, with a limiting magnitude

of V =16.

33

Fig. 2.3.— Histogram of rNLTT magnitudes of the 738 stars in the candidate

subdwarf sample.

34

Fig. 2.4.— Positions of the candidate subdwarfs. The selection criteria includes

declination limits of −20o < δ < +20o. The rNLTT uses the 2MASS second

incremental release, which accounts for the lack of points from 0o < δ < +10o and

near RA =−110xo.

35

Fig. 2.5.— Histogram of the number of observations obtained of the candidate

subdwarfs. The stars with zero observations are those that met the selection criteria

but were not observed in this study.

36

Fig. 2.6.— Standard deviation of multiple measurements of a given star as a function

of that star’s V -band magnitude, given for V -band magnitude, and the B−V , V −R,

and V − I color indices. Nine stars have a standard deviation in the V -band of >

0.08 mag; these are due to either low-level variability or spurious measurements.

37

8 10 12

-0.5

0

0.5

Fig. 2.7.— Comparison of the photometry presented in this work to that of the

rNLTT. The inset shows only stars with Hipparcos and Tycho-2 photometry. Filled

circles in the inset show Hipparcos stars, crosses show Tycho-2 stars. The standard

deviation of the Hipparcos stars is 0.026 mag, while that of the Tycho-2 stars is 0.26

mag. The remaining stars in the main figure have only USNO-A photometry.

38

Fig. 2.8.— Comparison of the photometry of rNLTT stars with only USNO-A

photometry with the photometry presented in this work. Recursively discarded 3-σ

outliers are plotted as crosses. The remaining points are fit with Vthiswork−VUSNO−A =

0.011 + 0.085(Vthiswork − 14). The scatter about this line is 0.27 mag.

39

Fig. 2.9.— Reduced proper motion diagram of the sample using improved photometry.

Three stars now fall to the left of the lower discriminator and are likely to be white

dwarfs. Twelve stars lie on or near the upper discriminator and may be main sequence

stars. The overdensity of points on the blue side of the diagram could signify a group

of stars with common proper motion, however, a common space motion could not

be fit to cause these stars to form a moving group. This possibility will be further

investigated using spectroscopic observations of these stars.

40

Fig. 2.10.— BV I color-color diagram for the sample. Overplotted are Y2 isochrones

of a 10 Gyr population with [α/Fe]=0 for [Fe/H]=0, −1, −2, and −3. The sample

is clearly representative of a metal-poor population. None of the isochrones fit the

data very well; these highly accurate and precise data may be used to calibrate future

theoretical isochrones.

41

B V

Telescope Date Zero Point Extinction Color Zero Point Extinction Color

MDM 1.3m 21 Mar 2003 −22.613 0.329 −0.044 −22.732 0.238 0.012

MDM 1.3m 24 Mar 2003 −22.568 0.222 −0.044 −22.692 0.133 0.012

MDM 1.3m 16 Oct 2003 −22.688 0.219 −0.030 −22.754 0.105 0.003

MDM 1.3m 17 Oct 2003 −22.707 0.248 −0.030 −22.794 0.145 0.003

MDM 1.3m 18 Oct 2003 −22.806 0.320 −0.030 −22.820 0.162 0.003

MDM 1.3m 19 Oct 2003 −22.757 0.271 −0.030 −22.731 0.077 0.003

MDM 1.3m 21 Oct 2003 −22.679 0.223 −0.030 −22.785 0.127 0.003

MDM 1.3m 22 Oct 2003 −22.698 0.243 −0.030 −22.785 0.132 0.003

(cont’d)

Table 2.1. Nightly Photometric Solutions for B and V

42

Table 2.1—Continued

B V


MDM 1.3m 04 Dec 2003 −22.709 0.237 −0.024 −22.752 0.123 0.013

MDM 1.3m 06 Dec 2003 −22.702 0.253 −0.024 −22.767 0.135 0.013

MDM 1.3m 08 Dec 2003 −22.693 0.226 −0.024 −22.781 0.130 0.013

MDM 1.3m 02 Oct 2004 −17.714 0.279 −0.254 −18.119 0.092 −0.008

CTIO 1.0m 23 Mar 2004 −21.694 0.243 0.107 −21.826 0.127 −0.026

CTIO 1.0m 24 Mar 2004 −21.628 0.222 0.104 −21.823 0.130 −0.013

CTIO 0.9m 07 Mar 2003 −21.807 0.267 0.090 −22.016 0.151 −0.020

CTIO 0.9m 08 Mar 2003 −21.790 0.241 0.090 −22.023 0.143 −0.020

CTIO 0.9m 09 Mar 2003 −21.839 0.257 0.090 −22.028 0.133 −0.020

(cont’d)

43


B V


CTIO 0.9m 10 Mar 2003 −17.015 0.266 0.090 −17.124 0.144 −0.020

CTIO 0.9m 11 Mar 2003 −21.854 0.261 0.090 −22.037 0.135 −0.020

CTIO 0.9m 12 Mar 2003 −21.854 0.254 0.090 −22.048 0.139 −0.020

CTIO 0.9m 28 Jul 2003 −21.799 0.232 0.087 −21.989 0.123 −0.035

CTIO 0.9m 29 Jul 2003 −21.781 0.208 0.087 −21.994 0.114 −0.035

CTIO 0.9m 30 Jul 2003 −16.965 0.383 0.087 −17.150 0.149 −0.035

CTIO 0.9m 31 Jul 2003 −21.784 0.219 0.087 −21.988 0.118 −0.035

CTIO 0.9m 01 Aug 2003 −21.836 0.259 0.087 −22.026 0.148 −0.035

CTIO 0.9m 02 Aug 2003 −21.773 0.220 0.087 −21.988 0.125 −0.035

44

R I


MDM 1.3m 21 Mar 2003 −22.624 0.190 −0.042 −21.716 0.110 0.002

MDM 1.3m 24 Mar 2003 −22.587 0.091 −0.042 −21.679 0.014 0.002

MDM 1.3m 16 Oct 2003 −22.638 0.066 −0.053 −21.775 0.026 0.009

MDM 1.3m 17 Oct 2003 −22.664 0.090 −0.053 −21.784 0.035 0.009

MDM 1.3m 18 Oct 2003 −22.738 0.148 −0.053 −21.905 0.125 0.009

MDM 1.3m 19 Oct 2003 −22.604 0.024 −0.053 −21.746 −0.010 0.009

MDM 1.3m 21 Oct 2003 −22.689 0.095 −0.053 −21.911 0.128 0.009

MDM 1.3m 22 Oct 2003 −22.696 0.102 −0.053 −21.832 0.061 0.009

MDM 1.3m 04 Dec 2003 −22.620 0.069 −0.036 −21.762 0.037 0.009

MDM 1.3m 06 Dec 2003 −22.639 0.086 −0.036 −21.786 0.056 0.009

(cont’d)Table 2.2. Nightly Photometric Solutions for R and I

45


R I


MDM 1.3m 08 Dec 2003 −22.628 0.063 −0.036 −21.776 0.038 0.009

MDM 1.3m 02 Oct 2004 −18.208 0.114 −0.101 −17.364 0.008 0.028

CTIO 1.0m 23 Mar 2004 −21.803 0.094 −0.032 −20.999 0.067 −0.027

CTIO 1.0m 24 Mar 2004 −21.777 0.087 −0.031 −20.964 0.046 −0.018

CTIO 0.9m 07 Mar 2003 −21.969 0.108 −0.007 −21.118 0.059 −0.010

CTIO 0.9m 08 Mar 2003 −21.949 0.083 −0.007 −21.131 0.054 −0.010

CTIO 0.9m 09 Mar 2003 −21.967 0.089 −0.007 −21.135 0.048 −0.010

CTIO 0.9m 10 Mar 2003 −17.046 0.092 −0.007 −16.309 0.074 −0.010

CTIO 0.9m 11 Mar 2003 −21.979 0.092 −0.007 −21.138 0.046 −0.010

CTIO 0.9m 12 Mar 2003 −21.986 0.097 −0.007 −21.162 0.058 −0.010

(cont’d)

46


R I


CTIO 0.9m 28 Jul 2003 −21.947 0.079 −0.013 −21.084 0.033 −0.023

CTIO 0.9m 29 Jul 2003 −21.944 0.067 −0.013 −21.070 0.007 −0.023

CTIO 0.9m 30 Jul 2003 −17.281 0.144 −0.013 −16.580 0.082 −0.023

CTIO 0.9m 31 Jul 2003 −21.948 0.078 −0.013 −21.094 0.036 −0.023

CTIO 0.9m 01 Aug 2003 −22.027 0.144 −0.013 −21.137 0.074 −0.023

CTIO 0.9m 02 Aug 2003 −21.942 0.080 −0.013 −21.074 0.030 −0.023

47

NLTT α(2000) δ(2000) V B − V V − R V − I V − J V − H V − K n Notesa

1645 00:30:49.2 −03:51:46 14.788 1.387 0.884 1.580 2.590 3.126 3.336 2

1684 00:31:29.3 −06:18:06 15.094 1.465 0.923 1.785 2.778 3.303 3.476 1

1815 00:34:01.9 +17:32:29 15.481 0.853 0.500 0.972 1.669 2.133 2.234 1

1870 00:34:45.3 +12:01:06 13.903 0.776 0.489 0.922 1.568 1.975 2.036 1

1994 00:36:47.2 −18:50:14 14.462 0.594 0.421 0.838 1.410 1.845 1.903 1

2045 00:38:05.8 −07:04:51 13.504 0.887 0.540 1.062 1.808 2.334 2.442 1

2107 00:39:10.7 −04:43:57 15.530 1.471 0.886 1.691 2.637 3.203 3.341 1

2112 00:39:11.3 −13:56:36 14.405 0.824 0.452 0.874 1.590 2.117 2.149 1

(cont’d)Table 2.3. BV RI Photometry of Candidate Subdwarfs

48



2171 00:39:59.2 −15:34:08 14.891 0.721 0.382 0.834 1.570 2.038 2.156 1

2205 00:40:36.7 −07:29:57 13.993 1.170 0.751 1.387 2.291 2.933 2.965 1

2324 00:42:40.2 −11:32:17 15.674 1.450 1.122 2.538 2.829 3.349 3.566 1

2404 00:44:03.6 −13:55:26 12.114 0.430 0.291 0.590 1.060 1.331 1.378 1

2427 00:44:24.2 −00:37:37 13.500 0.750 0.460 0.876 1.530 1.943 2.049 2

2856 00:51:38.6 −04:10:55 14.782 1.317 0.640 1.072 1.980 2.523 2.590 1

2868 00:51:50.7 −15:31:54 13.514 1.096 0.050 0.452 0.999 1.395 1.463 1

2953 00:53:22.6 −01:58:57 15.924 1.060 0.658 1.217 2.072 2.624 2.683 1

2966 00:53:34.0 −03:18:15 15.613 1.153 0.731 1.367 2.219 2.808 2.951 1

3035 00:55:12.0 +19:04:24 15.876 1.304 0.790 1.476 2.410 2.941 3.161 1

(cont’d)

49



3516 01:03:54.3 −03:51:14 12.432 0.475 0.375 0.732 1.258 1.594 1.638 1

3531 01:04:05.3 −01:33:18 13.762 0.986 0.554 0.423 1.639 1.988 2.117 1

3808 01:08:40.5 −15:13:13 15.463 1.225 0.712 1.211 2.440 3.053 3.233 1

3847 01:09:29.0 −05:07:25 15.803 1.556 1.119 2.146 4.157 4.604 4.833 1

3965 01:11:24.6 −16:11:19 16.113 1.398 0.912 1.734 2.681 3.211 3.337 1

3985 01:11:54.5 −07:30:44 14.547 0.837 0.567 1.146 1.868 2.413 2.502 1

4245 01:16:26.8 −10:52:43 15.629 0.869 0.539 1.027 1.696 2.147 2.363 1

4285 01:17:24.7 −00:53:50 15.476 0.766 0.470 0.936 1.530 1.971 2.058 1

4447 01:20:24.7 −05:51:51 15.938 1.254 0.790 1.475 2.371 2.977 3.056 1

4517 01:21:45.9 −01:52:00 13.964 1.109 0.646 1.142 2.046 2.627 2.766 1

(cont’d)

50



4817 01:26:55.2 +12:00:26 11.358 0.502 0.338 0.679 1.132 1.441 1.476 1

4838 01:27:15.1 −06:30:21 15.448 1.332 0.835 1.575 2.482 2.969 3.236 1

4922 01:28:56.1 −01:25:09 15.397 1.243 0.768 0.968 2.382 2.901 3.085 1

5022 01:30:51.2 −04:07:29 13.989 1.272 0.659 1.438 2.406 2.976 3.074 2

5042 01:31:08.2 −15:38:26 14.426 0.992 0.548 1.029 1.826 2.416 2.437 1

5052 01:31:24.5 −18:23:12 14.137 0.912 0.645 1.423 2.370 2.897 3.053 1

5192 01:33:41.7 −01:23:41 14.325 0.773 0.388 0.790 1.535 1.970 2.029 2

5193 01:33:52.3 +13:21:22 14.640 0.623 0.545 1.084 2.369 2.835 2.858 1

5222 01:34:02.5 −12:41:55 13.640 0.418 0.237 0.462 1.106 1.404 1.470 1

5255 01:34:34.1 −16:02:11 12.061 0.539 0.368 0.695 1.205 1.507 1.512 1

(cont’d)

51



5289 01:35:07.5 −03:28:06 15.626 1.369 0.843 1.583 2.461 3.069 3.287 1

5404 01:37:00.1 −07:11:43 13.140 0.648 0.448 0.634 1.387 1.692 1.784 1

5506 01:39:10.5 +12:10:01 14.531 0.085 0.711 0.938 2.107 2.468 2.525 1

5711 01:42:47.9 −02:22:44 12.369 0.645 0.380 0.711 1.263 1.617 1.716 1

5881 01:46:09.7 +15:41:47 13.196 0.248 0.614 0.702 1.796 2.048 2.115 1

6415 01:54:32.1 −18:27:11 12.169 0.439 0.325 0.646 1.054 1.363 1.401 1

6519 01:57:09.7 +12:15:37 14.789 1.446 0.877 1.679 2.642 3.152 3.358 1

6582 01:58:01.4 −18:41:05 15.693 1.289 0.810 1.524 2.408 2.898 3.069 1

6614 01:58:49.1 +14:41:04 15.712 1.292 0.793 1.495 2.421 3.021 3.215 1

6774 02:01:31.7 −11:08:40 12.653 0.741 0.205 0.793 1.451 1.875 1.917 1

(cont’d)

52



6816 02:02:15.3 −11:35:18 16.097 1.221 0.775 1.445 2.334 2.939 3.159 1

6842 02:02:48.5 −11:07:48 14.560 0.904 0.375 0.928 1.579 1.956 2.080 1

6856 02:03:18.1 +13:04:22 16.054 1.263 0.756 1.441 2.292 2.886 3.042 1

6863 02:03:08.7 −19:02:48 15.312 0.905 0.550 1.067 1.750 2.244 2.397 1

7078 02:08:04.9 +17:39:11 14.369 0.745 0.469 0.936 1.549 1.976 2.090 1

7207 02:10:03.3 −10:08:24 14.475 0.694 0.417 0.848 1.461 1.862 1.978 2

7299 02:12:02.1 −14:00:29 11.488 0.422 0.312 0.596 0.989 1.287 1.299 2

7301 02:12:19.7 +12:49:26 14.872 1.466 1.158 2.650 2.078 2.680 3.061 1

7360 02:13:50.0 +15:59:11 13.141 1.097 0.551 1.057 2.048 2.605 2.719 1

7364 02:13:40.2 −00:05:19 12.875 0.312 0.736 0.613 1.755 2.083 2.065 1

(cont’d)

53



7415 02:14:40.3 −01:12:05 9.066 0.565 0.354 0.689 1.167 1.495 1.547 2

7417 02:14:33.9 −07:29:18 11.597 0.528 0.337 0.653 1.074 1.396 1.448 2

7439 02:14:55.5 −13:18:50 15.332 0.963 0.640 1.151 2.015 2.657 2.727 1

7467 02:15:29.7 −06:22:28 15.873 1.372 0.864 1.653 2.571 3.116 3.361 1

7596 02:17:57.6 −19:36:48 16.185 1.299 0.790 1.471 2.388 2.945 3.156 1

7654 02:19:13.7 −13:32:17 16.056 0.751 0.441 0.858 3.288 3.824 3.949 1

7769 02:21:54.7 +14:24:27 14.039 0.880 0.550 1.078 1.898 2.409 2.555 1

7914 02:24:44.5 +13:28:14 14.343 1.110 0.711 1.349 2.219 2.791 2.981 1

7966 02:25:53.8 +17:57:51 13.990 0.935 0.598 1.096 1.926 2.318 2.472 1

7968 02:25:57.1 +18:21:21 14.329 1.083 0.692 1.057 2.249 2.827 2.954 1

(cont’d)

54



8034 02:27:17.2 −03:05:24 11.803 0.438 0.327 0.651 1.080 1.378 1.394 1

8227 02:31:25.8 −16:59:05 10.470 0.420 0.311 0.599 1.005 1.267 1.337 2

8230 02:31:30.0 −15:36:48 13.475 0.782 0.650 1.291 2.094 2.652 2.775 1

8319 02:33:21.3 −06:43:41 13.149 0.231 0.751 0.993 2.151 2.524 2.517 1

8323 02:33:13.2 −19:41:19 12.858 0.623 0.369 0.811 1.594 1.969 1.988 1

8342 02:34:12.5 +17:45:51 14.911 1.679 1.059 2.299 3.507 3.978 4.202 1

8405 02:35:20.5 +18:49:31 15.823 1.196 0.769 1.451 2.334 2.986 3.096 1

8459 02:36:33.7 +17:47:13 12.605 0.632 0.521 0.870 1.494 1.809 1.871 1

8507 02:37:33.0 +14:26:57 13.927 0.958 0.587 1.115 1.881 2.435 2.525 1

8720 02:42:00.8 +13:50:05 13.426 0.698 0.442 0.871 1.480 1.825 1.940 1

(cont’d)

55



8783 02:43:22.0 +13:25:57 11.471 0.518 0.338 0.676 1.118 1.412 1.464 1

8833 02:44:11.7 −05:27:00 12.749 0.091 0.587 1.007 1.646 1.925 1.924 1

8866 02:44:39.8 −13:43:51 15.844 1.185 0.766 1.402 2.186 2.838 2.930 1

9026 02:48:20.3 −12:45:14 13.698 0.663 0.225 0.685 1.472 1.886 1.955 1

9382 02:56:47.8 +18:55:36 12.314 0.726 0.417 0.811 1.365 1.702 1.757 1

9437 02:57:41.2 −05:38:51 13.607 0.410 0.346 0.617 1.164 1.458 1.448 1

9523 02:58:54.5 −09:30:14 15.357 1.270 0.689 1.286 2.056 2.623 2.769 2

9550 02:59:17.9 −17:07:43 15.538 0.917 0.546 1.081 1.811 2.339 2.503 1

9578 02:59:49.7 −11:20:42 10.545 0.547 0.355 0.690 1.094 1.472 1.571 2

9597 03:00:23.0 −05:57:50 11.950 0.447 0.323 0.654 1.125 1.372 1.405 2

(cont’d)

56



9622 03:01:12.6 +16:19:19 14.262 0.627 0.419 0.855 1.467 1.831 1.894 1

9628 03:00:47.4 −17:16:39 13.096 0.515 0.260 0.380 1.420 1.684 1.812 1

9648 03:01:43.3 +16:10:54 14.898 1.143 0.647 1.286 2.121 2.604 2.724 1

9653 03:01:27.0 −13:05:49 15.602 1.091 0.678 1.275 2.133 2.725 2.868 1

9727 03:03:04.5 −07:01:33 15.757 1.177 0.721 1.348 2.164 2.751 2.977 1

9734 03:03:17.9 −03:07:23 14.990 1.009 0.630 1.203 1.971 2.597 2.660 1

9799 03:04:19.8 −04:02:43 15.401 1.172 0.722 1.342 2.260 2.807 2.951 1

9848 03:05:11.4 −18:06:40 16.557 1.455 0.917 1.797 2.773 3.339 3.619 1

9893 03:06:28.7 −07:40:42 14.409 1.450 0.902 1.709 2.650 3.204 3.417 1

9898 03:06:21.5 −18:18:39 14.210 0.670 0.424 0.826 1.416 1.838 1.918 1

(cont’d)

57



9938 03:07:12.6 −08:26:38 16.167 1.243 0.757 1.438 2.422 3.061 3.142 1

10018 03:08:48.9 −13:43:57 15.372 1.432 0.871 1.631 2.579 3.124 3.311 1

10022 03:08:53.2 −12:09:08 15.798 1.502 0.951 1.885 2.930 3.454 3.693 1

10119 03:10:21.7 −13:02:24 13.930 0.762 0.608 1.088 1.786 2.240 2.371 1

10135 03:11:00.8 +00:00:18 15.721 1.046 0.647 1.152 2.059 2.590 2.754 2

10176 03:11:24.7 −18:08:30 15.750 1.426 0.907 1.729 2.761 3.320 3.540 1

10243 03:13:24.2 +18:49:38 14.117 1.450 0.898 1.682 2.640 3.088 3.308 1

10401 03:15:49.0 −15:00:44 14.589 0.922 0.555 1.066 1.781 2.264 2.401 1

10517 03:18:15.7 −02:25:56 14.450 0.858 0.550 1.045 1.740 2.261 2.353 1

10536 03:18:28.9 −07:08:26 11.222 0.425 0.304 0.604 0.982 1.260 1.318 2

(cont’d)

58



10548 03:18:41.4 −07:08:11 15.916 1.258 0.795 1.495 2.425 2.987 3.159 1

10821 03:23:52.8 −17:18:21 13.388 1.014 0.908 1.638 2.643 3.188 3.380 1

10850 03:24:50.4 +12:15:24 10.749 0.565 0.355 0.711 1.201 1.506 1.602 2

10883 03:25:26.4 −02:53:16 15.872 0.716 0.438 0.949 1.569 2.002 2.090 1

10972 03:27:17.1 −14:29:32 13.977 0.785 0.490 0.954 1.718 2.156 2.258 1

11007 03:28:09.9 −15:44:49 12.225 0.504 0.332 0.657 1.086 1.427 1.452 2

11010 03:28:27.0 −01:04:24 14.085 0.608 0.412 0.823 1.373 1.780 1.838 1

11015 03:28:26.1 −11:32:01 16.293 1.497 0.957 1.890 2.946 3.519 3.667 1

11032 03:29:23.1 +18:54:52 14.217 0.819 0.506 0.974 1.647 2.182 2.312 1

11068 03:29:28.8 −19:30:04 15.443 0.800 0.505 0.985 1.673 2.179 2.269 1

(cont’d)

59



11201 03:32:38.7 −17:34:49 16.144 1.503 0.890 1.759 2.865 3.427 3.616 1

11356 03:35:55.6 −18:04:04 16.234 1.164 0.773 1.454 2.359 2.938 3.131 1

11462 03:38:15.7 −11:29:14 13.039 1.769 1.106 2.260 3.389 3.939 4.200 1

11486 03:38:46.3 −16:07:22 11.830 0.862 0.540 1.001 0.710 1.453 1.647 2

11515 03:39:27.6 −10:59:25 12.963 0.742 0.471 0.905 1.525 1.927 1.985 1

11584 03:41:02.1 −07:49:54 13.441 0.739 0.436 0.864 1.514 1.920 1.974 1

11795 03:46:12.7 −00:43:40 12.981 0.551 0.368 0.631 1.223 1.499 1.604 1

11938 03:49:25.7 −03:19:36 14.345 1.354 0.862 1.622 2.550 3.115 3.320 1

12017 03:51:12.3 −09:20:24 12.335 0.804 0.497 0.927 1.573 2.035 2.120 2

12026 03:51:21.8 −11:13:14 15.768 1.224 0.749 1.377 2.294 2.882 3.072 1

(cont’d)

60



12027 03:51:13.5 −19:53:36 15.785 1.072 0.628 1.184 1.988 2.525 2.725 1

12044 03:51:47.7 −05:33:03 15.829 1.084 0.569 1.133 1.902 2.382 2.452 1

12103 03:53:12.2 −15:26:21 11.319 0.581 0.366 0.704 1.214 1.523 1.541 2

12227 03:57:04.4 −09:52:05 14.161 0.781 0.510 0.998 1.643 2.193 2.243 1

12350 04:00:28.4 −11:16:07 12.089 0.422 0.296 0.688 1.023 1.321 1.356 3

12489 04:04:48.6 −02:22:42 14.553 0.751 0.478 0.923 1.524 1.993 2.080 1

12537 04:05:43.0 −13:21:38 14.511 0.837 0.502 0.990 1.700 2.181 2.249 1

12704 04:10:49.1 −04:11:25 15.417 0.192 0.658 1.229 1.985 2.410 2.602 1

12769 04:12:53.5 −08:16:45 14.098 0.963 0.596 1.101 1.857 2.404 2.529 1

12829 04:14:55.9 +19:47:26 14.623 1.135 0.715 1.406 2.291 2.842 3.021 1

(cont’d)

61



12845 04:14:58.1 −05:37:49 10.601 0.677 0.409 0.807 1.331 1.704 1.792 1

12856 04:15:08.3 −08:33:49 10.802 0.467 0.315 0.630 1.089 1.310 1.407 1

12876 04:15:46.1 −01:27:07 15.587 1.507 0.918 1.533 2.770 3.291 3.509 1

12923 04:16:51.0 −10:26:54 15.198 1.307 0.791 1.520 2.487 3.034 3.164 1

12986 04:18:34.5 −13:12:27 11.581 0.480 0.302 0.643 1.066 1.334 1.372 1

13022 04:19:39.2 −03:35:48 15.878 1.233 0.762 1.446 2.293 2.896 3.085 1

13173 04:23:35.2 −19:49:16 14.893 0.958 0.559 1.163 1.929 2.372 2.511 2

13344 04:28:30.5 −06:03:54 13.785 0.758 0.462 0.888 1.544 2.033 2.072 2

13368 04:29:09.3 −01:13:47 15.495 1.311 0.787 1.470 2.416 2.963 3.140 1

13402 04:30:13.1 −03:03:13 14.724 0.613 0.436 0.865 1.457 1.860 1.926 2

(cont’d)

62



13469 04:32:11.3 −07:56:36 15.067 1.334 0.861 1.563 2.504 3.042 3.248 1

13470 04:32:15.4 −03:39:07 13.753 1.117 0.629 1.155 1.968 2.515 2.633 3

13548 04:34:14.0 −13:56:03 14.131 1.224 0.778 1.459 2.333 2.888 3.081 2

13641 04:37:49.5 +19:40:10 12.932 1.211 0.734 1.410 2.294 2.909 3.076 2

13660 04:38:16.5 +12:51:03 12.358 0.924 0.568 1.073 1.842 2.309 2.459 3

13694 04:39:04.8 −08:51:07 15.352 1.157 0.687 1.318 2.174 2.826 2.910 1

13706 04:39:30.8 −01:08:41 14.478 0.935 0.623 1.160 1.983 2.564 2.666 2

13770 04:42:00.0 −04:16:47 12.444 0.614 0.387 0.757 1.296 1.629 1.747 4

13811 04:43:09.3 −03:09:37 13.442 0.555 0.380 0.743 1.256 1.646 1.668 3

13899 04:45:31.0 −13:30:43 12.274 0.602 0.405 0.813 1.379 1.772 1.841 3

(cont’d)

63



13920 04:46:11.7 −08:23:41 14.434 0.722 0.456 0.908 1.599 2.013 2.141 2

13940 04:47:25.4 +17:58:37 14.370 1.256 0.786 1.456 2.374 3.032 3.185 1

14020 04:49:31.7 −15:54:25 14.549 1.387 0.844 1.570 2.545 3.042 3.231 2

14091 04:52:22.1 +16:18:29 13.860 1.070 0.651 1.258 2.118 2.581 2.786 2

14131 04:53:17.3 −03:57:46 13.441 0.724 0.436 0.865 1.520 1.874 1.990 3

14136 04:53:21.2 −09:24:31 15.036 0.822 0.541 1.002 1.620 2.178 2.315 1

14169 04:55:33.3 +16:12:43 13.409 0.752 0.488 0.986 1.721 2.144 2.206 2

14175 04:55:17.3 −10:22:45 15.669 1.265 0.783 1.450 2.369 2.924 3.184 1

14197 04:56:23.3 +14:55:11 12.413 0.891 0.556 1.083 1.828 2.360 2.478 3

14218 04:56:24.7 −15:04:24 14.183 0.721 0.463 0.891 1.509 1.965 2.009 2

(cont’d)

64



14299 04:59:12.0 −10:16:36 13.939 0.554 0.380 0.762 1.241 1.699 1.721 2

14391 05:02:17.2 +15:32:41 13.518 0.847 0.510 0.999 1.685 2.220 2.351 2

14408 05:02:20.9 −19:32:02 14.721 1.374 0.944 2.008 3.048 3.564 3.784 2 1

14450 05:04:26.8 +15:49:20 14.741 1.143 0.688 1.312 2.168 2.650 2.815 1

14507 05:06:20.4 −13:11:26 13.936 0.970 0.612 1.151 1.879 2.523 2.603 2

14549 05:08:12.8 −05:41:24 14.509 0.874 0.555 1.068 1.804 2.342 2.467 2

14606 05:10:16.0 −07:51:35 12.756 0.569 0.355 0.702 1.202 1.532 1.562 3

14618 05:10:41.7 −04:26:51 14.604 1.027 0.708 1.279 2.207 2.733 2.910 2

14658 05:11:42.5 −14:00:30 11.700 0.508 0.319 0.636 1.062 1.339 1.405 3

14805 05:16:56.7 −00:11:42 11.596 0.426 0.508 0.645 1.076 1.295 1.406 1

(cont’d)

65



14822 05:17:32.3 −06:11:22 12.683 0.900 0.541 1.012 1.672 2.224 2.328 3

14863 05:18:50.3 −11:54:20 15.359 1.483 0.956 1.881 2.880 3.430 3.593 1

14864 05:19:01.3 −05:53:45 14.260 0.942 0.568 1.125 1.844 2.354 2.503 2

14888 05:19:50.5 −07:00:05 14.321 1.002 0.649 1.230 2.021 2.672 2.792 2

14977 05:23:02.3 −08:38:17 14.705 0.887 0.610 1.194 1.999 2.570 2.665 2

15002 05:23:56.7 −10:56:01 13.824 0.775 0.489 0.950 1.627 2.049 2.166 2

15039 05:25:25.5 −02:19:09 14.757 0.770 0.524 1.017 1.692 2.230 2.315 2

15094 05:27:36.0 +16:56:38 13.800 0.628 0.418 0.840 1.419 1.773 1.879 1

15161 05:29:05.4 −16:32:23 10.958 0.545 0.337 0.681 1.122 1.465 1.543 1

15183 05:30:30.1 −05:01:07 12.554 0.856 0.516 0.987 1.652 2.179 2.236 3

(cont’d)

66



15218 05:31:50.9 +16:13:13 12.269 0.732 0.462 0.871 1.517 1.917 1.993 1

15529 05:43:14.9 −19:16:35 12.411 0.576 0.371 0.733 1.201 1.596 1.675 5

15788 05:53:58.8 −14:22:53 11.496 0.524 0.364 0.699 1.170 1.499 1.540 1

15881 05:59:19.9 +12:15:23 13.818 1.126 0.712 1.323 2.253 2.853 2.980 3

15939 06:01:15.1 −16:49:26 12.930 0.492 0.325 0.647 1.091 1.391 1.406 3

15945 06:01:40.2 −12:29:26 14.319 0.594 0.425 0.865 1.500 1.861 1.994 2

15973 06:03:14.9 +19:21:39 9.310 0.588 0.356 0.763 1.336 1.625 1.739 2

15974 06:03:14.5 +19:21:34 13.814 1.040 0.608 1.400 3.250 3.768 3.990 2 1

15979 06:02:40.1 −17:36:18 16.055 1.267 0.817 1.544 2.425 2.890 3.068 1

16030 06:04:54.6 −03:50:05 13.858 1.081 0.648 1.234 1.994 2.552 2.699 3

(cont’d)

67



16185 06:11:20.3 −00:38:25 14.445 0.758 0.516 0.973 1.009 1.631 1.806 1

16242 06:13:31.3 +17:45:06 10.605 0.659 0.372 0.745 1.322 1.671 1.736 1

16250 06:13:17.9 −12:24:20 13.430 0.740 0.446 0.846 1.462 1.860 1.963 3

16320 06:16:43.8 +18:09:49 10.814 0.786 0.430 0.841 1.387 1.736 1.849 1

16444 06:22:38.6 −12:53:05 12.987 0.991 0.597 1.140 1.979 2.480 2.590 3

16520 06:26:07.9 −14:50:55 16.231 1.607 1.020 2.097 3.201 3.714 3.958 1

16573 06:29:31.3 +18:17:54 12.882 1.148 0.797 1.553 2.510 3.160 3.291 1

16579 06:29:43.3 +15:18:25 12.343 0.666 0.414 0.819 1.416 1.766 1.816 2 1

16606 06:30:24.4 −05:22:54 12.270 0.633 0.344 0.695 1.119 1.438 1.468 3

16849 06:41:06.0 +18:24:09 15.315 1.295 0.770 1.466 2.398 2.895 3.151 1

(cont’d)

68



16869 06:42:18.0 +17:21:36 13.164 0.718 0.436 0.853 1.509 1.986 2.012 3

16986 06:47:26.8 +17:39:54 15.779 1.029 0.603 1.188 1.914 2.533 2.672 1

17039 06:48:53.9 −04:59:06 12.914 0.611 0.397 0.791 1.364 1.740 1.760 3

17136 06:53:27.7 −16:14:35 14.068 0.866 0.537 1.048 1.799 2.320 2.422 3

17154 06:54:12.8 −19:54:20 13.327 0.613 0.386 0.728 1.280 1.649 1.704 4

17198 06:56:28.5 −19:17:29 14.622 0.764 0.479 0.940 1.620 2.060 2.210 2

17231 06:58:15.7 −09:32:01 12.806 0.801 0.491 0.937 1.574 1.497 2.175 3

17234 06:58:38.5 −00:28:50 9.009 0.558 0.346 0.675 1.117 1.412 1.464 1

17485 07:10:02.6 −01:17:58 11.852 0.443 0.336 0.668 1.131 1.472 1.537 1

17570 07:13:40.6 −13:27:57 14.425 1.449 0.893 1.691 2.660 3.165 3.385 1

(cont’d)

69



17680 07:18:59.3 +18:14:28 13.643 0.591 0.386 0.760 1.262 1.624 1.695 1

17738 07:21:12.3 −15:21:30 9.802 0.744 0.431 0.819 1.403 1.803 1.870 1

17786 07:23:17.6 +19:00:57 12.000 0.485 0.315 0.643 1.104 1.392 1.461 3

17872 07:27:02.3 +19:05:55 10.727 0.447 0.309 0.633 1.074 1.334 1.340 1

18019 07:31:41.2 −01:02:21 13.288 0.751 0.404 0.798 1.338 1.798 1.867 3

18121 07:34:53.0 −10:23:10 11.100 0.646 0.399 0.775 1.271 1.644 1.743 1

18131 07:35:54.6 +19:12:14 14.373 0.630 0.402 0.793 1.375 1.736 1.819 1

18135 07:35:24.3 −11:45:55 11.196 0.658 0.367 0.730 1.172 1.558 1.626 1

18292 07:41:09.7 −17:32:34 13.026 0.520 0.364 0.729 1.188 1.565 1.584 3

18346 07:43:44.1 −00:03:49 11.253 0.488 0.344 0.660 1.080 1.417 1.444 2

(cont’d)

70



18347 07:43:44.0 −00:04:01 10.202 0.451 0.314 0.624 1.001 1.289 1.352 3 2

18401 07:45:24.4 −15:03:09 11.605 0.471 0.342 0.654 1.134 1.449 1.536 1

18424 07:47:08.6 +14:57:51 12.659 0.772 0.457 0.877 1.562 1.923 1.989 2

18463 07:48:33.7 +19:42:08 13.822 1.137 0.715 1.360 2.262 2.900 2.968 4

18502 07:50:18.5 +18:55:57 12.248 0.565 0.372 0.720 1.204 1.498 0.310 1

18532 07:51:02.1 −13:51:05 15.031 1.404 0.891 1.704 2.676 3.265 3.446 1

18674 07:56:30.3 −07:44:26 13.530 0.687 0.423 0.833 1.396 1.798 1.845 3

18731 07:58:53.9 +18:35:08 13.115 0.814 0.499 0.960 1.638 2.151 2.173 4

18798 08:00:50.3 −04:05:19 14.495 1.073 0.694 1.339 2.153 2.715 2.876 2 1

18799 08:00:50.4 −04:05:32 10.980 0.593 0.291 0.562 1.015 1.279 1.356 4

(cont’d)

71



18834 08:02:13.8 −07:33:59 13.882 0.759 0.478 0.906 1.527 1.990 2.073 2

18877 08:03:39.5 −08:57:51 12.832 0.776 0.463 0.908 1.554 1.984 2.094 3

18982 08:07:42.0 −12:58:05 11.357 0.739 0.420 0.797 1.383 1.743 1.815 1

19037 08:10:04.8 +12:23:38 14.919 1.248 0.783 1.444 2.410 2.928 3.142 1

19151 08:13:27.8 −09:27:57 14.285 1.411 0.923 1.818 2.841 3.349 3.549 2

19210 08:16:07.4 +19:41:52 11.189 0.367 0.280 0.557 0.966 1.164 1.260 1

19301 08:18:43.0 −02:15:27 14.710 0.677 0.448 0.871 1.453 1.940 2.036 2

19309 08:18:54.4 −16:14:32 13.676 0.833 0.489 0.974 1.654 2.103 2.212 3

19462 08:24:16.9 −13:56:27 13.728 0.602 0.393 0.774 1.316 1.680 1.748 2

19466 08:25:01.0 +16:05:29 15.716 1.395 0.867 1.743 2.642 3.266 3.451 1

(cont’d)

72



19550 08:26:53.6 −12:45:44 11.096 0.509 0.340 0.648 1.114 1.430 1.506 1 2

19570 08:28:01.6 +15:34:35 14.379 0.815 0.521 0.979 1.679 2.164 2.306 1

19614 08:29:09.4 +17:16:40 15.748 1.441 1.004 1.706 2.554 3.109 3.307 1

19643 08:29:40.7 −01:44:48 11.930 0.946 0.568 1.108 1.816 2.334 2.475 1

19736 08:32:20.0 −18:51:08 13.763 0.736 0.474 0.933 1.488 1.905 2.038 4

19749 08:32:54.0 −10:03:33 14.275 0.800 0.510 0.999 1.595 2.208 2.330 2

19824 08:35:01.7 −04:13:56 14.628 0.951 0.572 1.122 1.886 2.390 2.566 2

20192 08:45:32.7 −14:31:53 14.508 1.112 0.694 1.291 2.139 2.768 2.907 2

20232 08:46:39.6 −13:21:25 10.235 0.310 0.211 0.421 0.732 0.863 0.933 1

20252 08:47:49.3 +17:30:39 14.918 0.907 0.566 1.070 1.823 2.381 2.418 1

(cont’d)

73



20288 08:48:37.7 +13:27:24 14.910 0.832 0.526 0.999 1.680 2.181 2.292 1

20381 08:51:24.0 +12:37:37 13.703 1.061 0.638 1.223 2.121 2.698 2.783 3

20392 08:51:43.5 +08:53:44 13.848 0.737 0.442 0.862 1.488 1.927 2.012 3

20476 08:53:57.4 +18:02:15 13.181 0.545 0.359 0.723 1.253 1.588 1.649 3

20492 08:54:07.9 −02:08:01 13.280 0.424 0.291 0.599 1.042 1.280 1.315 3

20684 08:59:03.4 −06:23:46 11.968 0.547 0.428 0.809 1.363 1.694 1.770 1

20691 08:59:10.1 −04:01:37 9.648 0.466 0.313 0.643 1.093 1.372 1.455 1

20700 08:59:16.4 −12:33:54 12.063 0.600 0.387 0.734 1.300 1.626 1.723 5

20756 09:00:37.5 −15:55:07 13.955 0.651 0.416 0.833 1.365 1.806 1.847 4

20768 09:01:08.4 −01:08:38 14.048 0.679 0.431 0.835 1.396 1.857 1.893 2

(cont’d)

74



20792 09:01:24.4 −14:40:59 10.035 0.510 0.336 0.681 1.134 1.436 1.507 2

20980 09:06:20.5 −08:53:12 12.001 0.450 0.276 0.576 0.983 1.209 1.232 1

21001 09:06:58.1 −18:06:12 15.130 1.445 0.922 1.745 2.761 3.354 3.575 2

21039 09:08:23.1 −02:08:27 14.024 0.669 0.426 0.821 1.320 1.769 1.813 3

21084 09:09:13.8 −07:23:42 11.890 0.554 0.350 0.811 1.132 1.446 1.549 4

21112 09:10:23.6 +19:43:37 15.299 0.971 0.548 1.026 1.653 2.161 2.299 1

21133 09:10:44.9 −03:48:10 12.746 0.535 0.343 0.694 1.139 1.469 1.507 3

21341 09:15:59.6 −06:57:02 14.263 0.968 0.609 1.159 1.957 2.469 2.610 2

21370 09:16:50.9 −05:23:38 13.741 0.668 0.436 0.838 1.444 1.842 1.978 3

21449 09:19:08.4 +13:07:39 12.563 0.404 0.285 0.584 1.064 1.326 1.351 4

(cont’d)

75



21601 09:23:01.3 +19:51:02 14.556 1.486 0.955 1.882 2.906 3.417 3.585 2

21617 09:23:00.0 −12:38:03 12.867 0.723 0.424 0.825 1.427 1.786 1.878 3

21744 09:25:56.3 −16:04:48 12.160 0.610 0.395 0.778 1.286 1.641 1.710 1

22026 09:32:53.1 +15:09:23 12.618 0.592 0.359 0.714 1.219 1.568 1.633 4

22053 09:33:29.7 −04:41:13 12.090 0.445 0.331 0.667 1.083 1.376 1.387 1

22520 09:45:37.8 −04:40:29 10.849 0.484 0.350 0.674 1.100 1.485 1.517 1

22711 09:49:44.1 −07:39:23 13.851 0.613 0.409 0.803 1.344 1.677 1.802 2

22752 09:50:51.4 −06:44:49 13.861 0.836 0.505 0.964 1.681 2.116 2.214 3

22945 09:55:42.1 +16:05:25 13.175 0.571 0.366 0.727 1.243 1.577 1.624 3

23192 10:00:56.9 −16:29:10 13.777 0.647 0.400 0.805 1.300 1.687 1.770 4

(cont’d)

76



23894 10:17:01.1 −02:40:06 14.643 1.220 0.779 1.460 2.331 2.956 3.122 2

24006 10:19:21.3 +14:24:09 15.521 1.464 0.903 1.717 2.760 3.269 3.493 3

24082 10:20:50.7 −06:41:10 13.143 0.587 0.380 0.753 1.251 1.631 1.685 4

24087 10:20:51.2 −13:42:34 14.672 1.351 0.840 1.584 2.535 3.051 3.283 2

24353 10:26:44.3 −02:21:37 13.180 0.650 0.404 0.799 1.341 1.747 1.841 4

24371 10:27:01.8 −02:09:13 14.187 0.698 0.435 0.852 1.464 1.832 1.953 2

24426 10:27:53.1 −11:52:58 14.274 1.286 0.808 1.482 2.369 2.910 3.099 1

24718 10:34:10.9 −02:48:51 13.118 0.509 0.331 0.676 1.161 1.469 1.554 4

24839 10:36:37.4 −11:54:33 12.590 0.745 0.449 0.892 1.527 1.930 2.083 4

24984 10:39:53.2 +15:08:38 12.493 0.444 0.307 0.613 1.032 1.329 1.378 3

(cont’d)

77



25006 10:40:16.8 +19:37:00 14.083 0.942 0.566 1.067 1.875 2.390 2.501 4

25093 10:41:45.4 −18:57:26 14.934 0.999 0.627 1.152 1.897 2.497 2.637 1

25177 10:43:59.4 +12:48:05 12.219 0.468 0.312 0.628 1.091 1.397 1.448 4

25190 10:44:12.9 −06:42:01 13.886 0.526 0.365 0.715 1.193 1.522 1.619 2

25218 10:44:39.3 −14:38:19 12.792 1.465 0.931 1.887 1.201 1.744 1.992 4

25234 10:45:01.2 −02:07:17 13.221 1.064 0.632 1.178 2.039 2.567 2.694 4

25475 10:50:31.4 +19:58:01 13.852 0.785 0.469 0.922 1.546 2.016 2.138 4

25521 10:51:19.4 −10:49:18 13.692 0.816 0.488 0.959 1.651 2.129 2.197 2

25625 10:53:09.0 −14:33:37 13.787 1.343 0.839 1.549 2.458 2.951 3.142 2

25776 10:56:33.6 +14:33:20 13.778 0.737 0.435 0.843 1.439 1.885 2.008 3

(cont’d)

78



25909 10:59:18.8 +14:19:07 13.546 0.647 0.399 0.782 1.300 1.664 1.785 3

25970 11:00:25.4 −05:19:36 14.860 0.999 0.620 1.168 1.944 2.469 2.602 2

26232 11:05:20.7 −03:14:59 14.361 1.035 0.644 1.229 2.085 2.637 2.754 2

26298 11:06:20.2 −03:01:49 14.438 0.777 0.497 0.947 1.603 2.109 2.236 2

26449 11:09:17.7 −19:17:36 13.877 1.176 0.715 1.322 2.203 2.777 2.990 2

26482 11:10:02.7 −02:47:26 12.506 0.908 0.543 1.059 1.793 2.235 2.391 3

26503 11:10:31.9 +19:13:18 14.239 1.063 0.660 1.243 2.064 2.672 2.820 2

26532 11:10:49.9 −01:58:55 14.773 0.866 0.530 1.015 1.712 2.244 2.362 2

26565 11:11:22.7 −06:31:56 14.767 1.712 0.945 1.802 2.867 3.388 3.654 2

26588 11:11:52.5 +15:50:00 13.571 0.859 0.527 1.007 1.713 2.250 2.328 3

(cont’d)

79



26650 11:13:03.5 −12:48:02 12.499 0.380 0.275 0.585 0.942 1.219 1.280 3

26677 11:13:39.0 −05:15:41 13.520 0.692 0.443 0.883 1.484 1.950 2.070 3

27053 11:20:12.3 −00:46:55 13.645 0.784 0.466 0.902 1.561 2.033 2.098 3

27326 11:24:59.6 −15:43:35 14.440 0.845 0.512 0.957 1.624 2.114 2.249 1

27365 11:25:58.0 −13:10:45 14.388 0.924 0.485 0.942 1.588 2.087 2.188 1

27436 11:27:19.7 −04:47:00 13.009 0.976 0.594 1.124 1.915 2.455 2.579 3

27650 11:31:38.4 −14:21:39 14.296 1.007 0.619 1.174 2.001 2.533 2.670 1

27763 11:33:27.9 −01:48:15 13.609 0.816 0.488 0.951 1.623 2.090 2.201 3

27767 11:33:34.9 +16:45:24 14.703 0.767 0.480 0.936 1.547 1.973 2.082 2

27831 11:34:14.9 −17:19:39 11.773 0.561 0.324 0.649 1.150 1.470 1.498 1

(cont’d)

80



28182 11:40:24.1 −17:23:39 13.882 1.034 0.604 1.141 1.932 2.511 2.637 3

28199 11:40:36.5 −02:01:14 13.229 0.805 0.460 0.889 1.502 1.954 2.078 3

28304 11:42:29.2 +11:59:34 13.347 0.718 0.392 0.767 1.312 1.709 1.802 3

28434 11:45:18.5 −06:38:53 14.866 1.089 0.687 1.273 2.081 2.687 2.825 2

28459 11:45:41.2 −12:10:06 13.352 0.689 0.429 0.817 1.394 1.800 1.875 4

28955 11:55:07.4 −14:02:16 12.530 0.491 0.315 0.646 1.067 1.326 1.385 4

29023 11:56:21.7 −04:23:13 13.009 0.445 0.304 0.611 1.042 1.323 1.373 4

29064 11:57:23.9 +19:51:59 14.014 0.923 0.576 1.087 1.814 2.311 2.433 2

29256 12:00:23.4 −03:25:45 14.676 0.820 0.459 0.894 1.559 2.051 2.094 1

29365 12:02:13.8 −07:11:47 14.249 0.771 0.493 0.924 1.643 2.096 2.151 1

(cont’d)

81



29442 12:03:39.2 −06:45:10 14.404 0.638 0.347 0.704 1.239 1.589 1.605 2 1

29551 12:05:21.0 +19:40:45 11.532 0.401 0.248 0.534 0.921 1.101 1.163 1

29594 12:06:02.1 +12:18:19 13.233 0.521 0.345 0.694 1.189 1.560 1.609 4

29905 12:11:32.4 −15:36:09 12.338 0.686 0.429 0.860 1.435 1.869 1.892 4

29933 12:12:01.4 +13:15:41 10.162 0.468 0.311 0.623 1.043 1.346 1.375 1

30128 12:15:19.1 +19:24:35 13.122 0.699 0.434 0.841 1.473 1.856 1.968 3

30182 12:16:18.5 −12:07:55 14.019 1.139 0.710 1.332 2.199 2.714 2.902 1

30193 12:16:28.3 +15:01:16 14.618 0.848 0.550 1.057 1.749 2.271 2.410 1

30274 12:18:24.3 −12:52:04 12.910 0.387 0.257 0.526 0.857 1.105 1.166 4

30400 12:20:31.5 −11:48:18 13.379 0.684 0.435 0.839 1.468 1.801 1.874 4

(cont’d)

82



30462 12:21:39.1 −05:26:48 12.827 0.830 0.494 0.930 1.597 2.078 2.137 3

30636 12:24:26.8 −04:43:37 14.840 1.702 0.962 1.869 2.867 3.404 3.582 1

30824 12:28:14.1 −05:47:34 14.557 0.831 0.523 0.965 1.419 2.122 2.173 1

30838 12:28:18.3 +12:22:36 12.516 0.458 0.331 0.651 1.099 1.406 1.468 4

30839 12:28:24.3 −09:56:00 14.655 1.267 0.791 1.467 2.395 2.926 3.092 1

31146 12:34:25.1 +15:16:49 11.976 0.409 0.300 0.598 1.016 1.315 1.326 2

31155 12:34:36.6 −01:32:52 13.588 0.529 0.348 0.719 1.218 1.505 1.576 2

31233 12:35:50.3 −10:51:19 13.833 0.754 0.461 0.899 1.558 1.986 2.115 2

31240 12:35:54.0 +16:30:43 15.016 1.017 0.614 1.150 1.856 2.377 2.566 1

31272 12:36:46.4 −11:53:34 14.690 0.687 0.411 0.737 2.660 3.173 3.431 1

(cont’d)

83



31534 12:41:12.4 −08:10:12 14.798 0.840 0.461 0.867 1.462 1.940 2.078 1

31763 12:45:18.7 −16:22:38 14.458 0.998 0.621 1.161 1.932 2.492 2.652 1

31847 12:46:36.2 −07:12:10 14.004 0.843 0.499 0.903 1.515 1.988 2.041 1

31965 12:48:44.8 −01:32:35 14.164 1.057 0.666 1.224 2.066 2.651 2.745 1

31967 12:48:47.8 −11:12:28 14.304 1.595 0.893 1.630 2.641 3.276 3.411 1

32016 12:49:37.5 +14:53:13 14.749 0.760 0.460 0.922 1.603 2.049 2.158 1

32141 12:52:12.4 −12:04:35 14.913 0.901 0.543 0.996 1.699 2.259 2.386 1

32316 12:55:40.9 +12:33:31 11.289 0.506 0.318 0.667 1.111 1.396 1.439 2

32357 12:56:23.7 +15:41:44 13.791 1.326 0.819 1.533 2.409 2.979 3.136 3

32392 12:57:01.2 −01:03:40 14.611 0.949 0.558 1.015 1.711 2.265 2.381 1

(cont’d)

84



32562 13:00:22.7 −05:38:44 14.281 0.762 0.471 0.887 1.475 1.920 1.940 1

32648 13:02:01.6 −02:05:22 12.813 0.709 0.466 0.912 1.572 1.916 2.071 3

32917 13:06:59.6 +17:55:49 13.752 0.510 0.345 0.699 1.103 1.489 1.532 3

32995 13:08:23.7 +14:11:45 13.446 0.907 0.565 1.068 1.784 2.341 2.440 3

33104 13:10:05.6 −02:07:18 14.013 0.471 0.298 0.612 1.073 1.359 1.411 1

33146 13:11:00.8 −00:44:38 12.691 0.418 0.297 0.595 1.024 1.252 1.310 2

33156 13:11:04.3 +12:20:00 14.178 0.699 0.429 0.848 1.469 1.892 2.004 3

33168 13:11:23.7 −09:23:44 14.540 0.545 0.358 0.696 1.164 1.541 1.633 1

33221 13:12:12.8 −08:28:15 13.236 0.887 0.539 1.002 1.719 2.205 2.268 2

33371 13:14:26.9 −04:05:44 12.807 0.906 0.544 1.069 1.808 2.295 2.401 4

(cont’d)

85



33823 13:21:38.0 −11:53:18 12.165 0.731 0.418 0.814 1.388 1.785 1.837 3

33971 13:24:00.2 −02:44:33 12.774 0.519 0.348 0.689 1.158 1.471 1.510 3

34051 13:25:23.5 −01:21:51 13.520 0.746 0.459 0.916 1.579 1.971 2.046 4

34627 13:37:02.6 −12:35:44 14.559 1.345 0.825 1.553 2.508 3.023 3.277 1

34628 13:36:47.5 +19:05:13 11.936 0.842 0.505 0.978 1.647 2.135 2.287 3

35068 13:44:36.5 −03:08:42 13.166 0.567 0.383 0.761 1.331 1.647 1.703 5

35318 13:48:40.4 +15:30:17 13.392 0.980 0.595 1.146 1.920 2.393 2.561 4

35758 13:57:04.6 −02:08:12 13.628 0.591 0.413 0.767 1.352 1.700 1.759 1

35890 13:59:18.6 −13:42:43 12.776 0.604 0.425 0.842 1.457 1.795 1.897 4

35942 14:00:12.7 −03:46:53 14.079 0.679 0.422 0.804 1.356 1.772 1.829 1

(cont’d)

86



36020 14:01:28.0 +17:47:20 14.177 0.724 0.401 0.817 1.412 1.815 1.917 1

36059 14:02:30.1 −05:39:05 11.149 0.359 0.283 0.573 0.998 1.198 1.229 2

36446 14:10:27.1 −13:56:04 10.681 0.580 0.376 0.773 1.240 1.606 1.711 2

36520 14:12:02.1 −18:48:41 12.057 0.544 0.355 0.727 1.219 1.575 1.655 4

36540 14:12:08.5 −05:38:40 14.083 0.855 0.527 1.007 1.717 2.173 2.281 1

36564 14:12:46.0 −14:44:53 13.605 0.678 0.435 0.858 1.461 1.924 1.933 4

37158 14:23:29.6 −12:11:09 14.590 0.679 0.437 0.861 1.517 1.903 1.926 1

37342 14:26:27.7 +14:58:33 14.416 1.505 1.129 2.511 2.727 3.323 3.625 4

37658 14:32:33.4 −12:36:41 14.746 0.754 0.477 0.904 1.485 2.001 2.091 1

37684 14:32:46.4 +16:00:58 13.285 0.545 0.365 0.731 1.204 1.549 1.603 5

(cont’d)

87



37807 14:35:12.7 +12:13:19 11.968 0.470 0.318 0.662 1.130 1.409 1.486 3

37840 14:36:08.0 −16:24:09 16.284 1.433 0.852 1.616 2.682 3.281 3.559 1

37887 14:36:54.9 −17:01:42 16.197 1.387 0.890 1.666 2.695 3.307 3.466 1

37911 14:37:06.4 −05:10:19 15.953 1.399 0.872 1.641 2.719 3.297 3.493 1

37960 14:38:12.2 −00:50:38 13.039 0.896 0.551 1.050 1.856 2.342 2.382 4

38141 14:42:33.3 −18:18:38 15.656 1.044 0.596 1.150 2.008 2.480 2.747 1

38221 14:43:56.2 −11:52:29 11.476 0.574 0.383 0.786 1.275 1.631 1.666 3

38311 14:45:56.7 −00:31:37 13.108 0.519 0.342 0.693 1.215 1.447 1.540 4

38502 14:49:50.0 +12:31:59 15.018 1.358 0.835 1.560 2.483 3.018 3.192 1

38520 14:50:41.2 −16:56:31 16.769 1.602 1.084 2.590 4.908 5.394 5.665 1

(cont’d)

88



38779 14:55:35.8 −15:33:44 14.638 1.603 0.949 1.813 2.874 3.349 3.553 1

38792 14:55:58.3 −19:53:29 15.952 1.219 0.752 1.412 2.430 2.961 3.184 1

38814 14:56:04.3 −03:19:23 13.019 0.532 0.364 0.743 1.262 1.565 1.654 4

38929 14:58:19.1 −02:28:29 15.805 1.426 0.889 1.650 2.687 3.260 3.397 1

39059 15:01:29.7 −16:40:08 15.989 1.300 0.843 1.503 2.588 3.144 3.333 1

39076 15:01:46.8 −13:26:58 14.756 0.607 0.404 0.796 1.367 1.734 1.808 1

39121 15:03:02.3 −19:42:50 12.420 0.813 0.567 1.053 1.730 2.242 2.405 3

39272 15:05:58.0 −15:18:33 16.286 1.638 1.082 2.282 3.478 4.018 4.212 1

39378 15:08:04.3 +14:22:50 13.486 0.806 0.476 0.908 1.547 2.040 2.100 4

39401 15:09:14.0 −19:56:09 15.606 1.146 0.711 1.313 2.224 2.834 3.007 1

(cont’d)

89



39456 15:10:13.1 −16:22:46 9.066 0.771 0.462 0.906 1.529 1.876 2.097 3

39457 15:10:13.0 −16:27:47 9.426 0.791 0.513 0.985 1.662 2.139 2.293 2

39670 15:14:52.5 −18:37:51 11.386 0.539 0.359 0.751 1.231 1.551 1.621 3

39721 15:15:38.2 +19:11:42 13.578 1.273 0.790 1.472 2.328 2.919 3.106 4

40003 15:21:55.5 −14:03:48 13.499 0.860 0.527 1.053 1.829 2.247 2.409 3

40022 15:21:50.3 +14:44:03 13.918 0.915 0.556 1.064 1.790 2.377 2.461 5

40313 15:28:14.0 +16:43:11 13.703 1.345 0.850 1.600 2.561 3.094 3.306 5

40459 15:31:27.1 +15:41:22 14.286 0.476 0.357 0.695 1.156 1.450 1.497 1

40604 15:34:55.7 +16:59:19 14.271 0.868 0.540 1.034 1.746 2.217 2.328 1

40723 15:37:51.7 −18:37:19 13.402 0.472 0.346 0.704 1.193 1.498 1.563 3

(cont’d)

90



40901 15:41:19.4 +13:49:29 15.136 1.474 0.961 1.942 3.036 3.605 3.802 1

41111 15:45:16.6 +15:10:45 13.719 0.908 0.552 1.059 1.792 2.327 2.391 4

41218 15:48:13.3 −14:44:49 14.895 1.063 0.653 1.233 2.108 2.723 2.891 1

41242 15:48:51.8 −11:53:58 14.214 1.077 0.647 1.233 2.039 2.606 2.748 1

41993 16:06:35.7 +13:25:07 14.451 1.001 0.591 1.134 1.955 2.478 2.554 1

42136 16:09:46.6 +16:57:11 13.329 0.694 0.414 0.812 1.408 1.793 1.868 4

42183 16:10:52.7 +13:16:16 12.836 0.494 0.334 0.687 1.181 1.552 1.559 4

42301 16:14:14.5 +16:51:00 12.844 0.593 0.376 0.730 1.273 1.619 1.624 6

42743 16:25:14.0 +15:40:54 13.455 1.381 0.872 1.662 2.648 3.232 3.398 4

43100 16:35:04.3 −12:41:21 13.458 1.303 0.832 1.560 2.628 3.256 3.451 4

(cont’d)

91



43121 16:35:35.5 −13:41:37 15.594 1.555 0.926 1.792 2.816 3.385 3.598 1

43207 16:37:42.3 −17:05:00 15.733 1.507 0.928 1.786 2.824 3.331 3.602 1

43291 16:39:54.9 −15:49:52 12.519 0.831 0.545 1.089 1.879 2.345 2.453 5

43444 16:43:58.6 −19:31:36 15.131 1.163 0.736 1.421 2.443 3.032 3.242 1

43607 16:49:32.1 −14:56:21 15.424 1.554 1.000 2.071 3.280 3.853 4.018 1

43659 16:51:09.9 −12:13:28 14.859 1.628 0.986 1.838 3.006 3.766 3.976 1

43675 16:51:05.5 +15:51:49 13.719 0.879 0.361 1.037 1.766 2.254 2.387 2

43737 16:53:38.8 −13:27:21 14.926 1.501 0.924 1.832 2.848 3.372 3.604 2

43778 16:54:33.2 +14:26:24 15.833 1.244 0.737 1.432 2.339 2.913 3.121 1

43887 16:57:57.7 −12:28:06 14.203 0.969 0.599 1.191 2.070 2.604 2.725 4

(cont’d)

92



43923 16:58:57.4 −14:40:18 13.473 1.008 0.621 1.182 2.013 2.572 2.706 4

44039 17:01:44.0 +16:09:03 11.470 0.448 0.342 0.691 1.125 1.380 1.439 1

44226 17:08:05.1 +17:57:38 10.467 0.471 0.344 0.711 1.124 1.399 1.527 1

44233 17:08:21.1 +12:25:40 15.232 0.857 0.519 0.993 1.769 2.222 2.337 1

44568 17:18:42.6 +16:23:45 12.294 0.509 0.322 0.648 1.134 1.458 1.486 4

44639 17:20:53.8 +15:32:48 11.813 0.612 0.364 0.752 1.226 1.578 1.663 1

44683 17:23:23.9 −14:13:13 11.830 0.770 0.443 0.850 1.439 1.836 1.884 2

44749 17:25:34.8 −18:46:10 14.671 1.139 0.710 1.350 2.323 2.947 3.105 4

44769 17:25:29.4 +19:23:17 15.194 1.499 0.944 1.840 2.920 3.400 3.599 2

44932 17:30:42.6 +15:04:00 15.799 1.340 0.846 1.565 2.571 3.119 3.278 1

(cont’d)

93



45010 17:32:33.7 +17:00:06 13.667 0.526 0.355 0.688 1.154 1.428 1.601 2

45011 17:33:12.6 −15:49:14 13.525 1.315 0.832 1.543 2.465 3.069 3.223 4

45026 17:33:51.6 −16:58:58 11.830 0.737 0.462 0.893 1.344 1.715 1.817 2 1

45204 17:39:49.9 −14:19:55 14.674 0.904 0.558 1.118 1.868 2.340 2.473 1

45367 17:45:08.4 −16:45:11 13.959 1.460 0.964 2.020 2.336 −0.048 3.142 4

45416 17:46:36.3 −12:58:17 14.428 1.305 0.753 1.467 2.391 2.902 3.097 1

45609 17:52:48.4 +14:38:37 12.530 0.953 0.572 1.113 1.860 2.427 2.543 5

45616 17:52:59.7 +15:21:03 11.862 0.508 0.352 0.720 1.181 1.495 1.534 1

45620 17:53:10.2 +12:10:35 16.257 1.496 0.914 1.708 2.712 3.291 3.466 1

45754 17:59:43.0 −19:52:49 14.373 0.750 0.519 1.053 1.959 2.483 2.722 4

(cont’d)

94



46039 18:10:04.5 +16:01:46 11.420 0.607 0.387 0.787 1.326 1.656 1.718 1

46209 18:16:23.0 +19:08:15 14.944 0.835 0.491 0.978 1.649 2.110 2.187 1

46215 18:16:58.5 −04:03:08 13.623 1.095 0.634 1.163 2.005 2.634 2.763 5

46320 18:20:34.8 +16:08:19 13.560 0.769 0.462 0.903 1.531 1.907 2.013 1

46730 18:37:11.8 −00:53:23 11.871 0.620 0.391 0.789 1.304 1.717 1.761 5

46738 18:37:26.2 −00:25:13 13.784 0.683 0.439 0.874 1.462 1.783 1.884 4

46798 18:39:09.7 −00:07:14 10.775 0.510 0.338 0.689 1.127 1.391 1.487 2

46826 18:39:58.1 +16:25:44 15.375 1.308 0.809 1.505 2.442 2.992 3.263 1

46843 18:40:29.2 +19:36:06 14.081 0.821 0.470 0.925 1.558 1.982 2.096 1

46966 18:45:21.5 +17:00:31 13.810 0.898 0.575 1.152 1.974 2.435 2.554 2

(cont’d)

95



47073 18:50:45.8 −16:22:02 13.667 0.708 0.439 0.922 1.559 1.924 1.989 1

47132 18:52:35.6 +17:43:24 12.897 0.827 0.467 0.909 1.570 1.988 2.090 1

47242 18:58:25.2 −13:12:41 12.876 0.913 0.497 0.978 1.728 2.156 2.265 6

47257 18:59:15.2 −16:10:19 11.269 0.482 0.352 0.694 1.209 1.483 1.508 2

47331 19:01:51.0 +16:03:48 10.378 0.619 0.401 0.786 1.274 1.655 1.737 1

47425 19:07:33.2 −01:21:04 15.086 0.897 0.559 1.160 1.966 2.441 2.550 1

47480 19:09:38.7 +16:53:54 13.838 0.807 0.506 0.996 1.735 2.225 2.305 2

47481 19:10:05.1 −00:58:39 9.875 0.264 0.155 0.342 0.645 0.704 0.761 2

47525 19:13:04.6 −18:07:42 14.386 1.390 0.833 1.586 2.531 3.127 3.299 1

47533 19:12:46.7 +12:12:13 14.462 1.012 0.627 1.192 2.116 2.730 2.896 2

(cont’d)

96



47543 19:13:20.7 −00:35:42 9.187 0.514 0.343 0.698 1.135 1.439 1.502 2

47711 19:21:53.1 −19:22:10 13.665 0.671 0.456 0.895 1.584 1.977 2.096 5

47811 19:27:32.1 −18:03:09 13.485 0.559 0.373 0.730 1.254 1.560 1.544 4

47944 19:34:17.0 −03:52:08 13.972 0.990 0.613 1.214 2.064 2.476 2.546 1

47972 19:35:36.4 −04:10:15 12.736 0.698 0.477 0.964 1.628 1.986 2.085 2

48011 19:36:45.0 +17:21:09 14.668 1.025 0.639 1.245 2.007 2.591 2.694 2

48056 19:39:12.1 −05:21:58 13.744 0.690 0.476 0.932 1.572 1.948 2.030 2

48062 19:39:16.2 −03:13:53 12.503 0.868 0.517 1.026 1.779 2.273 2.362 1

48133 19:42:59.1 −15:07:08 15.175 0.932 0.600 1.188 2.062 2.567 2.683 1

48149 19:43:42.7 −15:55:37 12.416 0.618 0.402 0.819 1.438 1.758 1.852 2

(cont’d)

97



48255 19:48:17.6 −01:48:23 14.713 1.208 0.717 1.447 2.376 2.940 3.111 1

48391 19:53:32.6 +18:45:36 15.230 1.363 0.885 1.561 2.542 3.149 3.306 2

48592 20:02:04.3 +15:07:48 12.179 0.486 0.372 0.689 1.152 1.426 1.511 1

48658 20:04:31.1 −12:17:01 14.358 1.070 0.654 1.257 2.171 2.784 2.907 1

48866 20:11:47.6 +15:08:29 12.688 0.574 0.366 0.720 1.216 1.542 1.584 2

48925 20:15:01.5 −13:10:34 13.654 0.601 0.390 0.784 1.378 1.789 1.800 2

48997 20:17:31.2 −00:10:52 14.296 0.829 0.527 1.003 1.801 2.238 2.306 1

49082 20:20:20.0 −02:48:37 16.197 1.478 1.010 2.183 3.369 3.867 4.119 2

49226 20:25:34.2 −12:02:26 11.196 0.587 0.385 0.759 1.258 1.613 1.675 1

49245 20:26:13.8 −14:28:34 15.463 1.445 0.907 1.703 2.723 3.228 3.465 2

(cont’d)

98



49301 20:28:25.7 −15:04:26 12.399 0.533 0.376 0.755 1.249 1.579 1.640 2

49304 20:28:21.0 −03:08:35 14.947 1.150 0.722 1.355 2.328 2.966 3.107 1

49482 20:34:37.9 −18:02:55 14.910 1.489 0.953 1.889 2.890 3.421 3.624 2

49486 20:34:22.5 +11:52:03 15.973 1.354 0.923 2.025 3.444 4.134 4.274 2

49487 20:34:22.7 +11:52:00 12.283 0.878 0.521 0.980 1.658 2.176 2.238 3

49488 20:34:36.9 −03:10:09 14.852 1.340 0.818 1.589 2.623 3.256 3.410 1

49497 20:35:02.9 −12:31:51 15.910 1.417 0.890 1.667 2.624 3.154 3.357 2

49611 20:38:47.1 −14:22:47 14.664 1.376 0.849 1.570 2.592 3.097 3.309 2

49618 20:38:55.7 −06:27:47 12.246 0.575 0.306 0.646 1.123 1.467 1.508 2

49624 20:39:15.9 −18:51:15 14.577 0.799 0.500 0.965 1.716 2.232 2.285 1

(cont’d)

99



49627 20:39:20.9 −19:28:55 14.332 1.018 0.604 1.107 1.985 2.513 2.659 1

49726 20:42:30.1 −02:15:29 15.893 1.359 0.819 1.528 2.439 2.978 3.198 1

49749 20:42:45.9 +16:27:22 14.844 1.185 0.735 1.372 2.182 2.851 2.964 2

49819 20:44:59.6 −01:40:57 14.024 0.628 0.404 0.792 1.372 1.697 1.817 2

49821 20:45:01.2 −01:40:55 12.772 0.497 0.308 0.619 1.017 1.323 1.395 2

49872 20:47:12.4 −10:11:31 12.104 0.570 0.366 0.728 1.296 1.621 1.720 2

49897 20:47:43.6 −02:35:13 15.769 1.020 0.610 1.178 1.953 2.435 2.582 1

49949 20:49:32.9 −07:43:39 12.562 0.522 0.329 0.664 1.063 1.394 1.399 2

50185 20:56:39.9 −09:39:19 10.266 0.505 0.324 0.659 1.072 1.417 1.466 1

50190 20:56:46.7 −07:50:11 11.993 0.558 0.351 0.701 1.097 1.454 1.517 2

(cont’d)

100



50215 20:57:42.5 −19:34:28 14.722 1.489 0.926 1.772 2.800 3.327 3.523 1

50257 20:58:40.1 −01:06:11 13.795 0.681 0.428 0.845 1.490 1.864 1.933 2

50270 20:59:19.3 −16:27:52 11.629 0.485 0.336 0.663 1.106 1.391 1.431 1

50339 21:01:35.5 −18:38:17 14.468 0.689 0.415 0.842 1.484 1.877 1.968 1

50346 21:01:35.2 −00:42:37 15.649 1.277 0.786 1.520 2.474 3.114 3.228 1

50376 21:02:18.0 −06:53:53 13.948 0.779 0.484 0.929 1.629 2.074 2.190 1

50474 21:04:51.6 −00:37:36 13.150 0.611 0.384 0.760 1.279 1.645 1.694 1

50556 21:06:53.9 +15:36:28 15.723 1.006 0.619 1.178 1.975 2.560 2.656 2

50759 21:12:00.5 +18:22:16 15.920 1.468 0.808 1.514 2.411 2.957 3.113 2

50869 21:15:42.6 −09:00:41 15.790 0.514 1.402 2.079 2.928 3.499 3.605 1

(cont’d)

101



50911 21:16:41.6 −01:18:09 11.591 0.467 0.307 0.679 1.088 1.372 1.440 1 2

51006 21:19:17.1 −10:54:43 14.069 0.942 0.576 1.114 1.838 2.350 2.498 1

51088 21:21:34.8 −19:03:39 15.189 1.407 0.840 1.558 2.486 2.963 3.146 1

51115 21:22:21.6 −19:29:41 14.919 1.120 0.656 1.233 2.170 2.716 2.844 1

51153 21:23:21.3 −01:21:39 15.080 1.104 0.664 1.285 2.068 2.606 2.800 1

51740 21:38:57.1 −06:07:13 15.347 1.286 0.801 1.488 2.361 2.998 3.189 1

51754 21:39:01.7 +19:03:32 15.004 1.049 0.638 1.252 2.143 2.659 2.818 2

51824 21:41:10.8 −07:28:51 11.883 0.652 0.388 0.770 1.280 1.654 1.695 1

51856 21:41:40.2 +17:35:16 13.374 0.572 0.339 0.589 1.262 1.604 1.674 2

52089 21:47:16.0 +13:55:50 14.909 1.098 0.693 1.300 2.091 2.775 2.884 2

(cont’d)

102



52377 21:54:06.5 −01:17:10 14.515 0.213 0.142 0.525 2.037 2.728 3.072 2

52398 21:54:42.2 −14:17:27 14.593 0.791 0.517 0.973 1.684 2.224 2.259 1

52456 21:55:59.2 −17:30:22 12.328 0.628 0.372 0.704 1.261 1.622 1.664 2 1

52532 21:57:36.0 −03:28:09 15.508 1.352 0.846 1.620 2.590 3.147 3.336 2

52573 21:58:30.5 −10:22:18 15.257 1.197 0.744 1.393 2.270 2.895 3.013 2

52639 21:59:54.9 −00:39:47 13.177 0.758 0.486 0.954 1.566 2.018 2.102 1

52648 22:00:17.3 −07:24:45 15.066 1.499 1.086 2.352 0.646 1.051 1.448 1

52666 22:00:49.7 −14:36:45 15.044 1.211 0.761 1.431 2.298 2.851 2.963 2

52816 22:03:43.3 +14:54:41 15.725 1.245 0.772 1.453 2.373 2.884 3.073 2

52894 22:05:40.5 +12:29:21 16.036 1.271 0.785 1.468 2.375 2.932 3.063 2

(cont’d)

103



53190 22:12:33.0 −07:27:37 15.362 1.130 0.706 1.342 2.201 2.778 2.946 2

53254 22:13:47.2 −06:27:15 14.674 1.396 0.864 1.661 2.623 3.199 3.430 2

53255 22:13:50.8 −06:27:13 15.024 1.541 0.936 1.769 2.805 3.333 3.600 2 1

53274 22:14:24.0 −08:44:42 11.855 0.760 0.535 1.044 1.776 2.217 2.382 1

53316 22:15:31.4 −05:54:47 15.384 1.430 0.882 1.673 2.662 3.267 3.487 2

53346 22:16:06.9 −09:40:03 13.813 0.687 0.400 0.770 1.295 1.675 1.702 2

53480 22:18:41.2 −10:08:19 12.552 0.593 0.287 0.685 1.302 1.637 1.697 2 1

53617 22:21:43.9 −04:08:57 17.328 1.493 1.285 2.888 4.485 5.045 5.264 1

53702 22:23:06.3 +18:46:22 15.283 1.375 0.849 1.623 2.588 3.209 3.288 2

53707 22:23:25.4 −13:13:08 12.100 0.585 0.377 0.788 1.277 1.637 1.674 1

(cont’d)

104



53781 22:25:10.7 −11:52:42 13.795 0.679 0.433 0.823 1.355 1.785 1.789 2

53801 22:25:33.4 −04:01:31 11.835 0.594 0.401 0.748 1.240 1.554 1.643 1

53823 22:26:06.7 −13:53:19 13.764 0.819 0.501 0.951 1.580 2.025 2.133 2

54027 22:30:38.8 −18:42:53 13.260 0.701 0.418 0.830 1.426 1.837 1.929 2

54088 22:32:02.2 −14:48:55 14.130 1.058 0.646 1.209 1.983 2.517 2.634 2

54168 22:33:40.1 −10:47:47 13.356 0.279 0.312 0.669 1.068 1.377 1.429 2

54184 22:34:05.6 −11:07:09 13.965 1.080 0.662 1.242 2.054 2.541 2.720 2

54349 22:36:56.3 +13:19:41 14.442 1.243 0.779 1.449 2.359 2.893 3.120 2

54450 22:39:09.7 −10:17:33 15.583 1.255 0.811 1.500 2.457 3.099 3.318 1

54578 22:41:41.1 −18:54:41 15.836 1.209 0.768 1.379 2.331 2.944 3.097 1

(cont’d)

105



54598 22:41:58.1 −00:48:24 14.747 0.943 0.578 1.118 1.878 2.471 2.492 1

54608 22:42:15.3 −07:44:57 15.999 1.176 0.718 1.333 2.222 2.845 2.970 1

54620 22:42:37.2 −09:00:10 15.194 1.464 0.894 1.746 2.733 3.252 3.485 2

54699 22:43:59.7 +15:11:09 15.109 0.982 0.573 1.079 1.775 2.315 2.425 2

54710 22:44:31.6 −03:37:47 15.180 1.209 0.742 1.385 2.316 2.909 3.041 2

54730 22:44:56.3 −02:21:13 11.491 0.636 0.416 0.823 1.375 1.782 1.815 1

55411 22:58:05.5 −08:36:24 15.913 1.469 0.884 1.674 2.603 3.180 3.303 1

55603 23:01:39.2 −19:09:37 12.111 0.433 0.312 0.667 1.039 1.329 1.399 1

55732 23:04:24.3 −16:19:15 13.442 0.751 0.442 0.862 1.445 1.879 1.969 2

55733 23:04:17.5 +11:54:31 14.499 0.621 0.414 0.801 1.352 1.746 1.823 2

(cont’d)

106



55942 23:08:45.2 −07:45:36 13.509 0.979 0.571 1.056 1.837 2.387 2.481 2

56002 23:09:54.6 +13:32:01 14.356 0.917 0.540 1.064 1.810 2.259 2.416 2

56290 23:16:05.3 −10:55:10 12.556 0.442 0.309 0.644 1.118 1.385 1.442 2

56420 23:18:13.5 −03:47:06 15.628 0.970 0.580 1.105 1.891 2.339 2.517 1

56533 23:20:25.3 −09:43:38 15.890 1.144 0.736 1.284 2.247 2.887 2.978 1

56534 23:20:26.1 −17:53:36 12.688 0.674 0.391 0.779 1.301 1.721 1.789 1

56753 23:24:27.9 −19:32:54 16.373 1.343 0.824 1.535 2.511 3.080 3.219 1

56774 23:24:49.6 −19:06:28 12.924 0.509 0.327 0.679 1.169 1.460 1.451 2

56817 23:25:38.8 −18:49:00 16.103 1.553 0.948 1.893 2.940 3.439 3.676 1

56818 23:25:35.0 +16:14:19 13.968 0.860 0.518 1.020 1.766 2.274 2.406 2

(cont’d)

107



56855 23:26:27.0 −10:58:07 13.717 0.559 0.354 0.736 1.157 1.507 1.574 2

57038 23:29:43.5 −09:29:56 13.856 0.733 0.433 0.870 1.434 1.928 1.990 2

57214 23:33:31.3 −08:30:19 15.769 0.901 0.539 1.056 1.795 2.154 2.354 2

57452 23:37:57.3 −07:45:33 13.572 0.904 0.531 0.994 1.735 2.241 2.274 2

57546 23:39:45.3 −15:57:26 16.213 1.481 0.911 1.866 2.924 3.442 3.650 1

57564 23:40:03.0 −19:27:28 10.567 0.461 0.295 0.648 1.011 1.272 1.377 1

57630 23:41:18.0 −07:36:10 14.974 0.914 0.579 1.088 1.830 2.378 2.508 2

57631 23:41:17.9 −19:47:36 13.458 0.819 0.496 0.967 1.673 2.154 2.236 2

57647 23:41:28.5 −19:43:45 14.726 0.855 0.517 1.005 1.719 2.194 2.305 2

57741 23:42:59.8 −18:48:43 14.212 0.753 0.460 0.900 1.485 1.912 2.019 2

(cont’d)

108



57744 23:43:01.2 −19:29:44 16.125 1.436 0.849 1.631 2.578 3.131 3.285 1

57781 23:43:34.9 −07:55:24 10.115 0.654 0.387 0.766 1.224 1.623 1.701 1

57832 23:44:31.3 −06:12:41 15.200 1.087 0.651 1.234 2.015 2.616 2.706 1

57851 23:44:59.8 +18:03:28 15.200 1.416 0.904 1.793 2.770 3.377 3.546 1

57856 23:45:06.7 −19:36:45 13.188 0.634 0.425 0.798 1.387 1.769 1.838 2

58071 23:49:13.1 +14:30:36 13.089 0.436 0.298 0.623 1.066 1.349 1.375 3

58141 23:50:33.9 −08:34:02 15.812 1.293 0.789 1.491 2.359 2.964 3.183 1

58403 23:55:16.9 −13:19:42 15.195 0.874 0.524 1.019 1.699 2.228 2.326 1

58522 23:57:19.4 −19:23:40 15.009 1.431 0.889 1.724 2.651 3.262 3.442 2

58526 23:57:18.9 −00:52:47 15.636 0.730 0.495 0.963 1.533 2.013 2.033 1

(cont’d)

109



58555 23:57:51.4 −06:16:54 15.055 1.468 0.912 1.775 2.737 3.292 3.529 1

58812 00:01:56.0 −09:51:47 14.932 1.104 0.667 1.256 2.091 2.667 2.796 1

a (1) Star may be variable, as suggested by standard deviation between multiple measurements of >0.08 mag.

(2) Star may be variable, as suggested by large discrepancy with Hipparcos photometry.

110

All V <13.5 V >13.5

Color Observatory σ N σ N σ N

V MDM 0.025 115 0.016 24 0.027 91

CTIO 0.018 282 0.014 132 0.023 150

Both 0.025 97 0.013 10 0.027 87

All 0.020 397 0.014 156 0.024 241

B − V MDM 0.020 101 0.019 23 0.021 78

CTIO 0.016 261 0.014 125 0.018 136

Both 0.021 83 0.019 9 0.021 74

All 0.017 362 0.015 148 0.019 214

V − R MDM 0.015 114 0.018 24 0.014 90

CTIO 0.013 284 0.012 133 0.014 151

Both 0.014 96 0.016 10 0.014 86

All 0.014 398 0.012 157 0.014 241

V − I MDM 0.019 112 0.015 23 0.020 89

CTIO 0.016 279 0.013 130 0.018 149

Both 0.020 95 0.017 9 0.020 86

All 0.017 391 0.014 153 0.019 238

Table 2.4. Photometric Errors

111

Chapter 3

Mapping the Local Galactic Halo. II. Optical

Spectrophotometry of Cool Subdwarf

Candidates

3.1. Introduction

The results of an optical spectrophotometric survey of a sample of candidate

cool, metal-poor subdwarfs in the solar neighborhood are presented. Moderate

resolution (∼1 A) spectroscopic observations provide confirmation of the assigned

luminosity classes, as well as radial velocities, metallicities, effective temperatures,

and surface gravities for about 350 candidate subdwarfs. Metallicity estimates

presented here are accurate to ∼0.35 dex. The subdwarfs discussed here are a subset

of the photometric study presented by Marshall (2006) (hereafter referred to as

Chapter 2). We find that the method for selecting a metal-poor population described

in Chapter 2 is very successful; 91% of the stars studied are indeed metal-poor

subdwarfs (with [Fe/H]< −0.5). We further stress that this method is an ideal way

of selecting bright, very metal-poor stars for future high-resolution follow-up studies.

112

The spectroscopic survey described here is a subset of the sample of candidate

cool halo subdwarfs presented in Chapter 2. Chapter 2 describes the sample selection

and presents photometry for 635 candidate cool halo subdwarfs.

Although many of the stars in our sample have been identified as likely

subdwarfs by previous work, 107 of our program stars have no reference in the

SIMBAD database other than the source paper (Gould & Salim 2003; Salim &

Gould 2003).

In § 2 we discuss the observations and data reduction methods. Section 3

presents results, and includes a discussion of radial velocity determinations, spectral

type estimation, metallicity estimates, distance estimates, and determination of

effective temperatures. In § 4 we discuss the metallicity distribution of our program

stars, and consider the fraction of subdwarfs that we successfully identify in this

project. A number of particularly interesting stars, including carbon-enhanced

metal-poor stars, and several bright very metal-poor stars are discussed in this

section. Section 6 compares out observations with theoretical isochrones of similar

stars. Our conclusions are presented in § 5.

3.2. Observations and Data Reduction

Spectrophotometric observations were obtained during 2003-2005 with the

MDM Observatory on Kitt Peak, Arizona, and at the Cerro Tololo Inter-American

113

Observatory (CTIO) in Chile. Spectrophotometry was obtained as a rough check on

the accuracy of the colors of the candidate subdwarfs derived in Chapter 2, as well

as to insure that any measurements made across a wide wavelength region in the

spectrum would be as accurate as possible. Only relative spectrophotometry was

performed; we did not obtain absolute flux measurements with these observations.

Chapter 2 fully describes the selection criteria of the sample. The targets

were selected so as to be observable from both observatories. Hence, our stars were

required to be equatorial, i.e., to have declinations of −20o < δ < +20o. Since

spectrophotometric measurements were desired, all observations were obtained at

low airmass, in order minimize the effects of atmospheric dispersion.

Spectrophotometric observations were obtained with the CTIO 1.5m telescope

during 2003 and 2004, and with the MDM Observatory 2.4m telescope during

2003 – 2005. Table 3.1 presents a list of the specific observing runs, as well as

the configurations used in each. Moderate resolution spectra were obtained in

three wavelength ranges: “B” (∼3800-5400 A), “G” (∼5200-6800 A), and “R”

(∼6500-8100A). All observations were obtained using a North-South oriented slit,

and observations were made as the targets transited the meridian (± 1 hour of

transit). Simulations of atmospheric dispersion effects for the two observatories

require observations of the target stars within one hour of transiting the meridian

in order to prevent slit losses due to atmospheric dispersion. With these observing

procedures, any star in the sample observed at either observatory will suffer less

114

than a 10% signal loss for a 1.′′ slit at either the blue or red end of the spectra. We

adopted this observing technique for all of the spectrophotometric observations.

The CCDS Spectrograph 1 was used for all observations obtained at the

MDM 2.4m telescope. The 350 l/mm grating was used for the moderate resolution

observations, and was rotated to provide the appropriate wavelength coverage for

each of the three desired wavelength ranges. A 1” (87 micron) slit was used for all

observations, producing a spectral resolution of 3.4 Aper resolution element.

The RC Spectrograph 2 was used to obtain observations at the CTIO 1.5m

telescope. Grating “26/I” at tilt 16.26 degrees was used for the B spectra while

grating “35/I” at 18.26 degrees and 20.8 degrees tilt, respectively, was used to obtain

the G and R spectra. A 2” (110 micron) slit provided similar resolution to those

obtained at MDM.

Spectrophotometric observations of 319 stars were obtained. Most stars (233)

have observations at all three (B, G, and R) wavelength settings. Spectrophotometric

standard stars were also observed on each night, generally about once every 1-2

hours throughout the night.

Formal signal-to-noise (S/N) ratios were computed for the spectra, measured

by finding a simple linear fit to a region of the spectrum free from absorption features

1See http: //www-astronomy.mps.ohio-state.edu/MDM/CCDS/.2See http: //www.ctio.noao.edu/spectrographs/60spec/60spec.html.

115

and measuring the standard deviation about that fit. This standard deviation is a

good estimate of the S/N ratio of the spectrum. Spectra generally have formal S/N

ratios of ∼100 for the targets with V < 12, S/N ∼50 for 12 < V < 14, S/N ∼30 for

14 < V < 16.

The data were reduced using standard proceedures within IRAF1. All frames

were overscan subtracted and trimmed to dimensions containing relevant data. The

B and G data from MDM were reduced identically. Flat fields and argon and xenon

calibration lamp spectra were obtained at the beginning and end of the night using

lamps internal to the instrument. These master flat fields were used to flatten

each night’s B and G spectra. Due to significant fringing redward of ∼7200A, the

R spectra at MDM were flattened more carefully, using an average of flat fields

obtained before and after each R observation at each telescope pointing to attempt

to remove the fringing.

The spectra were then extracted with the IRAF task APALL. For the R spectra,

the flat and comparison lamp spectra at each telescope pointing were extracted

using the target spectrum as a reference trace. The spectra were then wavelength

calibrated using either a master lamp spectrum obtained at the beginning of the

night (B and G) or the lamp spectra associated with each pointing (R). The spectra

1IRAF is distributed by the National Optical Astronomy Observatory, which is operated by the

Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the

National Sience Foundation.

116

were then linearized, and spectrophotometric standard stars were used to remove the

instrumental signature from the spectra. All standards observed on each night were

combined into one master sensitivity function and applied to all data for that night.

A similar observing procedure was performed at CTIO, however, since there is

much less fringing in the CCD in the RC Spectrograph, we did not take flat lamp

spectra at each telescope pointing. Instead, only comparison lamp spectra were

obtained before and after each observation.

In addition to the moderate-resolution spectra described above, higher-

resolution spectra of a subset of candidates were obtained from MDM. These were

obtained with the aim of obtaining higher-precision radial velocity measurements,

in order to check the accuracy of the radial velocities obtained from the moderate-

resolution spectra. We again used the CCDS spectrograph, but with the 1800

l/mm grating, producing 0.275 A pix−1 or about 0.7 A resolution over five nights

in January and April 2004. These spectra are centered on the Mg I triplet at

5179 A and cover the wavelength range ∼5000-5300 A. Flat and comparison lamps

were obtained before and after each observation at each telescope pointing. These

high-dispersion spectra were reduced in a similar way as described above. Many

(about 15 per night) CORAVEL (Udry et al. 1999) and CORAVEL-ELODIE radial

velocity standards (Udry et al. 1999) were also observed during each of these nights

to provide a standard system from which to base our radial velocity measurements.

117

3.3. Results

The entire spectroscopic dataset is presented in Appendix I; a representative

sample of the candidate subdwarf spectra is shown in Figure 3.1. For these figures

we have combined the spectra by using the region in which the spectra overlap in

wavelength. For example, for each pair of B and G spectra we first trim off the

tails where the sensitivity function derived from observations of standard stars was

not well fit at the ends of the spectrum, then integrate over the overlap region and

normalize the flux in the overlap region to that in the other spectrum, and average

the two spectra together. A similar procedure was then performed to add the R

spectrum onto the BG combined spectrum. For some spectra little or no overlap

region was available; these spectra were normalized by eye before combining them.

Most of the analysis described below has been done using only one of the three

spectra for a given star (i.e., we generally do not use the fully combined spectrum to

measure line indices, radial velocities, etc.).

3.3.1. Radial Velocities

Radial velocities were measured for the program stars in two different ways.

High-resolution (0.7 A) radial velocities of 47 of the brightest targets were measured

as a check of the lower-resolution radial velocity measurements. The spectra were

reduced by flattening the images with the flat lamps obtained on either side of

118

the target spectrum, then deriving a wavelength solution for each target using the

comparison lamp spectra. All of the observations obtained on one night were then

cross-correlated, using the IRAF task FXCOR, against each of the radial velocity

standards and the average of each heliocentric radial velocity was taken to be the

final radial velocity for each target star. We also cross-correlated each radial velocity

standard spectrum against all other observations of radial velocity standards and

thereby derive a very robust measurement of the precision of the method. These

high-precision radial velocities are found to be accurate to ∼2 km s−1.

Lower-resolution radial velocities were obtained for 297 of the target stars with

the medium-resolution spectra. We used the G spectra only since this wavelength

range has many absorption features available for radial velocity measurement across

all of the spectral types included in the sample, and also has the benefit of having

several bright O I night sky emission lines in the wavelength range from which

to set an accurate wavelength scale. Once the spectra were reduced as described

above, a spectrum of the night sky was extracted for each target (just the night sky

spectrum extracted automatically by APALL in its normal usage) and the bright

O I emission lines were used to shift the spectrum to the appropriate wavelength.

This was necessary because the G spectra did not have calibration lamp exposures

at each telescope pointing. Once the spectra were shifted, the radial velocities were

measured in two ways, following the methodology described in Beers et al. (1999).

119

First, several of the higher S/N spectra with spectral types from G-K were

selected in order to produce a template spectrum with many absorption features.

These spectra were shifted so that they had zero radial velocity, and then co-added

to form the template. This template was cross-correlated against the G spectra to

derive the radial velocities for each star. The average of the errors reported by IRAF

is about 30 km s−1.

As a check on these measurements, radial velocities were also derived using

line measurements. About 14 features were identified on each spectrum using the

IRAF task RVIDLINES, which then computes a radial velocity for each star. The

average of the errors reported by IRAF for these measurements is comparable to the

cross-correlation method, about 30 km s−1. However, as described below, there are

other problems with using this technique.

Finally, we correct all radial velocities to a heliocentric rest frame using the

IRAF task RVCORRECT.

The above procedure was performed for both the MDM and CTIO spectra

separately. Each subset had similar results (i.e., the internal errors for both the MDM

and CTIO groups of spectra were ∼30 km s−1). Figure 3.2 shows a comparison of the

two methods, plotting the radial velocities derived via the cross-correlation method

against those derived via the line-measurement method. There is a significant

deviation between the two methods at large radial velocities. We suspect that the

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line-measurement method fails for large radial velocities, since the algorithm used

for this method is more likely to fail for larger pixel shifts. We choose to adopt the

radial velocities measured by the cross-correlation method for all of the stars, except

for three stars, when the cross-correlation failed and produced a spurious result, i.e.,

an unbelievably large radial velocity. In those cases we adopt the radial velocity as

measured with lines. We report high-precision radial velocities for the 47 stars with

these measurements.

Figure 3.3 shows a comparison of high-precision radial velocities and low-

precision cross-correlation radial velocities for the 44 stars with both types of

measurements. It is clear that our estimated internal error for the low-precision

radial velocities is appropriate: the scatter in this figure is ∼35 km s−1. Figure 3.3

shows the low-precision radial velocities are systematically overestimated by about

42 km s−1. Therefore we subtract 42.6 km s−1 from all of the derived radial velocities.

We suspect that this offset is due to a systematic error in measuring the centroid of

the night sky emission lines used to set the reference wavelength scale of the spectra.

Once we subtract this offset the difference between the high- and low-precision radial

velocities is VR = 0 ± 38 km s−1. We adopt 40 km s−1 as the error estimate on these

radial velocities.

In Table 3.2 we present the final derived radial velocities for each program star.

Stars for which high-precision radial velocities are reported are indicated in Column

(3).

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As a check on our method, we compare our radial velocity measurements with

the high-precision (∼2 km s−1) radial velocities measured by Carney et al. (1996).

Figure 3.4 shows a comparison of the radial velocities derived in this study with

those presented by Carney et al. (1996). We find that the radial velocities of the

61 stars in common between these two works are comparable, with a zero-point

offset of 11.6 km s−1 and a scatter of 41 km s−1, comparable with the errors of the

present work. This is consistent with the errors measured in our radial velocities.

This figure also demonstrates that our choice of the cross-correlation method over

the line-measurement method was correct: the scatter for higher radial velocities is

about the same as at low radial velocities.

3.3.2. Simulated Photometry

As a check on the accuracy of our spectrophotometry, we have used the

combined 3800-8000 A spectra of each star with all three bands to simulate BVR

photometry. We integrate across each photometric bandpass and compare the results

with the photometric measurements presented in Chapter 2.

We are able to derive standard optical photometry from our spectrophotometry

for the B, V, and R bands. We reproduce the accurate and precise (i.e., good to

≈1-2%) photometry from Chapter 2 to about 13% in B-V and to about 14% in

V-R using the spectrophotometry. Figure 3.5 shows the histogram of the difference

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between the photometry of Chapter 2 and the integrated spectrophotometry

presented here.

3.3.3. Spectral Types

We estimate spectral types by comparing each spectrum to the spectra of

the 20 stars in the sample with previously measured MK spectral types (Houk &

Cowley 1975; Houk 1978, 1982; Houk & Smith-Moore 1988; Houk & Swift 1999).

These roughly estimated spectral types are presented in a histogram in Figure 3.6.

It should be kept in mind that, at present, there does not exist a Population II

equivalent of the MK spectral classification system, hence this information is of only

marginal interest and is used as only a very rough guide. We note that there are

several (19) A-type stars in the sample; these stars are most likely hot horizontal

branch stars. We also find a large number (56) of M stars in the sample; these

stars’ faint absolute magnitudes imply that they must be very nearby and may be

interesting targets for future follow-up observations.

3.3.4. Metallicity Estimates

The measured spectra allow us to estimate metallicities for the program stars.

Most of the stars are expected to have relatively low metallicity ([Fe/H]< −1), given

the selection criteria based on position in a reduced proper motion diagram (see

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Chapter 2). Furthermore, most of the target stars are F-, G-, and K-type stars (in

the color range 0.3 < (B − V )0 < 1.2). We therefore concentrate on techniques

to estimate metallicity most applicable to low-metallicity stars that fall in this

range. However, we also demonstrate that the redder M-type stars in our sample

are consistent with low metallicity as well. In addition to obtaining [Fe/H] estimates

for the stars we also obtain estimates for [C/Fe] for all of the stars in the sample. In

this paper, the terms [Fe/H] and metallicity are used interchangeably.

We obtain metallicity estimates with two different line index techniques

described below. We have obtained B spectra, in which these lines are measured,

for 291 stars. We report metallicities for 254 stars which fall in the appropriate

temperature ranges for these line-index methods.

Measurement of Line Indices

A technique that is commonly employed to determine metallicity from

moderate-resolution spectra is to use line indices to measure flux from the stars in

the region of metallic-line absorption features. A line index is formed by integrating

the flux between two wavelengths in the spectrum in the vicinity of a particular

absorption feature, and comparing to the integrated flux in a nearby continuum

region (i.e., a region free of absorption features). The particular indices we measure

are described by Beers et al. (1999) and are defined in Table 3.3. These include

measures of several strong lines such as the Ca II K line, the Hδ Balmer line, and

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the G-band (referring to the complex of CH absorption features near 4310 A that is

most pronounced in F-K–type stars).

Line indices were measured in each spectrum using the IRAF utility

EQWIDTHS, which uses red and blue side bands to linearly interpolate a continuum

across the line band. The equivalent width of the line is then obtained by measuring

the flux in the line compared to the continuum. We measured all of the line indices

listed in Table 3.3, and present the indices for the 291 stars for which we have

obtained spectra in the appropriate range for these indices in Table 3.4. In this

Table, stars for which the index was either unmeasureable (e.g., the spectrum did

not cover the wavelength range of the index) or negative (indicating the presence of

emission or simply due to noise) are reported as “—”.

Derivation of Metallicities

Metallicities of the candidate subdwarfs are determined using two different

methods: the line-index technique of Beers et al. (1999) and the line-index technique

of Rossi et al. (2005).

The Beers et al. (1999) method measures the strength of the Ca II K line at

3933.7 A in moderate-resolution spectra to estimate metallicity in dwarf and giant

stars. In particular, it uses the KP index, an optimum equivalent width measurement

of the Ca II K line formed from selecting one of the K6, K12, or K18 indices

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depending on the strength of the Ca II K feature, compared with the strength of the

4101.7 A Hδ line (i.e., the HP2 index, again, chosen from HD12 or HD24 depending

on the strength of the Hδ feature in the given star). The method is applicable only

for the color range 0.3 ≤ (B − V )0 ≤ 1.2; this constraint is specified because for

(B − V )0 < 0.3 the Ca II K line is often too weak faint to measure accurately, while

for (B − V )0 > 1.2 the Ca II K line approaches saturation. Most of our data are

ideally suited to this technique, since the majority of the stars in the sample have

B spectra and fall in the appropriate color range. We use this line-index method to

derive [Fe/H] for most of the stars in the sample; the method fails when the index

measurement is negative (typically due to a noisy spectrum) or when the star falls

outside of the specified color range. (Beers et al. 1999) estimate that this technique

is precise to ∼0.2 dex, but note that it becomes slightly worse than this for more

metal-rich stars.

Rossi et al. (2005) present another line-index approach to estimate metallicities,

which has been calibrated for Carbon-Enhanced Metal-Poor (CEMP, [C/Fe] > +0.5

in our definition) stars. This method uses two of the line indices used by Beers

et al. (1999) to derive regression relations for [Fe/H] and [C/Fe] in CEMP stars,

i.e., stars with a strong 4310 A GP (G-band) index; however, the method can be

used to estimate [Fe/H] and [C/Fe] for non-CEMP stars as well. In particular, this

technique uses the KP index and the (J − K)0 color to measure [Fe/H] and the KP

and GP indices to estimate [C/Fe]. This technique is applicable over the color range

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0.2 < (J − K)0 < 0.8, corresponding to about 0.3 < (B − V )0 < 1.5. We measure

[Fe/H] and [C/Fe] for all of the stars in the sample using this technique. This

method provides estimates for both [Fe/H] and [C/Fe]; Rossi et al. (2005) estimate

that these abundances are precise to 0.25 dex. It should be noted that this method

is calibrated primarily with spectra of giants; this may affect the precision of the

method when applied to the dwarfs discussed here.

The final metallicities are obtained by choosing one of the above methods for

each star. The Beers et al. (1999) method was used preferentially, since it is the most

well-known method. We used this method for 231 of the 291 stars with B spectra. If

this method failed, if one of the indices used in this method was bad, or if the star

was carbon-enhanced ([C/Fe] > +0.5), then the Rossi et al. (2005) metallicity was

adopted. We use the Rossi et al. (2005) metallicity estimate for 23 stars. We are

unable to measure a metallicity for 37 stars, generally because they were either too

hot or too cool for either of these methods to apply.

Table 3.5 presents the final adopted metallicities for 254 program stars. Column

(1) lists the NLTT identifier of the star, Columns (2) and (3) list the value of

[Fe/H] measured by the Ca II K method of Beers et al. (1999) and the line-index

method of Rossi et al. (2005) Column (4) lists the carbon abundance for each star

as measured by the Rossi et al. (2005) method. Column (5) lists the final adopted

value for [Fe/H], while Column (6) indicates which method was used to determine

the metallicity.

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Comparison With High Resolution Metallicity Estimates

We compare the above metallicities to metallicities listed in the catalog of

Cayrel de Strobel et al. (2001). This catalog is a compilation of previously published

atmospheric parameters determined from high-resolution, high S/N spectra from a

variety of sources. The 2001 version of the catalog contains bright F, G, and K stars

in the Galactic field as well as in certain stellar clusters.

The Cayrel de Strobel et al. (2001) catalog contains 26 of the stars in the

present sample. We compare the final metallicities derived here with the metallicities

obtained from high-resolution spectroscopy in Figure 3.7. We reproduce the

high-resolution metallicities to −0.10±0.40 dex. This scatter should be considered

a very generous upper limit on the accuracy of our metallicity determinations,

since it includes scatter associated with the fine-analysis measurements (which

differs from observer to observer). If we take 0.25 dex as representative of the

observer-to-observer scatter in the fine-analysis metallicity estimates, this indicates

that the intrinsic scatter in our medium-resolution metallicities is on the order of

0.3 dex.

Comparison to Moderate-Resolution Metallicities

Since the present sample has many stars in common with the kinematically-

selected study of Carney et al. (1996), we also compare the metallicities derived

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here with those derived by Carney et al. (1996). We find 47 stars in common with

the Carney et al. (1996) sample; we compare our metallicities in Figure 3.8. Our

metallicities reproduce those of Carney et al. (1996) to −0.40±0.39 dex. The 0.4 dex

offset between the two metallicity determinations seems large and may be indicative

of a systematic offset in our determination of metallicities. Carney et al. (1996) cites

the accuracy of their metallicities to be 0.1 – 0.2 dex; this implies our metallicities

are accurate to 0.33 – 0.38 dex. We adopt a final accuracy for our metallicities of

0.35 dex.

Comparison to Gizis (1997) Metallicities for Low-Mass Stars

The cooler stars in the sample (i.e., those with (B −V )0 >1.2) lie outside of the

color range over which the above methods are most accurate. Nonetheless, we wish

to provide confirmation that these stars are indeed metal-poor. There is currently

no reliable means of measuring metallicities of these M subdwarfs, since theoretical

models have difficulty reproducing stellar spectra at these cool temperatures. We

are able, however, to check roughly the metallicities of the cool stars in our sample.

To this end, we determine crude metallicity groupings for these 19 stars using the

luminosity classifications described by Gizis (1997). These line indices are defined in

Table 3.6. We measure line indices in the R spectra using the batch line integration

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program “blint”. Indices are constructed using the following equation, using the

TiO5 index as an example:

TiO5 =

∫ 71267135 Fλdλ/9A

∫ 70427046 Fλdλ/4A

(3.1)

The values of the indices measured in the spectra are given in Table 3.7.

The classification system for M subdwarfs described by Gizis (1997) divides

late-type stars into separate luminosity classes (i.e., dwarf, subdwarf, extreme

subdwarf) using index measurements of the CaH and TiO molecular features that

are prevalent in these late-type stars. This method is applicable for cool subdwarfs

(spectral types K7-M5) over the color range 1.2 < (B − V )0 < 2.0. The CaH indices

are compared to the TiO index and a discriminator line is drawn to separate the

three classes of stars. Figure 3.13 shows this figure using the indices measured for

the target stars. The discriminator line drawn in Figure 3.13(a) separates dwarfs

(top) from subdwarfs and extreme subdwarfs (lower right); the discriminator in

Figure 3.13(b) separates dwarfs and subdwarfs (left) from extreme subdwarfs (right).

We find that, amongst the 19 stars in the applicable color range for this classification,

all but two of the stars fall in or very near to the subdwarf range. Subdwarfs, as

defined by Gizis (1997), have −2<[Fe/H]< −1, while extreme subdwarfs are defined

to have [Fe/H]<-2. It is not surprising that we find no stars with [Fe/H]< −2: since

we find 2% of our sample of F-K stars have [Fe/H]< −2 (see § 3.4.4 below) we do not

expect to find any extremely metal-poor stars in this subset of the data. However,

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this technique is inaccurate and gives only a rough guide to the metallicity of the

sample stars.

3.3.5. Distance Estimates

Following the method outlined by Beers et al. (2000), we calculate distance

estimates for the stars in the sample based on the metallicity and absorption and

reddening-corrected magnitudes and colors, respectively, towards each star. We

report distance estimates for 235 stars.

Reddening Estimates

Most of the stars in the sample are expected to be relatively nearby (i.e., within

300 pc). Consequently, we do not large amounts of interstellar reddening in the

directions to the targets. We calculate estimates of interstellar reddening to each star

using the dust map of Schlegel et al. (1998). This work is based on measurements of

dust emission in the Galaxy made by the COBE and IRAS satellites. We assume a

V-band absorption AV = 3.1E(B − V ) and that the dust layer has a scale height of

h = 125pc. For stars within 50 pc of the sun, we assume the colors are unreddened.

The reddening to the remaining stars is obtained by reducing the total reddening

by a factor exp[−|Dsinb|/h], where |b| is the Galactic latitude. We then iterate to

obtain consistent values of E(B − V ) and D. Using this method we derive first-pass

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dereddened (B − V )0 and (J − K)0 color indices. The technique used for estimating

distances described below refines these color indices further.

Estimated Distances

The distance to each star is estimated using the method described by Beers et

al. (2000). This technique uses the (B − V )0 color index and an assumed luminosity

type to calculate the absolute magnitude (MV ) along with the metallicity of the

star. We assume that all the stars in the sample are dwarfs; the method then

uses a color-magnitude relation along with the metallicity to iteratively modify

the interstellar reddening and finally to calculate a distance. Beers et al. (2000)

estimate these distances to have an associated accuracy of ∼20%. It should be noted

that the turn-off stars in the sample will have systematically inaccurate distance

estimates since they do not lie on the linear part of the CMD; it is not feasible to

determine whether they are main-sequence stars or somewhat evolved subgiants.

This technique is applicable for stars with (B − V )0 > 1, allowing us to estimate

distances for 232 stars.

We compare these distance estimates to distance estimates derived via

main-sequence fitting. We use the color-magnitude relation given by Gould (2003)

to derive distances to each subdwarf using the observed (V − J)0 color index. This

method has an intrinsic error of 0.2 mag Gould (2003), or about 10% of the distance.

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Again, the distances to the turn-off stars may be slightly overestimated since they

do not lie on the linear part of the CMD.

Figure 3.9 shows the comparison of the two methods. If we do not consider

stars with DGould - DCB >200 pc, the original sample of 289 stars is reduced to 256

stars and the two distance estimates agree to 22±63 pc.

We plot the difference between the two distance estimates against (B − V )0 in

Figure 3.10. The distance estimates disagree for (B − V )0 >1; for this reason we use

only stars with (B−V )0 <1 in future kinematic analyses (see Chapter 4). We expect

the reason for this discrepancy is that the metallicity estimates are less robust for

the cooler stars, causing the Beers et al. (2000) method to produce a slightly larger

distance. The Gould (2003) method should be insensitive to any color effect.

Five of the stars in the sample have accurate Hipparcos distances (i.e., σπ/π

< 0.12); we report the astrometric distance measurement for these stars. Next we

adopt the Beers et al. (2000) distance unless it is unavailable, or if it is >1000 pc;

this includes 274 stars. For the remaining 13 stars we adopt the distance derived via

the Gould (2003) method.

Table 3.8 lists our final distance estimates for the sample, along with the final

(B − V )0 and (J − K)0 color indices. Columns (2) and (3) list the (B − V )0 and

(J − K)0 color indices of the star, while Column (4) lists the distance estimate

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derived for each star. Stars for which no distance estimate could be obtained are

indicated as “—”.

Comparison with Hipparcos Distances

Finally, we compare our distance estimates to the astrometric distances

measured by the Hipparcos satellite, for the stars in common. Forty stars in the

sample have parallax measurements in the Hipparcos catalog. Figure 3.11 compares

these distances to those derived with the Beers et al. (2000) method. The two

methods agree (excluding the four stars with |DHipp - Dthiswork| >200 pc ) is -8±43

pc, implying a ∼14% error in our distance determinations. We adopt a more

conservative estimate of 20% error in the distances.

3.3.6. Derivation of Effective Temperatures

Effective temperatures are determined for 290 of the stars in the sample.

Effective temperature (Teff) is measured is obtained using the technique described by

Allende Prieto et al. (2006). This method fits model spectra to the observed spectra

using a χ2 analysis to derive metallicity as well as surface gravity and effective

temperature for the target stars. Effective temperatures and surface gravities are

calculated for stars with 4500K < Teff < 9250K. Allende Prieto et al. (2006)

estimate this method yields effective temperatures precise to about 150 K.

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Figure 3.12 plots Teff as a function of (B − V )0 and of (J − K)0. This Figure

shows that temperature estimates derived here are only applicable for stars with

(B−V )0 < 0.85, corresponding to Teff=5000K, because of the way the temperatures

are calculated. Hence, from this point forward discussions involving Teff will only

include stars with Teff >5000K.

3.4. Discussion

3.4.1. Radial Velocities and Proper Motions

In Figure 3.14 we present the radial velocities and proper motions of the

sample stars as a function of metallicity. This Figure highlights the differences

between the present sample and other non-kinematically–selected samples. A

comparison of this Figure to Figure 6 of Beers et al. (2000) shows that, while our

radial velocity distribution is essentially the same, our lower limit of 0.′′018 yr−1

causes the present study to sample nearly a completely different set of stars than do

non-kinematically–selected samples. Only a small fraction of the Beers et al. (2000)

stars have proper motions µ > 0.′′018 yr−1.

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3.4.2. Metallicity Distribution

We present a histogram of the derived metallicities in Figure 3.15. The

metallicity distribution is strongly peaked at [Fe/H]=−0.8. This is somewhat

surprising since the sample should be dominated by halo stars (see Chapter 2). We

identify a significant number (28) of stars that are very metal-poor ([Fe/H]< −2).

The importance of these stars is discussed below. We discuss the metallicity

distribution of the halo in greater detail in Chapter 5.

3.4.3. Fraction of Subdwarfs

The primary goal of this project is to produce a catalog of confirmed subdwarf

stars with accurate and precise photometry that will be used, along with astrometric

distances obtained from a future satellite mission (e.g., SIM or GAIA), to calibrate

distances to distant globular clusters. We intend to confirm that these stars are

indeed subdwarfs using their placement on a Reduced Proper Motion (RPM)

diagram (see Chapter 2) and their metallicities. In Chapter 2 we showed that nearly

all of the 635 stars (with the exception of three white dwarf candidates) in the

sample with accurate photometry are clearly dwarf or turn-off stars based on their

position in an accurate RPM diagram (see Figs. 9 & 10 of Chapter 2).

Figure 3.15 in the present work shows that, of the stars with derived

metallicities, 140 of the 254 subdwarf candidates indeed turn out to have metallicities

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consistent with that of a halo population ([Fe/H]< −1 ). It should be kept in mind

that the sample may contain some (or many) thick disk stars, and that even some of

the stars with [Fe/H]< −1 may be members of the so-called metal-weak thick-disk

population (MWTD; see Chiba & Beers 2000). This is particularly true since many

of our stars are quite nearby, where the density of the thick disk dominates over that

of the halo. The likely MWTD stars can only be identified by consideration of their

space motions. The remaining 112 stars have [Fe/H]> −1, implying that they are

most likely members of the thick disk. We note the re-discovery of one extremely

metal-poor ([Fe/H]< −3) stars in our sample, discussed in more detail below. In

Chapter 4 we will better constrain the sample by using kinematic information to

divide the sample into separate halo and thick disk populations.

Given the large numbers of metal-poor stars we have identified in our sample

(55% with [Fe/H]< −1, 91% with [Fe/H]< −0.5), we conclude that the method of

selecting subdwarfs from a population of high proper motion stars using a RPM

digram described in Chapter 2 is very efficient at selecting metal-poor stars.

3.4.4. The “Effective Yield” of Metal-Poor Stars

A quantity often referred to as the “effective yield” of a sample of metal-poor

stars indicates what percentage of the sample is metal-poor (MP; [Fe/H] < −1),

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very metal-poor (VMP; [Fe/H]< −2), extremely metal-poor (EMP; [Fe/H]< −3),

ultra-metal-poor (UMP; [Fe/H]< −4), and so on.

Table 3.9 presents the “effective yield” for the current sample and compares

it with previous searches for metal-poor stars. Information on previous surveys are

taken from Beers & Christlieb (2005). We emphasize here that the current sample,

though not constructed with the intention of searching for VMP stars, in fact finds

VMP stars with an efficiency comparable to previous studies constructed for the sole

purpose of finding metal-poor stars. If further constraints (e.g., color or observed

magnitude cuts) were placed on the selection criteria used for this sample perhaps

an even higher effective yield could be achieved. It is also noteworthy that this

sample, unlike samples derived from surveys with rather faint bright limits (e.g.,

the Sloan Digital Sky Survey; York et al. 2000), is capable of finding targets with

V < 14 mag (the SDSS bright magnitude limit is g =14 mag). This is especially

important when searching for candidates for follow-up high-resolution spectroscopy:

even with today’s 8-10m class telescopes, fine-analysis of high-resolution spectra

requires relatively bright targets.

Ten of the 28 VMP stars in our sample are previously unreported anywhere

in the literature other than the source papers (Gould & Salim 2003; Salim &

Gould 2003). Many more of the stars in our sample have no previous metallicity

determinations in the literature.

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We find one EMP star in the sample: NLTT 36059 ([Fe/H] = −3.03). This star

has several previous metallicity determinations; it is in the Cayrel de Strobel et al.

(2001) high-resolution spectroscopic catalog which quotes a metallicity of [Fe/H] =

−3.38. Carney et al. (1996) cites a metallicity for NLTT 36059 of [Fe/H] = −2.8.

Both of these measurements agree well with our determination, and confirm that

this is indeed an extremely metal-poor star.

3.4.5. Carbon-Enhanced Metal-Poor Stars

CEMP stars are especially interesting to study, because they provide insight

into the nucleosynthetic history of the early Galaxy, in particular for the metal-poor

asymptotic giant branch stars that are likely to be responsible for the production

of around 80% of the CEMP stars (Aoki et al. 2006, in prep.). These stars have

recently been shown to be more frequent at low metallicity (Norris, Ryan, & Beers

1999; Rossi et al. 1999). Lucatello et al. (2006, in prep.) demonstrate, based on

high-resolution spectroscopic analysis of an unbiased sample of low-metallicity stars,

that a lower limit on the frequency of CEMP stars amongst VMP stars is 20%.

Beers & Christlieb (2005) note that for the small number of stars with [Fe/H]< −3.5

based on available high-resolution spectroscopy, the fraction of stars with [C/Fe]

≥ +1.0 is 40%, including the only two hyper metal-poor ([Fe/H]< −5.0) stars

known: HE 0107-5240 (Christlieb et al. 2002) and HE 1327-2326 (Frebel et al.

2005). If CEMP stars were more commonly formed in the past, when these old, very

139

metal-poor stars were formed, they may suggest that conditions early in the history

of the Galaxy were strikingly different from those found today.

We find that five stars in the present sample are carbon-enhanced ([C/Fe]>+0.5).

Table 3.10 lists the V magnitudes and the Fe and C abundances for these stars. For

reference, the spectra of the five CEMP stars are shown in Figure 3.16. Three of

these stars (NLTT 2404, NLTT 8783, and NLTT 49821) have several references in

the literature, while the two remaining stars (NLTT 2856 and NLTT 19550) have no

previous metallicity measurements in the literature. Only one of these stars (NLTT

2404) has previously been identified as a CEMP.

NLTT 2404 (LP 706-7) is a well-known strongly carbon-enhanced star studied

by many groups. Norris, Ryan, & Beers (1999) find [Fe/H]=−2.74±0.16 and

[C/Fe]=+2.15±0.23 with high-resolution spectroscopy. Aoki et al. (2002) also use

high-resolution abundance analysis and find [Fe/H]=−2.55 and [C/Fe]=+2.1 for this

star. Both of these determinations agree within the 1 σ errors with our estimate of

[Fe/H]=−2.66 and [C/Fe]=+2.42.

NLTT 8783 is a weakly carbon-enhanced star with [C/Fe]=+0.73. Ivans et

al. (2003) finds Fe/H=−1.94, while James (2000) finds [Fe/H]=−1.96. The high

resolution catalog of Cayrel de Strobel et al. (2001) reports [Fe/H]=−1.51. These

are all significantly less metal-poor than our estimate of [Fe/H]=−2.86. There are

apparently no carbon abundance measurements of this star in the literature.

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NLTT 49821 is another weakly carbon-enhanced star that has been studied by

one survey other than the rNLTT. Ryan & Norris (1991) estimate [Fe/H]=−2.24 for

NLTT 49821. This agrees well with our estimate of [Fe/H]=−2.3.

We find no mention of NLTT 2856 and NLTT 19550 in the literature (other

than the source papers). NLTT 19550 is relatively strongly carbon enhanced,

and with V =11.10 dex is an excellent candidate for high-resolution follow-up.

We find [Fe/H]=−2.69 and [C/Fe]=+1.57 for this star. NLTT 2856 is a weakly

carbon-enhanced star with [Fe/H]=−2.37 and [C/Fe]=+0.73.

As expected, the frequency of CEMP stars in the present sample increases for

stars with otherwise low metallicities. We plot [C/Fe] against [Fe/H] in Figure 3.17.

The familiar trend of increasing spread in [C/Fe] with decreasing [Fe/H] (Rossi et

al. 1999) is observed. While this trend is now well-known, its cause is not. There

are currently several proposed mechanisms for the enhanced carbon abundance in

very metal-poor stars. It is conceivable that the carbon in at least some of these

CEMP stars is primordial, originating from the first generation of stars (Woosley &

Weaver 1995; Karlsson 2006; Piau et al. 2006). Alternatively, an asymptotic giant

branch companion to the star might have transferred carbon-rich material before

its death (McClure, Fletcher, & Nemec 1980). Finally, unusual mixing may occur

during the helium core flash in low-metallicity stars (Fujimoto, Ikeda, & Iben 2000).

These possibilities are summarized by Beers & Christlieb (2005). The discovery of

141

additional extremely metal-poor stars with enhanced carbon abundances will help to

resolve this problem in the future.

Despite much recent work in this field, there are currently relatively few CEMPs

known. The largest sample of carbon-enhanced stars to date has been compiled by

Lucatello et al. (2006, in prep.); this sample contains only 54 CEMP stars. While

future surveys, especially the SDSS-II extension known as the Sloan Extension for

Galactic Understanding and Exploration (SEGUE), will undoubtedly uncover many

of these types of stars, the SDSS bright magnitude limit (g >14 mag) is a bit faint

for efficient high-resolution follow-up studies, even with 10-m class telescopes. The

selection criteria described in this work may represent another way to find these

rare, old stars. Again we emphasize that due to the nature of the sample selection,

most of these stars are bright and are ideal candidates for follow-up high-resolution

spectroscopic studies.

3.4.6. Hipparcos Stars in the Sample

For the stars with known astrometric distances, we can construct a color-

magnitude (CMD) diagram for stars of different metallicity classes. If such a

diagram were well-populated, it could perhaps be used to estimate metallicities of

metal-poor stars based on color indices alone. Unfortunately there are currently very

142

few metal-poor stars with measured astrometric distances, mainly due to the rather

bright (V ∼12) limiting magnitude of the Hipparcos satellite (ESA 1997).

Nonetheless, we construct a CMD for the stars in the sample with known

astrometric distances. Forty of the stars in the current sample with measured

metallicities are also in the Hipparcos catalog. Figure 3.18 shows the CMD for stars

in three metallicity classes, [Fe/H]> −1, −2<[Fe/H]< −1, and −3<[Fe/H]< −2. No

stars in this sample having [Fe/H]< −3 are in the Hipparcos catalog.

We note the presence of one star that is a significant outlier in the CMD. This

star is NLTT 2404, our well-known CEMP star (see § 3.4.5).

3.4.7. Color-Color Plot

In Chapter 2 we presented a color-color plot, comparing our new photometric

measurements with theoretical models in order to confirm that our sample was

consistent with a metal-poor (i.e., [Fe/H]< −1) population. Using the metallicities

derived in this paper we can now compare the observations to the theoretical

isochrones in much greater detail.

In Figure 3.19 we present a (J − K)0, (B − V )0 color-color diagram using

different symbols for stars in 1-dex metallicity bins. As in Chapter 2, we compare

the observations with the Yonsei-Yale (Y2; Kim et al. 2002) isochrones for a 10 Gyr

143

population with [α/Fe] = 0. It is now even more clear that the isochrones reproduce

the photometry well.

We compare the photometry to the isochrones for four metallicity bins in

Figure 3.20. While theory and observations agree well in general, there are a few

specific instances where there is some mismatch. For instance, the models for stars

with [Fe/H]> −1 deviate from the observations for (B − V )0 >0.8. There is also

significantly more scatter in the stars with −2< [Fe/H] < −1 than for the other

metallicity bins. This sort of comparison between accurate observations and models

can be used to improve future versions of the models. The infrared data presented

here are also important: it is currently difficult to obtain infrared photometry of the

very faint lower main sequence stars in distant globular clusters. The infrared data

presented here provide information on the shape of the lower main sequence in the

infrared.

3.5. Conclusions

A high-quality spectroscopic dataset of a sample of proper-motion-selected

candidate subdwarfs has been presented. From these data we derive metallicities,

reddenings, distances, spectral types, and effective temperatures for 254 stars, as

well as radial velocities for 298 stars.

144

We conclude that the method described in Chapter 2 for selecting candidate

halo subdwarfs from a reduced proper motion diagram is very successful. This

should be considered in future surveys that intend to study the halo and thick disk

populations.

Finally, we point out that selecting candidate subdwarfs from an RPM diagram

also includes large numbers of very metal-poor stars with [Fe/H]<-2; in particular,

this method has provided nearly as high an “effective yield” of these stars as previous

studies (e.g., the HK survey) constructed with the sole purpose of discovering very

metal-poor stars. We plan to employ a refinement of this technique in the future to

carry out additional searches for bright, very metal-poor stars.

145

4000 5000 6000 7000 8000

NLTT 57

4000 5000 6000 7000 8000

NLTT 341

4000 5000 6000 7000 8000

NLTT 812

4000 5000 6000 7000 8000

NLTT 1059

Fig. 3.1.— Representative sample of spectra of the sample stars; see the Appendix

for all of the spectra.

146

Fig. 3.2.— Comparison of the two methods used to derive low-precision radial

velocities. The one-to-one correlation line is shown.

147

Fig. 3.3.— Comparison of the high-precision radial velocities with the low-precision

radial velocities. The one-to-one correlation line is shown. The scatter about the

one-to-one correlation is ∼39 km s−1, confirming our estimate of the internal errors

for the low-precision radial velocities. The 42 km s−1 offset seen in this comparison

is removed to form the final low-precision radial velocities.

148

Fig. 3.4.— Comparison of radial velocities derived in this work with those measured

by Carney et al. (1996). The one-to-one correlation line is shown. The scatter about

the one-to-one correlation is ∼41 km s−1, consistent with our estimate of the internal

errors for our low-precision radial velocities. The 11 km s−1 offset between these two

datasets is within the errors of our low-precision radial velocities.

149

-1 -0.5 0 0.5 10

20

40

60

80

-1 -0.5 0 0.5 10

20

40

60

80

Fig. 3.5.— Comparison of B-V and V-R photometry measured in Chapter 2

and that measured by integrating over the spectra presented in this work. The

spectrophotometry in the B-V color index is precise to about 0.13 mag, while that in

the V-R color index is precise to about 0.14 mag.

150

0

20

40

60

80

100

Fig. 3.6.— Histogram of the first-pass estimates of spectral types.

151

Fig. 3.7.— Comparison of the metallicities derived here to those measured with

high-resolution spectroscopy by Cayrel de Strobel et al. (2001). We reproduce the

high-resolution metallicities to −0.10±0.40 dex. If the two outliers are removed, we

reproduce the high-resolution measurements to −0.11±0.20 dex.

152

Fig. 3.8.— Comparison of the metallicities derived here to those determined

previously with moderate-resolution spectroscopy by Carney et al. (1996). We

reproduce the Carney et al. (1996) metallicities to −0.4±0.39 dex, implying an error

in our determination of 0.35 dex and a possible systematic offset of ∼ −0.4 dex.

153

Fig. 3.9.— Comparison of the Beers et al. (2000) method of determining distances

and that of Gould (2003).

154

Fig. 3.10.— Comparison of the two distance methods as a function of (B − V )0.

155

Fig. 3.11.— Comparison of the final distance estimates to distances measured by

Hipparcos.

156

Fig. 3.12.— Teff as a function of (B − V )0 and (J − K)0.

157

Fig. 3.13.— Determination of luminosity class for the red stars in the sample based

on Gizis (1997) indices.

158

Fig. 3.14.— Radial velocities and proper motions of the sample stars as a function

of metallicity.

159

Fig. 3.15.— Metallicity distribution of the sample.

160

Fig. 3.16.— Spectra of the five carbon-enhanced metal-poor stars in the sample.

161

Fig. 3.17.— [C/Fe] vs. [Fe/H] for all stars with derived metallicities. The expected

trend of increasing scatter in [C/Fe] with decreasing [Fe/H] is observed.

162

Fig. 3.18.— CMD for the Hipparcos stars in the survey. Open circles represent

[Fe/H]> −1, filled circles represent −2<[Fe/H]< −1, and filled triangles represent

−3<[Fe/H]< −2.

163

Fig. 3.19.— (B − V )0—(J − K)0 color-color plot with metallicities. Open circles

represent [Fe/H]> −1, filled circles represent −2<[Fe/H]< −1, filled triangles

represent −3<[Fe/H]< −2, and stars represent [Fe/H]< −3.

164

Fig. 3.20.— (B − V )0—(J −K)0 color-color plot with metallicities. Symbols are the

same as in Figure 3.19. The isochrones reproduce the photometry relatively well for

all four metallicity bins.

165

Observatory Date Setting Grating

MDM 20 Mar 2003 B 350 l/mm

MDM 21 Mar 2003 G 350 l/mm

MDM 09 Jun 2003 R 350 l/mm

MDM 10 Jun 2003 B 350 l/mm

MDM 11 Jun 2003 G 350 l/mm

MDM 12 Jun 2003 R 350 l/mm

MDM 13 Jun 2003 R 350 l/mm

MDM 14 Jun 2003 R 350 l/mm

CTIO 22 Jul 2003 B 26

CTIO 23 Jul 2003 B 26

CTIO 24 Jul 2003 G 35

CTIO 25 Jul 2003 G 35

CTIO 28 Jul 2003 R 35

CTIO 26 Sep 2003 B 26

CTIO 27 Sep 2003 B 26

CTIO 28 Sep 2003 G 35

(cont’d)Table 3.1. Observing Log

166



CTIO 29 Sep 2003 R 35

CTIO 30 Sep 2003 R 35

CTIO 03 Oct 2003 R 35

CTIO 04 Oct 2003 R 35

CTIO 05 Oct 2003 R 35

MDM 29 Oct 2003 G 350 l/mm

MDM 30 Oct 2003 G 350 l/mm

MDM 31 Oct 2003 B 350 l/mm

MDM 01 Nov 2003 R 350 l/mm

MDM 03 Nov 2003 R 350 l/mm

MDM 04 Nov 2003 R 350 l/mm

MDM 05 Nov 2003 B 350 l/mm

MDM G 350 l/mm

MDM 09 Nov 2003 R 350 l/mm

MDM 27 Jan 2004 R 350 l/mm

MDM R 350 l/mm

(cont’d)

167



MDM B 350 l/mm

MDM 29 Jan 2004 rv 1800 l/mm

MDM 30 Jan 2004 rv 1800 l/mm

MDM 01 Feb 2004 rv 1800 l/mm

MDM 14 Apr 2004 R 350 l/mm

MDM 15 Apr 2004 R 350 l/mm

MDM 16 Apr 2004 R 350 l/mm

MDM 18 Apr 2004 G 350 l/mm

MDM G 350 l/mm

CTIO 10 Jun 2004 R 35

CTIO 11 Jun 2004 R 35

CTIO 12 Jun 2004 G 35

CTIO 13 Jun 2004 G 35

CTIO 14 Jun 2004 B 26

CTIO 15 Jun 2004 B 26

MDM 01 Jul 2004 B 350 l/mm

(cont’d)

168



MDM 03 Jul 2004 rv 1800 l/mm

MDM 04 Jul 2004 rv 1800 l/mm

MDM 05 Jul 2004 rv 1800 l/mm

MDM 07 Oct 2004 R 350 l/mm

MDM 08 Oct 2004 G 350 l/mm

MDM 09 Oct 2004 G 350 l/mm

MDM R 350 l/mm

MDM 06 Jan 2005 R 350 l/mm

MDM 07 Jan 2005 R 350 l/mm

MDM 08 Jan 2005 R 350 l/mm

MDM 26 Aug 2005 rv 1800 l/mm

169

NLTT ID VR Hi-Res

km s−1

57 163.2

341 −163.1

812 −195.3

1059 −127.3

1635 −28.7

1645 −177.9

1870 −143.5

2045 −79.4

2205 71.5

2404 130.3

2427 −150.4

2856 −91.8

2868 −145.4

3516 −46.9

3531 58.5

3847 34.1

(cont’d)Table 3.2. Final radial velocities for 298 stars

170


NLTT ID VR Hi-Res

km s−1

3985 −8.8

4517 −102.7

4817 −37.5

5052 34.3

5193 −50.0

5222 4.1

5255 152.0

5404 −51.9

5506 −50.2

5711 −23.9

5881 −3.7

6415 5.0

6774 −8.0

7299 7.9

7360 −173.8

7364 71.9

(cont’d)

171


NLTT ID VR Hi-Res

km s−1

7415 −32.1

7417 −152.6

7966 −65.3

7968 −163.1

8034 249.6

8227 252.8

8230 −167.1

8319 13.3

8323 −64.5

8459 −122.1

8720 −127.4

8783 232.9

8833 −39.7

9026 −7.3

9382 44.4

9437 −68.3

(cont’d)

172


NLTT ID VR Hi-Res

km s−1

9578 48.9

9597 9.9

9628 −120.6

10119 −42.9

10536 48.3

10821 262.7

10850 33.2

10972 −15.6

11007 192.0 H

11462 −72.4

11469 −9.2

11486 109.3

11515 −112.9

11584 −81.2

11795 −24.5

12017 66.8

(cont’d)

173


NLTT ID VR Hi-Res

km s−1

12103 7.0

12350 173.2

12845 321.2

12856 −171.7

12986 161.3

13344 −217.4

13470 109.5

13641 179.0

13660 61.6

13770 −23.2

13811 −19.4

13899 −19.2

14091 −133.8

14131 −132.5

14169 130.0

14197 165.4

(cont’d)

174


NLTT ID VR Hi-Res

km s−1

14391 118.7

14606 17.0

14658 55.4

14805 0.0 H

14822 −66.8

15161 258.3 H

15183 143.1

15218 −25.0

15529 364.0

15788 2.4

15881 108.8

15939 −74.7

15973 −189.4 H

15974 −171.7

16030 134.7

16242 30.4 H

(cont’d)

175


NLTT ID VR Hi-Res

km s−1

16250 48.9

16320 63.6

16444 −34.1

16573 120.0

16579 64.4

16606 −135.8

16849 −125.4

17039 −104.6

17136 48.6

17154 −24.0

17231 162.7

17234 −94.1 H

17485 87.4

17738 50.1 H

17786 −144.2

17872 48.4 H

(cont’d)

176


NLTT ID VR Hi-Res

km s−1

18292 178.3

18424 −9.8

18502 249.6 H

18799 180.0 H

18982 20.8

19210 −76.7

19550 −56.2

19643 62.3 H

20232 47.8 H

20684 95.6

20691 −6.8

20700 −13.0

20792 171.3

20980 111.3 H

21084 −28.6

21744 302.1 H

(cont’d)

177


NLTT ID VR Hi-Res

km s−1

22026 262.9

22053 218.6

22520 123.3 H

24839 −15.6

24984 16.8

25177 154.1

25218 −37.1

25234 129.9

26482 194.0

26650 −165.3

27436 −21.4

27831 −7.7 H

28199 98.9

28459 115.4

28955 177.0

29551 30.7 H

(cont’d)

178


NLTT ID VR Hi-Res

km s−1

29905 52.4

29933 102.3 H

30274 228.1

30400 124.6

30462 −99.0

30838 19.8

31146 −80.0

31233 −4.0

32316 5.5 H

32648 189.3

33146 −21.8

33221 −31.6

33371 194.0

33823 35.6

33971 55.4

34051 163.2

(cont’d)

179


NLTT ID VR Hi-Res

km s−1

34628 −112.3

35068 210.4

35890 185.9

36059 82.2 H

36446 122.4 H

36520 47.6

36564 72.5

37158 255.6

37658 −81.2

37807 −45.3

37960 −92.4

38221 −33.3 H

38311 83.3

38779 103.3

38814 1.2

39121 −113.1

(cont’d)

180


NLTT ID VR Hi-Res

km s−1

39456 323.9

39457 316.2

39670 −59.2 H

40003 −90.4

40313 −266.7

40723 90.9

41218 186.7

42183 −83.1

42301 −77.8 H

42743 45.3

43100 39.7

43291 61.7

43444 −99.7

43887 79.2

43923 258.8

44039 −120.8 H

(cont’d)

181


NLTT ID VR Hi-Res

km s−1

44226 −260.2 H

44568 78.8 H

44639 −154.2 H

44683 −53.7 H

44749 65.2

45011 −4.5

45026 −73.6 H

45204 −16.7

45215 100.2

45367 74.9

45416 −64.0

45609 −39.8 H

45616 87.9 H

45754 13.2

46039 32.6 H

46215 −19.5

(cont’d)

182


NLTT ID VR Hi-Res

km s−1

46730 −61.1

46738 71.7

46798 60.8 H

47073 −13.7

47132 13.8

47242 14.0

47257 −132.9 H

47331 38.4 H

47425 79.5

47481 33.5 H

47525 −76.1

47543 −62.3 H

47711 254.2

47811 184.3

47944 −4.7

47972 −210.9

(cont’d)

183


NLTT ID VR Hi-Res

km s−1

48056 124.5

48062 39.7 H

48133 68.3

48149 66.5

48255 −96.8

48592 −54.6 H

48658 −153.4

48866 −135.6

48925 89.6

49082 87.8

49226 50.4 H

49245 35.8

49301 −2.2

49482 18.9

49487 3.0

49497 −298.5

(cont’d)

184


NLTT ID VR Hi-Res

km s−1

49611 85.3

49618 −90.5

49624 −13.5

49627 58.1

49726 −4.3

49821 −37.7

49872 −122.4

49949 −111.3

50185 0.4 H

50190 −22.5

50215 −4.6

50257 −35.6

50270 −25.5 H

50339 15.9

50474 −130.9

50556 −103.1

(cont’d)

185


NLTT ID VR Hi-Res

km s−1

50759 −98.9

50869 −143.6

50911 43.4 H

50937 −253.0

51824 86.2 H

51856 −150.8

52089 −53.6

52398 −133.1

52456 32.2

52666 49.0

52816 −137.9

52894 −145.1

53274 −24.6 H

53480 −290.2

53707 −136.9 H

53781 −85.1

(cont’d)

186


NLTT ID VR Hi-Res

km s−1

53801 6.9

53823 −44.6

54027 −48.6

54088 157.6

54184 −79.4

54620 −48.0

54730 21.4

55603 7.1

55732 16.1

55733 −216.7

55942 −128.6

56002 −163.1

56290 −105.4

56534 −161.7

56774 −114.5

56818 −167.8

(cont’d)

187


NLTT ID VR Hi-Res

km s−1

56855 9.6

57038 107.6

57452 19.1

57564 −20.9

57631 49.1

57647 −129.5

57741 −3.5

57781 −33.3

57856 26.9

58071 −154.1

188

Line Line Band Blue Sideband Red Sideband

(A) (A) (A)

Ca II (K6) 3930.7 - 3936.7 3903.0 - 3923.0 4000.0 - 4020.0

Ca II (K12) 3927.7 - 3939.7 3903.0 - 3923.0 4000.0 - 4020.0

Ca II (K18) 3924.7 - 3942.7 3903.0 - 3923.0 4000.0 - 4020.0

Hδ (HD12) 4095.8 - 4107.8 4000.0 - 4020.0 4144.0 - 4164.0

Hδ (HD24) 4089.8 - 4113.8 4000.0 - 4020.0 4144.0 - 4164.0

G-band (GP) 4297.5 - 4312.5 4247.0 - 4267.0 4362.0 - 4372.0

Hγ (HG12) 4334.5 - 4346.5 4247.0 - 4267.0 4415.0 - 4435.0

Hγ (HG24) 4328.5 - 4352.5 4247.0 - 4267.0 4415.0 - 4435.0

Table 3.3. Line indices from Beers et al. (1999)

189

NLTT ID K6 K12 K18 HD12 HD24 GP HG12 HG24

57 3.19 4.64 5.03 2.89 3.76 1.15 2.94 3.93

341 4.15 6.90 8.29 1.45 1.34 3.46 1.40 1.55

812 4.18 6.88 8.14 1.69 1.64 3.21 1.69 1.69

1059 4.34 7.91 10.57 0.55 — 4.76 — —

1231 3.72 5.71 6.48 2.25 2.56 2.05 2.30 2.86

1635 4.26 7.51 9.54 1.03 0.71 4.21 1.07 0.78

1645 3.51 6.60 9.07 1.66 2.35 1.80 — —

1870 4.36 7.66 9.65 1.31 1.00 4.66 1.13 1.10

2045 3.45 6.32 8.47 0.18 — 4.62 — —

2205 3.93 7.27 10.09 1.32 0.87 3.97 — —

2404 1.40 1.68 1.61 2.74 3.40 4.06 2.60 3.45

2427 4.36 7.61 9.56 0.82 0.36 4.36 0.50 0.32

2856 2.95 5.15 6.30 — — 7.57 2.81 5.60

2868 4.20 7.65 10.09 0.76 0.33 5.08 0.94 1.48

3516 4.14 6.88 8.18 1.91 1.96 3.03 1.73 1.86

3531 4.51 7.59 9.41 0.79 0.17 5.98 0.98 0.58

(cont’d)Table 3.4. Measured line indices

190



3847 9.64 13.50 15.11 — — 4.48 1.55 —

3985 4.78 7.99 9.97 1.21 0.42 5.11 0.18 —

4517 4.15 7.28 9.70 1.37 0.95 3.60 — —

4817 3.82 5.91 6.72 2.36 2.78 1.99 2.35 2.81

5052 3.97 6.97 8.58 0.63 0.46 3.17 — —

5193 4.35 7.61 9.56 0.60 0.08 4.40 0.56 0.32

5222 1.81 2.41 2.46 2.47 3.04 0.66 2.50 3.26

5255 4.06 6.68 7.92 1.76 1.79 2.86 1.74 1.95

5404 — — — 1.30 1.16 3.56 1.08 0.92

5506 3.71 5.50 6.11 1.71 1.78 2.36 1.51 1.53

5711 4.25 7.37 9.24 1.41 1.20 4.46 1.38 1.25

5881 3.53 5.27 5.82 2.74 3.38 1.65 2.64 3.37

6415 3.37 5.04 5.61 2.40 2.85 1.60 2.41 3.02

6774 4.31 7.63 9.72 0.81 0.22 4.78 0.63 0.21

7299 3.07 4.34 4.67 2.93 3.83 1.20 2.89 3.83

7415 4.19 7.04 8.51 1.80 1.92 3.93 1.77 1.96

(cont’d)

191



7417 4.07 6.58 7.74 2.31 2.68 3.40 2.33 2.75

7966 4.36 7.43 8.91 0.49 — 4.30 0.38 0.07

7968 3.64 6.51 8.76 — — 5.37 — —

8034 2.84 3.92 4.17 2.84 3.64 1.06 2.82 3.53

8227 3.14 4.50 4.85 2.98 3.84 1.14 2.87 3.74

8230 4.36 8.03 10.90 0.57 — 4.49 — —

8459 4.17 7.02 8.55 1.85 1.97 3.68 1.81 2.03

8720 4.31 7.29 8.79 0.93 0.59 4.13 0.92 0.72

8783 1.92 2.40 2.44 2.66 3.40 1.15 2.57 3.34

8833 1.21 1.51 1.46 3.64 5.05 0.32 3.24 4.44

9026 4.04 6.59 7.79 1.50 1.15 3.62 1.26 1.40

9382 4.19 7.22 8.98 1.44 1.37 5.12 1.37 1.44

9437 2.79 3.84 4.08 3.10 4.10 1.02 2.78 3.60

9578 3.94 6.32 7.34 1.88 2.08 3.23 1.80 2.03

9597 2.09 2.65 2.69 3.22 4.42 0.65 3.02 4.08

9628 3.61 5.51 6.22 2.76 3.27 1.57 2.66 3.34

(cont’d)

192



10536 2.00 2.58 2.63 3.22 4.34 0.58 3.03 4.00

10821 4.38 7.57 9.78 1.04 0.44 2.90 — —

10850 3.90 6.19 7.13 1.80 1.99 2.68 1.77 2.00

11007 3.54 5.49 6.21 2.58 3.12 1.62 2.54 3.27

11462 3.34 5.88 7.78 1.66 2.50 1.36 — —

11486 3.69 6.73 8.95 0.23 — 5.45 — —

11515 4.36 7.67 9.76 0.92 0.31 4.71 1.00 0.85

11584 4.48 7.79 9.76 1.01 0.55 4.48 0.73 0.37

11795 3.31 4.89 5.32 2.30 2.74 1.76 2.28 2.70

12017 4.21 7.50 9.74 0.73 — 5.43 0.26 —

12103 4.10 7.02 8.65 1.71 1.75 4.44 1.76 1.96

12350 3.15 4.63 5.12 2.87 3.66 1.11 3.02 3.99

12845 4.30 7.58 9.70 1.15 0.67 4.46 0.78 0.44

12856 3.58 5.66 6.52 2.67 3.37 1.76 2.64 3.39

12986 3.58 5.53 6.27 2.76 3.48 1.82 2.75 3.56

13344 4.25 7.70 10.10 0.82 0.29 4.41 0.35 —

(cont’d)

193



13470 4.08 7.61 10.38 1.12 0.59 5.06 — —

13641 3.34 6.30 8.95 1.28 1.42 3.57 — —

13660 4.24 7.79 10.45 0.58 — 4.44 — —

13770 4.22 7.21 8.84 1.33 1.14 3.76 1.32 1.28

13811 3.73 5.40 5.92 1.53 1.63 2.66 1.39 1.38

13899 3.48 5.31 6.09 2.02 2.22 2.05 1.79 1.99

14091 4.05 6.79 8.22 0.23 — 3.14 — —

14131 4.33 7.39 8.84 0.62 0.09 3.96 0.62 0.42

14169 3.67 5.77 6.51 1.55 1.58 2.64 1.42 1.33

14197 4.35 7.61 9.69 0.50 — 4.28 0.04 —

14391 4.54 8.10 10.25 0.93 0.35 4.86 0.29 —

14606 4.22 6.93 8.24 2.02 2.19 3.73 2.04 2.42

14658 3.46 5.28 5.93 2.41 2.80 3.95 2.33 2.99

14805 2.36 3.07 3.20 2.96 3.89 0.93 2.80 3.64

14822 4.10 7.58 10.29 0.41 — 5.24 — —

15161 4.11 6.66 7.82 1.98 2.18 2.89 1.86 2.02

(cont’d)

194



15183 4.37 7.81 10.39 0.68 — 5.01 — —

15218 4.13 6.98 8.55 2.07 2.03 4.25 1.97 2.09

15529 4.20 6.93 8.18 1.35 1.15 3.77 1.38 1.35

15788 4.14 6.68 7.79 2.01 2.25 2.81 2.03 2.31

15881 4.19 7.29 9.66 0.99 — 4.67 — —

15939 4.02 6.50 7.56 2.45 2.92 2.15 2.46 3.07

15973 4.23 7.07 8.47 1.76 1.78 3.47 1.63 1.69

15974 3.48 6.20 8.27 1.11 0.71 2.92 — —

16030 4.23 7.25 9.14 0.36 — 3.51 — —

16242 4.24 7.35 9.18 1.43 1.24 4.97 1.33 1.17

16250 4.09 7.27 9.31 0.99 0.44 4.59 0.83 0.54

16320 4.30 7.45 9.52 0.93 0.15 5.80 0.66 —

16444 4.38 7.84 10.27 0.55 — 4.03 — —

16573 3.16 6.10 8.73 1.32 1.31 3.70 — —

16579 4.40 7.56 9.32 1.14 0.87 4.19 1.12 0.92

16869 4.32 7.66 9.69 0.64 0.10 4.27 0.36 —

(cont’d)

195



17039 4.09 6.57 7.74 1.17 0.99 3.28 1.19 1.22

17136 4.47 7.86 9.82 0.68 0.44 4.35 0.09 —

17234 4.22 7.08 8.57 2.00 2.22 4.36 2.02 2.29

17485 2.40 3.13 3.26 2.28 2.77 1.23 2.17 2.50

17738 4.32 7.55 9.61 0.93 0.40 5.43 0.65 0.11

17786 3.55 5.23 5.83 2.31 2.78 1.77 2.24 2.68

17872 3.38 4.94 5.40 2.88 3.67 1.38 2.76 3.53

18019 4.40 7.46 9.24 1.29 1.07 4.12 1.10 0.94

18424 4.39 7.73 10.02 0.72 0.03 5.41 0.32 —

19550 2.31 2.93 2.93 2.11 2.39 5.42 2.11 2.63

20232 1.42 1.72 1.66 4.63 6.79 0.45 4.42 6.49

20691 3.12 4.47 4.91 2.64 3.33 1.46 2.51 3.16

20792 3.89 6.04 6.89 2.25 2.59 2.47 2.14 2.54

20980 1.87 2.35 2.35 3.25 4.40 0.63 3.14 4.21

21084 4.16 6.88 8.20 2.10 2.40 3.64 2.18 2.45

21744 3.94 6.11 6.92 1.53 1.52 2.73 1.45 1.52

(cont’d)

196



22026 4.28 7.21 8.73 1.65 1.68 3.86 1.56 1.62

22302 3.45 4.94 5.35 2.77 3.50 1.63 2.70 3.43

22520 3.85 5.95 6.72 2.70 3.34 1.93 2.64 3.28

22752 4.38 7.84 10.26 0.80 0.06 5.29 — —

23192 4.37 7.34 8.80 1.18 1.05 4.35 1.15 1.01

24839 4.53 7.99 10.04 0.89 0.56 4.66 0.63 0.27

24984 3.35 4.86 5.29 2.79 3.55 1.25 2.72 3.44

25177 3.45 5.11 5.66 2.69 3.41 1.61 2.56 3.15

25218 2.24 4.29 6.67 1.58 2.17 1.99 — —

25234 3.79 7.01 10.16 0.37 — 5.32 — —

25521 4.68 8.40 10.95 0.88 0.20 4.53 — —

26482 4.50 8.00 10.27 0.57 — 4.32 — —

26650 1.36 1.72 1.72 3.23 4.43 0.52 3.19 4.24

27436 4.25 7.65 10.34 1.05 0.51 4.64 — —

27831 4.22 7.11 8.66 2.06 2.27 4.24 1.98 2.21

28199 4.25 7.63 10.14 0.33 — 5.16 — —

(cont’d)

197



28459 4.17 7.33 9.41 0.89 0.15 4.96 0.95 0.91

28955 2.51 3.36 3.51 2.76 3.58 0.91 2.65 3.45

29023 3.56 5.35 5.97 2.52 3.00 1.56 2.53 3.13

29551 2.98 4.14 4.44 3.64 4.97 1.08 3.52 4.81

29905 4.36 7.37 9.06 1.12 1.05 3.55 1.04 0.82

29933 3.54 5.28 5.86 2.60 3.19 1.96 2.55 3.15

30274 2.36 3.11 3.20 4.09 5.72 0.65 3.83 5.46

30400 4.40 7.63 9.75 1.03 0.85 4.76 0.81 0.31

30462 4.29 7.67 10.15 0.50 — 5.09 — —

31155 3.78 5.72 6.50 1.62 1.67 2.33 1.57 1.58

31233 4.39 7.68 9.76 0.28 — 4.48 0.34 —

31272 2.89 6.17 8.24 0.79 0.10 2.39 — —

32316 3.38 4.87 5.32 2.30 2.76 1.56 2.22 2.64

32392 4.68 8.44 10.86 0.02 — 4.86 — —

32648 4.06 6.57 7.63 0.47 0.04 3.33 0.69 0.66

33146 3.11 4.60 5.07 2.77 3.44 1.31 2.73 3.56

(cont’d)

198



33221 1.95 4.26 6.16 — — 5.57 — —

33371 4.43 7.67 9.66 0.40 — 4.01 — —

33823 4.30 7.50 9.55 0.96 0.37 5.53 0.76 0.22

33971 3.91 6.30 7.43 1.78 1.85 2.57 1.90 2.27

34051 4.33 7.29 8.87 0.29 — 3.44 0.72 1.59

34628 3.87 6.10 7.03 3.73 5.02 2.07 3.67 5.02

35068 3.61 5.52 6.24 1.22 1.15 2.50 1.35 1.32

35758 4.14 6.79 8.13 1.46 1.11 3.60 1.51 1.74

35890 3.90 6.01 6.75 1.43 1.40 3.40 1.95 2.00

36059 0.78 0.89 0.86 3.54 4.90 0.21 3.39 4.65

36446 4.11 6.61 7.68 1.84 1.97 2.90 1.67 1.74

36520 3.93 6.10 6.98 2.11 2.44 2.52 2.01 2.30

36564 4.48 7.14 8.37 1.10 0.72 3.37 1.03 0.86

37158 4.56 7.73 9.38 1.08 1.19 3.74 0.93 0.71

37658 4.05 6.51 7.43 1.34 1.47 3.28 0.66 0.61

37807 2.49 3.32 3.51 2.21 2.66 1.01 2.12 2.50

(cont’d)

199



37960 4.27 7.36 9.71 — — 6.06 0.35 —

38221 3.72 5.51 6.06 1.44 1.38 2.22 1.36 1.34

38311 3.58 5.49 6.22 2.17 2.88 1.92 2.03 2.36

38779 4.50 6.94 10.75 0.14 0.41 3.06 — —

38814 3.26 4.74 5.10 2.54 3.06 1.55 2.50 3.06

39076 4.05 6.60 7.79 2.25 2.64 2.77 1.63 2.00

39121 4.22 7.71 10.47 0.60 — 4.99 — —

39319 4.27 7.46 9.24 0.62 — 3.61 — —

39456 4.44 7.81 9.83 0.60 — 4.70 0.34 —

39457 4.41 7.90 10.26 0.40 — 4.72 — —

39670 3.32 4.73 5.18 2.08 2.46 1.81 2.00 2.28

40003 4.25 7.43 9.78 0.46 — 4.46 0.23 —

40313 3.71 6.64 8.81 1.51 1.68 2.65 — —

40723 1.99 2.64 2.80 2.49 3.09 0.75 2.65 3.79

41218 4.52 8.39 11.53 0.34 — 3.97 — —

41242 4.19 7.86 10.91 — — 3.85 — —

(cont’d)

200



42183 2.08 2.90 3.10 2.40 3.01 0.79 2.22 2.75

42301 4.30 7.24 8.81 1.84 1.96 4.10 1.77 1.86

42743 3.65 6.33 8.26 1.39 1.61 2.25 — —

43100 3.87 7.17 9.43 1.12 0.88 3.68 — —

43291 3.59 6.08 7.40 0.65 0.39 3.71 0.40 0.10

43444 3.79 7.08 10.08 1.20 1.08 3.39 — —

43675 4.67 8.19 10.42 1.03 0.56 4.49 0.10 —

43887 4.23 7.32 9.15 0.52 — 4.14 0.06 —

43923 4.41 7.87 10.36 0.47 — 4.07 — —

44039 2.07 2.79 2.94 2.81 3.68 0.70 2.67 3.45

44226 3.37 4.98 5.50 2.57 3.20 1.58 2.47 3.03

44568 3.64 5.53 6.17 2.82 3.60 1.63 2.67 3.42

44639 4.23 7.17 8.71 1.69 1.64 3.88 1.68 1.75

44683 4.19 7.20 8.93 1.41 1.18 4.87 1.28 1.14

44749 4.27 7.55 10.31 0.95 0.39 5.51 — —

45011 3.42 6.49 8.53 0.71 0.46 2.19 — —

(cont’d)

201



45026 4.20 7.30 9.20 1.56 1.53 4.55 1.45 1.40

45367 4.15 7.07 8.74 2.84 3.47 3.45 2.73 3.30

45609 4.36 7.96 10.63 0.54 — 4.41 — —

45616 3.49 5.41 6.17 2.53 3.12 1.89 2.41 2.97

45754 3.73 6.09 7.01 1.71 1.64 2.32 1.49 1.60

46039 4.27 7.21 8.73 1.89 2.00 3.33 1.88 2.01

46215 3.78 7.29 10.15 0.08 — 4.83 — —

46730 4.14 7.04 8.59 1.46 1.28 3.60 1.55 1.51

46738 4.09 6.68 7.94 1.66 1.44 2.76 1.31 1.28

47073 3.46 5.13 5.60 2.91 3.85 1.45 2.53 3.23

47132 4.31 7.82 10.24 0.47 — 5.26 0.10 —

47242 4.28 7.53 9.80 0.85 0.77 5.85 0.79 0.49

47257 1.83 2.32 2.34 2.65 3.43 0.70 2.57 3.22

47331 4.23 7.21 8.84 1.45 1.29 4.76 1.41 1.39

47425 4.23 7.76 10.22 1.33 1.05 3.92 0.89 0.57

47481 0.14 0.04 — 6.99 10.69 0.09 6.63 10.20

(cont’d)

202



47525 3.81 7.12 9.36 1.62 1.27 2.28 — —

47543 3.97 6.35 7.42 2.40 2.89 2.62 2.32 2.81

47711 3.56 5.48 6.32 1.00 0.61 2.39 1.02 1.00

47811 3.65 5.80 6.71 2.23 2.64 2.34 2.25 2.68

47944 3.93 6.42 7.58 2.43 2.36 2.68 1.77 1.30

47972 2.60 3.51 3.69 2.55 3.30 1.06 2.48 3.10

48056 3.79 5.70 6.35 1.92 2.40 2.04 1.82 1.80

48062 2.10 2.91 2.95 6.51 10.43 0.89 6.29 10.22

48133 5.08 8.37 10.07 1.30 1.06 4.40 0.50 —

48149 3.47 5.24 5.80 2.66 3.25 1.37 2.53 3.15

48255 4.68 7.95 9.66 0.23 — 3.26 — —

48592 3.89 5.98 6.80 2.71 3.32 1.82 2.67 3.27

48658 4.60 8.14 10.89 0.41 — 4.66 — —

48866 4.22 6.91 8.17 2.12 2.37 4.03 1.95 2.19

48925 3.47 5.23 5.86 2.05 2.50 2.02 1.79 1.93

49082 6.04 10.56 14.09 4.72 4.85 1.90 0.41 0.16

(cont’d)

203



49226 4.22 7.21 8.92 1.62 1.59 4.32 1.62 1.71

49245 0.78 2.22 5.78 — — 2.89 — —

49301 3.63 5.65 6.51 1.89 2.09 2.49 2.01 2.32

49482 3.12 6.97 9.76 2.48 3.19 0.38 — —

49487 4.31 7.71 10.24 0.41 — 5.40 — —

49497 6.40 9.17 8.38 — — 1.05 — —

49611 4.62 7.54 8.98 1.60 1.67 2.39 — —

49618 4.00 6.54 7.79 1.65 1.66 2.90 1.78 1.94

49624 4.38 7.64 9.99 0.30 — 4.72 0.19 —

49627 4.32 8.02 11.24 0.20 — 4.15 — —

49726 5.03 7.93 9.11 1.93 3.42 1.79 — —

49821 2.63 3.71 3.95 2.61 3.13 3.78 2.44 3.16

49872 3.86 6.24 7.25 1.69 1.71 2.84 1.91 2.09

49949 4.09 6.90 8.40 2.13 2.26 3.36 2.16 2.48

50185 3.86 6.09 7.03 2.32 2.68 2.60 2.30 2.86

50190 4.13 7.01 8.59 1.86 1.82 3.71 1.86 2.08

(cont’d)

204



50215 3.99 6.66 9.47 2.16 4.10 1.67 — —

50257 4.25 7.21 8.80 1.15 0.97 3.89 0.98 0.86

50270 3.53 5.35 5.96 2.49 3.00 1.79 2.49 3.21

50339 3.97 6.38 7.55 — — 3.39 0.79 0.66

50474 4.11 7.08 8.71 1.30 1.15 4.58 1.36 1.55

50556 4.05 7.64 10.74 0.70 — 4.72 — —

50759 5.19 9.34 11.70 2.16 2.60 1.99 — —

50869 3.63 6.97 9.51 0.65 — 3.49 — —

50911 3.17 4.65 5.06 2.11 2.51 1.35 2.16 2.57

50937 2.78 6.21 10.69 — — 3.70 — —

51088 3.45 5.35 6.88 2.31 1.83 1.85 — —

51824 4.16 7.28 9.29 1.29 0.76 5.00 1.15 0.98

51856 3.81 6.15 7.19 2.33 2.56 2.09 2.34 2.91

52089 4.23 7.36 10.63 1.31 1.05 3.65 — —

52398 4.38 7.80 10.36 0.49 0.03 4.31 0.17 —

52456 3.92 6.76 8.30 1.26 0.90 4.50 1.49 1.45

(cont’d)

205



52639 4.16 7.45 9.25 0.29 — 5.00 0.45 0.10

52666 3.90 7.23 9.23 0.08 — 2.71 — —

52816 4.28 7.46 9.70 0.14 — 2.13 — —

52894 3.21 6.15 8.23 1.49 0.25 1.91 — —

53274 4.40 8.04 10.75 0.49 — 4.44 — —

53480 3.59 5.56 6.34 1.91 2.06 2.00 1.94 2.19

53707 4.06 6.68 7.96 1.53 1.51 3.71 1.49 1.53

53781 4.17 7.32 9.18 1.08 0.62 4.80 1.10 0.95

53801 4.10 6.84 8.17 2.04 2.20 3.66 1.94 2.25

53823 4.16 7.53 9.90 0.65 0.10 5.17 0.44 —

54027 4.46 7.81 9.99 0.76 0.15 3.87 0.64 0.17

54088 3.82 7.07 9.56 — — 4.81 — —

54168 2.82 3.89 4.26 2.78 3.54 1.11 2.56 3.29

54184 4.40 7.41 9.09 0.78 0.32 3.05 — —

54620 4.06 8.76 11.39 0.04 — 1.94 — —

54730 4.24 7.02 8.42 0.83 0.45 3.96 0.84 0.55

(cont’d)

206



55603 2.44 3.33 3.43 2.68 3.35 0.83 2.73 3.51

55732 4.38 7.81 9.86 0.78 0.00 4.33 0.75 0.38

55733 3.89 6.32 7.29 1.79 1.86 2.39 1.83 1.99

55942 4.54 8.16 11.01 0.36 — 4.19 — —

56002 3.94 6.53 7.70 0.33 0.06 3.82 0.13 —

56290 2.06 2.84 3.00 2.47 2.91 0.98 2.37 2.87

56534 4.22 6.84 7.99 0.68 0.20 3.82 0.95 0.67

56774 3.41 5.22 5.81 1.84 2.09 2.09 1.91 2.22

56818 4.43 7.79 9.89 0.84 0.36 4.29 0.14 —

56855 4.09 6.55 7.71 1.56 1.34 2.89 1.56 1.70

57038 4.29 7.76 9.75 0.66 — 4.09 0.25 —

57452 4.21 7.50 10.01 0.22 — 5.50 — —

57564 3.05 4.38 4.75 2.84 3.63 1.20 2.75 3.60

57631 4.49 8.07 10.64 0.51 — 4.52 — —

57647 — — —- 0.44 — 4.38 0.21 —

57741 4.43 7.32 9.79 0.87 0.40 4.81 0.03 0.49

(cont’d)

207



57781 4.21 7.34 9.33 1.15 0.78 4.89 1.12 0.92

57856 4.34 7.45 9.13 1.04 0.65 4.23 1.06 0.67

58071 2.88 3.96 4.25 3.27 4.39 1.04 2.98 3.92

208

NLTT ID [Fe/H]K [Fe/H]R [C/Fe]R [Fe/H]F Method

(dex) (dex) (dex) (dex)

57 −1.58 −1.59 −0.45 −1.58 K

341 −0.67 −1 −0.35 −0.67 K

812 −1.03 −1.18 −0.39 −1.03 K

1059 −0.67 −1.3 −0.43 −0.67 K

1231 −1.07 −1.35 −0.44 −1.07 K

1635 −0.13 −0.73 −0.39 −0.13 K

1645 −2.16 −2.12 −1.05 −2.12 K

1870 −0.82 −0.67 −0.32 −0.82 K

2045 −1.83 −1.84 −0.13 −1.83 K

2205 −1.43 −1.51 −0.52 −1.43 K

2404 −2.87 −2.66 2.42 −2.66 R

2427 −0.99 −1.11 −0.36 −0.99 K

2856 −2.92 −2.37 0.73 −2.37 R

2868 −1.33 −0.74 −0.31 −1.33 K

3516 −0.22 −0.9 −0.45 −0.22 K

3531 −1.49 −0.94 −0.07 −1.49 K

(cont’d)Table 3.5. Derived metallicities

209




3985 −0.94 −1.34 −0.29 −0.94 K

4517 −1.61 −1.84 −0.55 −1.61 K

4817 −1.15 −1.2 −0.52 −1.15 K

5052 −1.83 −2.05 −0.48 −1.83 K

5193 0.1 −0.91 −0.35 −0.35 K

5222 −2.44 −2.85 0.46 −2.44 K

5255 −0.84 −0.72 −0.45 −0.84 K

5506 — −1.66 −0.23 −1.66 R

5711 −0.67 −0.93 −0.29 −0.67 K

5881 — −1.31 −0.47 −1.31 R

6415 −1.38 −1.61 −0.44 −1.38 K

6774 −0.99 −0.85 −0.31 −0.99 K

7299 −1.45 −1.9 −0.31 −1.45 K

7415 −0.65 −0.84 −0.28 −0.65 K

7417 −1 −1.05 −0.27 −1 K

7966 −1.44 −1.2 −0.27 −1.44 K

(cont’d)

210




7968 −1.78 −1.84 −0.05 −1.84 R

8034 −1.84 −2.01 −0.27 −1.84 K

8227 −1.58 −1.93 −0.41 −1.58 K

8230 −0.8 −1.37 −0.53 −0.8 K

8459 −0.65 −0.7 −0.34 −0.65 K

8720 −0.64 −0.88 −0.29 −0.64 K

8783 −2.65 −2.68 0.86 −2.68 R

8833 — −2.42 0.43 −2.42 R

9026 −1.66 −1.43 −0.22 −1.66 K

9382 −0.28 −0.35 −0.13 −0.28 K

9437 −1.02 −1.88 −0.27 −1.02 K

9578 −1.15 −1.54 −0.23 −1.15 K

9597 −2.06 −2.25 −0.11 −2.25 R

9628 −1.51 −1.55 −0.61 −1.51 K

10536 −2.3 −2.67 0.2 −2.3 K

10821 −1.2 −1.93 −0.75 −1.2 K

(cont’d)

211




11007 −1.36 −1.45 −0.58 −1.36 K

11486 −1.39 — −0.07 −1.39 K

11515 −0.46 −0.7 −0.32 −0.46 K

11584 −0.66 −0.78 −0.37 −0.66 K

11795 −1.48 −1.71 −0.16 −1.48 K

12017 −0.99 −1.13 −0.2 −0.99 K

12103 −0.65 −0.55 −0.2 −0.65 K

12350 −1.01 −1.81 −0.48 −1.01 K

12845 −0.61 −0.83 −0.37 −0.61 K

12856 −0.95 −1.16 −0.58 −0.95 K

12986 −1.07 −1.19 −0.5 −1.07 K

13344 −0.81 −0.96 −0.43 −0.81 K

13470 −1.29 −1.48 −0.35 −1.29 K

13660 −0.79 −1.14 −0.48 −0.79 K

13770 −0.36 −1 −0.37 −0.36 K

13811 −1.83 −1.78 −0.08 −1.83 K

(cont’d)

212




13899 −1.36 −1.68 −0.35 −1.36 K

14091 −2.12 −1.85 −0.42 −2.12 K

14131 −1.33 −1.11 −0.33 −1.33 K

14169 −2.05 −1.67 −0.23 −2.05 K

14197 −1.03 −1.48 −0.4 −1.03 K

14391 −0.66 −1.23 −0.37 −0.66 K

14606 −0.55 −0.72 −0.28 −0.55 K

14658 −1.06 −1.33 0.26 −1.33 R

14805 −1.66 −2.28 −0.02 −1.66 K

14822 −0.79 −1.38 −0.31 −0.79 K

15161 −0.84 −1.17 −0.42 −0.84 K

15183 −0.73 −1.1 −0.37 −0.73 K

15218 −1.1 −1.02 −0.22 −1.1 K

15529 −1.03 −1.28 −0.26 −1.03 K

15881 −1.61 −1.88 −0.32 −1.61 K

15973 −0.85 −0.95 −0.38 −0.85 K

(cont’d)

213




15974 −2.04 −2.33 −0.5 −2.04 K

16030 −1.71 −1.86 −0.49 −1.71 K

16242 −0.88 −0.79 −0.19 −0.88 K

16250 −0.3 −0.82 −0.28 −0.3 K

16320 −0.97 −0.93 −0.11 −0.97 K

16444 −0.74 −1.2 −0.54 −0.74 K

16579 −0.48 −0.66 −0.36 −0.48 K

16869 −0.61 −0.93 −0.4 −0.61 K

17039 −1 −0.93 −0.3 −1 K

17136 −0.92 −1.3 −0.4 −0.92 K

17234 −0.65 −0.69 −0.2 −0.65 K

17485 −2.04 −2.69 0.19 −2.04 K

17738 −0.99 −0.92 −0.18 −0.99 K

17786 −1.45 −1.54 −0.41 −1.45 K

17872 −1.66 −1.51 −0.38 −1.66 K

18019 −1.2 −1.24 −0.36 −1.2 K

(cont’d)

214




18424 −0.81 −0.61 −0.25 −0.81 K

19550 −2.4 −2.69 1.57 −2.69 R

20691 −1.96 −2.06 −0.19 −1.96 K

20792 −1.23 −1.31 −0.37 −1.23 K

20980 −2.61 −2.37 0.37 −2.61 K

21084 −0.68 −1.04 −0.29 −0.68 K

21744 −1.8 −1.46 −0.29 −1.8 K

22026 −0.65 −0.88 −0.33 −0.65 K

22302 −1.8 −3.34 −0.24 −1.8 K

22520 −0.95 −1.5 −0.55 −0.95 K

22752 −0.76 −0.89 −0.3 −0.76 K

23192 −0.7 −1.09 −0.24 −0.7 K

24839 −0.79 −1.08 −0.38 −0.79 K

24984 −1.48 −1.82 −0.45 −1.48 K

25177 −1.38 −1.64 −0.45 −1.38 K

25234 −1.18 −1.45 −0.28 −1.18 K

(cont’d)

215




25521 −0.76 −0.81 −0.53 −0.76 K

26482 −0.75 −1.23 −0.48 −0.75 K

26650 −2.45 −2.66 0.68 −2.45 K

27436 −0.83 −1.44 −0.43 −0.83 K

27831 −0.44 −0.67 −0.24 −0.44 K

28199 −0.88 −1.18 −0.3 −0.88 K

28459 −0.69 −0.95 −0.23 −0.69 K

28955 −2.19 −2.22 −0.17 −2.19 K

29023 −1.29 −1.43 −0.56 −1.29 K

29551 −1.26 −1.65 −0.34 −1.26 K

29905 −0.67 −0.92 −0.46 −0.67 K

29933 −1.29 −1.47 −0.33 −1.29 K

30274 −1.42 −2.22 −0.35 −1.42 K

30400 −0.24 −0.56 −0.31 −0.24 K

30462 −0.85 −1.03 −0.31 −0.85 K

31155 −1.33 −1.33 −0.34 −1.33 K

(cont’d)

216




31233 −0.83 −1.17 −0.37 −0.83 K

32316 −1.9 −1.78 −0.26 −1.9 K

32392 −0.5 −1.37 −0.46 −0.5 K

32648 −1.93 −1.58 −0.27 −1.93 K

33146 −1.34 −1.67 −0.32 −1.34 K

33371 −1.13 −1.38 −0.45 −1.13 K

33823 −0.88 −0.83 −0.15 −0.88 K

33971 −0.98 −1.01 −0.45 −0.98 K

34051 −1.35 −1.09 −0.46 −1.35 K

35068 −1.75 −1.47 −0.21 −1.75 K

35758 −0.84 −0.98 −0.29 −0.84 K

35890 −1.39 −1.5 −0.06 −1.39 K

36059 −3.03 −1.95 0.71 −3.03 K

36446 −1.18 −1.38 −0.39 −1.18 K

36520 −1.03 −1.41 −0.37 −1.03 K

36564 −1.18 −1.17 −0.39 −1.18 K

(cont’d)

217




37158 −0.17 −0.55 −0.47 −0.17 K

37658 −2.02 −1.96 −0.24 −2.02 K

37807 −2.1 −2.38 −0.07 −2.1 K

37960 −1.13 −1.1 −0.1 −1.65 R

38221 −1.65 −1.57 −0.27 −1.65 K

38311 −1.36 −1.24 −0.44 −1.36 K

38814 −1.76 −1.89 −0.22 −1.76 K

39076 −0.84 −1.1 −0.46 −0.84 K

39121 −0.79 −1.45 −0.38 −0.79 K

39319 −1.3 −1.41 −0.48 −1.3 K

39456 −0.94 −1.23 −0.34 −0.94 K

39457 −0.76 −1.37 −0.4 −0.76 K

39670 −1.88 −1.96 −0.08 −1.88 K

40003 −0.92 −1.17 −0.38 −0.92 K

40723 −2.32 −2.64 0.43 −2.32 K

41218 −0.14 −1.45 −0.72 −0.14 K

(cont’d)

218




41242 −0.53 −1.31 −0.67 −1.31 R

42183 −2.29 −2.61 −0.08 −2.29 K

42301 −0.28 −0.56 −0.29 −0.28 K

43100 −1.95 −2.09 −0.49 −1.95 K

43291 −2.07 −1.84 −0.12 −2.07 K

43444 −1.07 −1.82 −0.66 −1.07 K

43675 −0.79 −1.25 −0.47 −0.79 K

43887 −1.38 −1.57 −0.34 −1.38 K

43923 −0.75 −1.35 −0.54 −0.75 K

44039 −1.96 −2.34 −0.13 −1.96 K

44226 −1.66 −2.01 −0.28 −1.66 K

44568 −1.18 −1.33 −0.57 −1.18 K

44639 −0.65 −0.94 −0.33 −0.65 K

44683 −1.33 −0.9 −0.17 −0.9 R

44749 −0.97 −1.73 −0.27 −0.97 K

45026 −1.06 −0.98 −0.27 −1.06 K

(cont’d)

219




45609 −0.66 −1.48 −0.51 −0.66 K

45616 −1.36 −1.37 −0.44 −1.36 K

45754 −1.94 −2.6 −0.45 −1.94 K

46039 −0.65 −0.75 −0.46 −0.65 K

46215 −1.07 −1.71 −0.36 −1.07 K

47073 −2.19 −1.83 −0.53 −1.83 R

47132 −0.88 −0.85 −0.3 −0.88 K

47242 −0.96 −1.08 −0.14 −0.96 K

47257 −2.54 −2.5 0.5 −2.54 K

47331 −0.64 −1.05 −0.17 −0.64 K

47425 −0.88 −0.99 −0.55 −0.88 K

47543 −0.98 −1.12 −0.43 −0.98 K

47711 −2.1 −2.01 −0.27 −2.1 K

47811 −1.33 −0.9 −0.38 −1.33 K

47944 −2.28 −1.41 −0.44 −1.41 R

48056 −1.92 −1.62 −0.42 −1.92 K

(cont’d)

220




48133 −0.85 −1.18 −0.43 −0.85 K

48149 −1.94 −1.7 −0.63 −1.94 K

48255 −1.76 −1.83 −0.63 −1.76 K

48592 — −0.83 −0.62 −0.83 R

48658 −0.65 −1.55 −0.5 −0.65 K

48866 −0.55 −0.77 −0.2 −0.55 K

48925 −1.71 −1.71 −0.31 −1.71 K

49226 −0.36 −0.88 −0.27 −0.36 K

49301 −1.33 −1.46 −0.28 −1.33 K

49487 −0.82 −1.17 −0.28 −0.82 K

49618 −1.19 −1.03 −0.42 −1.19 K

49624 −0.94 −1.15 −0.36 −0.94 K

49627 −0.45 −1.24 −0.65 −0.45 K

49821 −2.04 −2.3 0.91 −2.3 R

49872 −1.15 −1.32 −0.32 −1.15 K

49949 −0.24 −0.62 −0.4 −0.24 K

(cont’d)

221




50185 −1.11 −1.31 −0.36 −1.11 K

50190 −0.34 −0.9 −0.35 −0.34 K

50257 −0.7 −0.9 −0.34 −0.7 K

50270 −1.45 −1.37 −0.43 −1.45 K

50339 −1.77 −1.47 −0.23 −1.47 R

50474 −0.44 −0.81 −0.18 −0.44 K

50556 −0.67 −1.36 −0.47 −0.67 K

50759 −0.92 −1.16 −1.34 −1.16 R

50869 0.41 −1.56 −0.55 −1.56 R

50911 −1.76 −1.92 −0.31 −1.76 K

51824 −0.3 −0.72 −0.2 −0.3 K

51856 −0.9 −1.17 −0.58 −0.9 K

52089 −0.85 −1.84 −0.68 −0.85 K

52398 −0.66 −1 −0.49 −0.66 K

52456 −1.03 −0.96 −0.13 −1.03 K

52639 −1.05 −1.22 −0.19 −1.05 K

(cont’d)

222




52666 −2.16 −1.75 −0.72 −1.75 R

52894 −2.52 −2.05 −0.86 −2.05 R

53274 −0.81 −1.1 −0.52 −0.81 K

53480 −1.69 −1.53 −0.43 −1.69 K

53707 −1.19 −1.03 −0.23 −1.19 K

53781 −0.67 −0.79 −0.22 −0.67 K

53801 −0.84 −0.96 −0.28 −0.84 K

53823 −0.92 −1.11 −0.27 −0.92 K

54027 −0.46 −0.88 −0.53 −0.46 K

54088 −1.4 −1.6 −0.28 −1.6 R

54184 −1.77 −1.79 −0.6 −1.77 K

54730 −1.18 −1.07 −0.26 −1.18 K

55603 −1.78 −2.4 −0.24 −1.78 K

55732 −0.83 −1 −0.42 −0.83 K

55733 −1.15 −1.37 −0.48 −1.15 K

55942 −0.34 −1.18 −0.61 −0.34 K

(cont’d)

223




56002 −2.17 −1.92 −0.16 −2.17 K

56290 −2.12 −2.41 0.14 −2.12 K

56534 −1.77 −1.43 −0.21 −1.77 K

56774 −1.58 −1.25 −0.26 −1.58 K

56818 −0.96 −1.47 −0.43 −0.96 K

56855 −1.18 −1.19 −0.4 −1.18 K

57038 −0.83 −1.16 −0.45 −0.83 K

57452 −0.89 −1.07 −0.23 −0.89 K

57564 −1.84 −2.11 −0.33 −1.84 K

57631 −0.71 −0.99 −0.49 −0.71 K

57741 −0.85 −1.1 −0.31 −0.85 K

57781 −0.48 −1 −0.23 −0.48 K

57856 −0.5 −0.92 −0.32 −0.5 K

58071 −1.84 −1.98 −0.3 −1.84 K

224

Line Line Band Sideband 1 Sideband 2

(A) (A) (A)

CaH 1 6380.0 - 6390.0 6345.0 - 6355.0 6410.0 - 6420.0

CaH 2 6814.0 - 6846.0 7042.0 - 7046.0

CaH 3 6960.0 - 6990.0 7042.0 - 7046.0

TiO 5 7126.0 - 7135.0 7042.0 - 7046.0

Table 3.6. Line indices from Gizis (1997)

225

Star V0 (B − V )0 (J − K)0 CaH1 CaH2 CaH3 TiO5

NLTT 1645 14.67 1.35 0.73 0.94 0.84 0.91 0.94

NLTT 2856 14.62 1.27 0.58 1.00 1.04 0.96 0.93

NLTT 11462 12.95 1.74 0.79 0.72 0.51 0.72 0.68

NLTT 25218 12.70 1.44 0.77 0.87 0.69 0.85 0.76

NLTT 40313 13.61 1.32 0.73 0.95 0.89 0.97 0.97

NLTT 45011 13.38 1.27 0.73 0.94 0.91 0.97 0.95

NLTT 45367 13.71 1.38 0.77 0.82 1.01 1.00 0.99

NLTT 47525 14.27 1.35 0.75 0.94 0.92 0.96 0.96

NLTT 49082 15.98 1.41 0.71 0.82 0.53 0.79 0.58

NLTT 49245 15.34 1.41 0.72 0.91 0.86 0.91 0.94

NLTT 49482 14.79 1.45 0.71 0.81 0.69 0.85 0.83

NLTT 49497 15.79 1.38 0.71 0.92 0.85 0.96 0.95

NLTT 49611 14.57 1.35 0.70 0.94 0.90 0.94 0.94

NLTT 49726 15.74 1.31 0.73 0.95 0.92 0.98 1.00

NLTT 50215 14.57 1.44 0.69 0.85 0.80 0.91 0.95

NLTT 50759 15.67 1.39 0.66 0.97 0.92 0.96 1.03

(cont’d)Table 3.7. Gizis (1997) Indices measured for stars with (B − V )0 >1.2

226


Star V0 (B − V )0 (J − K)0 CaH1 CaH2 CaH3 TiO5

NLTT 51088 15.07 1.37 0.64 — 0.92 0.95 0.97

NLTT 52816 15.63 1.21 0.68 0.97 0.98 0.97 0.91

NLTT 54620 15.07 1.42 0.73 0.88 0.80 0.86 0.92

227

NLTT ID (B − V )0 (J − K)0 D Teff

(mag) (mag) (pc) (K)

57 0.42 0.251 328 6356

341 0.53 0.394 298 5922

812 0.56 0.426 365 5811

1059 0.84 0.624 218 4941

1231 0.45 0.343 336 6232

1635 0.62 0.416 455 5598

1645 1.35 0.726 271 4500

1870 0.68 0.408 347 5403

2045 0.86 0.614 152 4890

2205 1.12 0.644 187 4501

2404 0.41 0.308 307 6398

2427 0.73 0.509 242 5247

2856 1.27 0.58 265 4176

2868 1.09 0.454 160 4514

3516 0.45 0.36 650 6232

3531 0.95 0.458 170 4680

(cont’d)Table 3.8. De-reddened color indices, distance estimates, and effective temperatures

228




3847 1.52 0.656 12 4048

3985 0.76 0.594 333 5159

4517 1.08 0.7 188 4500

4817 0.46 0.324 236 6191

5052 0.9 0.673 210 4794

5193 0.57 0.459 140 5774

5222 0.4 0.354 705 6436

5255 0.52 0.297 292 5957

5404 0.62 0.377 333 5598

5506 0.04 0.388 199 8197

5711 0.63 0.443 235 5564

5881 0.18 0.279 191 7458

6415 0.43 0.337 369 6314

6774 0.73 0.456 166 5247

7299 0.4 0.3 282 6436

7415 0.56 0.37 67 5811

(cont’d)

229




7417 0.51 0.364 62 5995

7966 0.83 0.486 181 4967

7968 0.96 0.635 196 4658

8034 0.41 0.294 284 6398

8227 0.41 0.322 169 6398

8230 0.75 0.661 303 5188

8459 0.55 0.337 322 5848

8720 0.6 0.4 419 5668

8783 0.46 0.316 176 6191

8833 0.06 0.258 183 8090

9026 0.63 0.463 324 5564

9382 0.53 0.282 291 5922

9437 0.35 0.254 911 6653

9578 0.51 0.457 135 5995

9597 0.39 0.25 293 6479

9628 0.49 0.372 429 6072

(cont’d)

230




10536 0.38 0.316 215 6522

10821 0.99 0.727 149 4595

10850 0.09 0.131 433 7926

11007 0.46 0.346 327 6191

11462 1.74 0.791 123 —

11486 0.82 0.917 76 4994

11515 0.67 0.42 280 5435

11584 0.7 0.44 303 5339

11795 0.41 0.301 456 6398

12017 0.77 0.527 121 5132

12103 0.55 0.307 191 5848

12350 0.37 0.303 451 6565

12845 0.66 0.451 98 5467

12856 0.44 0.298 212 6273

12986 0.44 0.286 290 6273

13344 0.73 0.508 309 5247

(cont’d)

231




13470 1.1 0.655 176 4501

13641 1.14 0.742 110 4532

13660 0.84 0.577 100 4941

13770 0.57 0.431 310 5774

13811 0.54 0.402 392 5885

13899 0.47 0.392 285 6151

14091 0.95 0.598 158 4680

14131 0.7 0.46 237 5339

14169 0.64 0.425 216 5531

14197 0.82 0.61 101 4994

14391 0.71 0.586 288 5308

14606 0.49 0.32 454 6072

14658 0.42 0.293 307 6356

14805 0.36 0.29 292 6609

14822 0.84 0.626 119 4941

15161 0.52 0.401 173 5957

(cont’d)

232




15183 0.82 0.564 124 4994

15218 0.63 0.416 174 5564

15529 0.55 0.454 327 5848

15788 0.33 0.26 334 6743

15881 1.09 0.707 174 4515

15939 0.33 0.225 679 6743

15973 0.57 0.393 77 5774

15974 1 0.72 173 4575

16030 1 0.665 167 4575

16242 0.65 0.404 91 5500

16250 0.6 0.421 427 5668

16320 0.79 0.462 58 5076

16444 0.93 0.581 120 4724

16573 1.13 0.771 116 4504

16579 0.63 0.38 242 5564

16869 0.67 0.473 294 5435

(cont’d)

233




17039 0.51 0.336 381 5995

17136 0.78 0.573 241 5104

17234 0.55 0.337 68 5848

17485 0.42 0.396 271 6356

17738 0.74 0.467 56 5217

17786 0.46 0.337 291 6191

17872 0.43 0.256 173 6314

18019 0.73 0.519 204 5247

18424 0.76 0.417 164 5159

19550 0.5 0.382 138 6033

20232 0.28 0.181 200 6969

20691 0.46 0.352 102 6191

20792 0.49 0.363 115 6072

20980 0.43 0.239 275 6314

21084 0.52 0.397 277 5957

21744 0.58 0.404 182 5739

(cont’d)

234




22026 0.56 0.394 336 5811

22302 0.46 0.709 1041 9249

22520 0.45 0.397 210 6232

22752 0.79 0.503 251 5076

23192 0.61 0.45 477 5633

24839 0.71 0.536 201 5308

24984 0.4 0.326 433 6436

25177 0.45 0.347 350 6232

25218 1.44 0.771 109 4500

25234 1.03 0.635 136 4507

25521 0.79 0.526 269 5076

26482 0.89 0.588 105 4818

26650 0.32 0.308 465 6788

27436 0.95 0.644 126 4680

27831 0.54 0.338 258 5885

28199 0.79 0.566 185 5076

(cont’d)

235




28459 0.66 0.461 321 5467

28955 0.46 0.298 340 6191

29023 0.43 0.321 555 6314

29551 0.37 0.222 327 6565

29905 0.64 0.427 212 5531

29933 0.45 0.322 140 6232

30274 0.33 0.279 619 6743

30400 0.64 0.386 467 5531

30462 0.81 0.53 142 5021

31155 0.5 0.338 548 6033

31233 0.72 0.537 323 5278

31272 0.63 0.741 512 5564

32316 0.49 0.318 184 6072

32392 0.93 0.66 274 4724

32648 0.7 0.489 161 5339

33146 0.38 0.266 528 6522

(cont’d)

236




33221 0.87 0.539 136 4865

33371 0.89 0.583 115 4818

33823 0.71 0.439 147 5308

33971 0.49 0.332 431 6072

34051 0.73 0.457 218 5247

34628 0.83 0.63 77 4967

35068 0.53 0.352 364 5922

35758 0.53 0.377 542 5922

35890 0.52 0.4 376 5957

36059 0.34 0.221 271 6698

36446 0.53 0.441 152 5922

36520 0.47 0.396 312 6151

36564 0.62 0.442 358 5598

37158 0.59 0.359 808 5703

37658 0.68 0.566 377 5403

37807 0.44 0.336 306 6273

(cont’d)

237




37960 0.88 0.516 129 4840

38221 0.52 0.361 189 5957

38311 0.47 0.295 471 6151

38779 1.52 0.639 245 4500

38814 0.43 0.332 432 6314

39076 0.51 0.381 931 5995

39121 0.77 0.655 145 5132

39319 0.83 0.563 298 9249

39456 0.76 0.558 29 5159

39457 0.78 0.621 30 5104

39670 0.46 0.35 215 6191

40003 0.79 0.54 187 5076

40313 1.32 0.725 166 4501

40723 0.37 0.31 556 6565

41218 0.96 0.723 288 4658

41242 0.98 0.649 201 4616

(cont’d)

238




42183 0.46 0.358 371 6191

42301 0.54 0.321 444 5885

42743 1.36 0.74 151 4501

43100 1.16 0.743 127 4507

43291 0.75 0.534 108 5188

43444 1.01 0.719 278 4541

43675 0.84 0.601 198 4941

43887 0.87 0.595 193 4865

43923 0.89 0.623 142 4818

44039 0.39 0.284 239 6479

44226 0.43 0.383 149 6314

44568 0.44 0.312 372 6273

44639 0.56 0.407 225 5811

44683 0.72 0.415 102 5278

44749 1.02 0.712 236 4505

45011 1.27 0.728 150 4501

(cont’d)

239




45026 0.7 0.453 119 5339

45367 1.38 0.766 175 4500

45609 0.93 0.673 104 4724

45616 0.46 0.323 273 6191

45754 0.63 0.693 355 5564

46039 0.56 0.362 188 5811

46215 1 0.698 149 4575

46730 -0.02 0.097 914 8540

46738 0.08 0.082 1553 7980

47073 0.63 0.39 253 5564

47132 0.78 0.49 156 5104

47242 0.87 0.517 121 4865

47257 0.42 0.269 198 6356

47331 0.58 0.443 124 5739

47425 0.79 0.524 383 5076

47481 0.18 0.076 328 7458

(cont’d)

240




47525 1.35 0.748 226 4502

47543 0.49 0.357 84 6072

47711 0.63 0.492 273 5564

47811 0.49 0.25 507 6072

47944 0.91 0.442 175 4770

47972 0.63 0.417 164 5564

48056 0.58 0.398 324 5739

48062 0.83 0.563 96 4967

48133 0.82 0.561 361 4994

48149 0.55 0.374 210 5848

48255 1.14 0.695 250 4502

48592 0.27 0.239 492 7016

48658 1.01 0.706 227 4517

48866 0.49 0.328 440 6072

48925 0.52 0.382 471 5957

49082 1.41 0.71 618 4503

(cont’d)

241




49226 0.57 0.407 180 5774

49245 1.41 0.722 368 4076

49301 0.49 0.371 322 6072

49482 1.45 0.714 287 4503

49487 0.86 0.57 98 4890

49497 1.38 0.713 454 4500

49611 1.35 0.697 259 4502

49618 0.55 0.365 285 5848

49624 0.76 0.549 357 5159

49627 0.99 0.654 237 4595

49726 1.31 0.729 444 4502

49821 0.45 0.348 418 6232

49872 0.52 0.394 263 5957

49949 0.46 0.306 605 6191

50185 0.48 0.374 136 6112

50190 0.5 0.39 342 6033

(cont’d)

242




50215 1.44 0.693 259 4500

50257 0.61 0.403 459 5633

50270 0.45 0.305 249 6232

50339 0.63 0.454 424 5564

50474 0.54 0.375 454 5885

50556 0.95 0.651 425 4680

50759 1.39 0.662 451 4500

50869 0.4 0.617 109 6436

50911 0.43 0.332 243 6314

50937 0.74 0.695 571 9249

51088 1.37 0.64 325 4097

51824 0.62 0.395 222 5598

51856 0.46 0.352 575 6191

52089 1.04 0.763 289 4505

52398 0.72 0.535 501 5278

52456 0.59 0.383 252 5703

(cont’d)

243




52639 0.73 0.516 198 5247

52666 1.18 0.645 309 4507

52816 1.21 0.68 422 4500

52894 1.2 0.648 462 4507

53274 0.73 0.586 170 5247

53480 0.55 0.375 260 5848

53707 0.56 0.377 252 5811

53781 0.63 0.404 434 5564

53801 0.54 0.373 234 5885

53823 0.78 0.533 225 5104

54027 0.66 0.483 351 5467

54088 1.02 0.631 202 4541

54168 0.23 0.331 655 7209

54184 1.04 0.646 186 4505

54620 1.42 0.732 339 4503

54730 0.61 0.42 147 5633

(cont’d)

244




55603 0.39 0.34 345 6479

55732 0.72 0.504 270 5278

55733 0.51 0.411 751 5995

55942 0.95 0.624 163 4680

56002 0.87 0.576 219 4865

56290 0.41 0.304 378 6398

56534 0.65 0.478 183 5500

56774 0.48 0.262 399 6112

56818 0.83 0.62 218 4967

56855 0.53 0.397 636 5922

57038 0.7 0.536 351 5339

57452 0.88 0.529 170 4840

57564 0.44 0.356 148 6273

57631 0.8 0.553 216 5048

57647 0.83 0.566 396 4967

57741 0.73 0.524 357 5247

(cont’d)

245




57781 0.64 0.467 87 5531

57856 0.6 0.431 416 5668

58071 0.4 0.289 525 6436

246

Survey N [Fe/H] < −2.0 [Fe/H] < −2.5 [Fe/H] < −3.0

This sample 254 11% 2% 0.4%

HK survey 2614 11% 4% 1%

(no B − V )

HK survey 2140 32% 11% 3%

(with B − V )

HES survey 571 59% 21% 6%

(faint TO stars)

HES survey 643 50% 20% 6%

(faint giants)

Table 3.9. “Effective yield” of the present sample

247

Star V [Fe/H] [C/Fe]

(mag) (dex) (dex)

NLTT 2404 12.11 −2.66 2.42

NLTT 2856 14.78 −2.37 0.73

NLTT 8783 11.47 −2.68 0.86

NLTT 19550 11.10 −2.69 1.57

NLTT 49821 12.77 −2.3 0.91

Table 3.10. Carbon-enhanced metal-poor stars

248

Chapter 4

Mapping the Local Galactic Halo. III.

Kinematics of Halo Subdwarfs and a Search for

Moving Groups

4.1. Introduction

There has historically been two competing models for the formation of the

Galaxy: monolithic collapse (Eggen, Lynden-Bell, & Sandage 1962) and accretion

of mass by merging with satellites (Searle & Zinn 1978). Recently there has been

increasing evidence for the latter: one of the most popular results of the SDSS to

date is the discovery of the so-called “Field of Streams” (Belokurov et al. 2006), a

group of satellite galaxies, including the Sagittarius dwarf galaxy, thought to be in

the process of merging with the Galaxy. Further support for the merging scenario

comes from cosmological simulations of the behavior of extragalactic groups of

galaxies. It now seems that old elliptical galaxies were formed via “hierarchical

merging” in the distant Universe (Peebles 1970; ?), a process quite similar to the

merging of small satellites with the Milky Way proposed by Searle & Zinn (1978).

249

There is ample evidence to support the merging hypothesis. Distinct from

these galaxies that are in the process of merging with the Milky Way are smaller

associations of tens of stars that have similar space velocities. Known as “moving

groups”, these objects are thought to be the remnants of merged galaxies that have

been tidally disrupted, leaving only small groups of stars with common velocities.

There is a longer history of looking for these small groups of stars: Eggen (1977)

searches for comoving groups, while more recently Helmi et al. (1999) and Re

Fiorentin et al. (2005) have found several small groups of stars that share a common

galacticentric velocity.

Furthermore, several studies have recently discovered a group of stars whose

rotational velocity is different from the thin disk, thick disk, or halo (Gilmore, Wyse,

& Norris 2002; Wyse et al. 2006; Fuchs et al. 1998). These stars must either be

members of a fourth Galactic population or associated with a moving group of stars

or merger remnant that has not yet diffused into the thick disk. The latter scenario

may be difficult to explain; this population has been observed in many different

Galactic positions. Nonetheless, what exactly comprises this new population of stars

remains to be seen.

Chapter 2 describes the selection of a sample of candidate halo subdwarfs

from the high proper motion-catalog of the rNLTT (Salim & Gould 2003; Gould

& Salim 2003). Kinematically-selected samples have inherent selection effects that

prevent their use for studying the kinematic properties of the Galaxy as a whole

250

(see Norris 1986), and non-kinematically selected surveys such as the HK Survey

(Beers, Preston, & Shectman 1985, 1992) or the HES Survey (Wisotzki et al. 2000)

are much better suited to studying the characteristics of the Galaxy. Nonetheless,

kinematically-selected samples are useful for different types of studies, in particular

since they are largely unbiased in metallicity (unlike the HK and HES Surveys, see

Carney et al. 1996). These kinematically-selected surveys may also be very useful

in studying the kinematics of the local solar neighborhood. Kinematically-selected

samples are often used to study stars within ∼ 25 pc of the sun: nearby stars have

higher proper motions than more distant stars (see Reid & Cruz 2002; Lepine 2005).

Furthermore, it is difficult to find a merger remnant or moving group in the vicinity

of the sun using star counts from an all-sky survey; because such a group would be

moving through the solar neighborhood, and its members would then be located all

over the sky, these groups could only be discovered on the basis of their kinematics.

In this paper we will study the kinematics of the sample presented in Chapter 2,

using the results of the spectrophotometric observations presented in Chapter 3. In

Section 4.2 we derive three-dimensional space motions for the stars in the sample

with radial velocity information. We describe the velocity distribution of the sample

in Section 4.3. Section 4.4 describes the search for moving groups in the sample.

In Section 4.5 we discuss the possible discovery of a merger remnant in the solar

neighborhood. Finally, we discuss the fastest-moving stars in Section 4.6.3.

251

4.2. Calculation of Space Motions

Galactocentric space motions may be calculated using an object’s observed

proper motion, distance, and radial velocity. In Chapter 3 we report radial velocities

precise to ∼40 km s−1 and distance estimates based on main sequence fitting and

dereddened (B − V )0 colors for stars with available spectroscopy. In Chapter 3 we

show that the derived distances are less secure for (B − V )0 >1; we therefore limit

the sample in the present work to (B − V )0 <1. The sample is derived from the

rNLTT of Gould & Salim (2003); Salim & Gould (2003); hence all of the stars have

available proper motion measurements which are accurate to 0.0055 mas yr−1.

We derive three-dimensional space velocities for the 230 stars in the sample with

measured radial velocities and estimated distances. We use the method described

by Johnson & Soderblom (1987) to convert these quantities into Galactocentric

space velocities in the usual cylindrical coordinate system. In this work we use a

left-handed coordinate system in which U is in the direction of the Galactic center,

V is in the direction of solar rotation, and W is towards the north Galactic pole.

We correct the space motions thus derived for the solar motion using the

Dehnen & Binney (1998) values for the solar velocity with respect to the local

standard of rest (LSR) of U0 = −10.00±0.36, V0 = 5.25±0.62, and W0 = 7.17±0.38.

252

In Figure 4.1 we present plots of the (U, V, W ) velocity components for the

stars. We note that there are five significant outliers in this figure. These stars may

be moving very fast or they may have errors in the distance estimates, resulting in

overestimated velocities. Figure 4.2 presents the same (U, V, W ) velocity components

for all but the five fastest-moving stars.

Table 4.1 presents the kinematic information for the sample. Column 1

gives the NLTT identifier, Columns 2-3 give the proper motion (from the rNLTT,

see Gould & Salim (2003); Salim & Gould (2003)). Column 4 gives the distance

estimated as described in Chapter 3 and Column 5 gives the radial velocity. Columns

6-8 present the (U, V, W ) velocity components. We calculate the Galactic restframe

velocity, VRF = (U2 + (V + VLSR)2 + W 2)1/2. We assume the canonical value for the

rotation of the LSR about the center of the Galaxy of VLSR = 220 km s−1 and list

the resulting VRF in Column 9.

4.3. Velocity Distribution

We wish to investigate the velocity distribution of the sample, in particular to

compare the characteristics of the local halo and thick disk populations to those that

have been derived of the Galaxy as a whole (see Chiba & Beers 2000; Norris 1986;

Carney et al. 1996). We have described the sample selection criteria in Chapter 2;

the high proper-motion stars selected in this manner are likely to be members of the

253

halo. In fact, the isolation of a purely halo population was the original motivation

for this work.

Using the velocity information described above, we derive velocity information

for the sample of 230 stars. We find < U > = −53 km s−1, < V > = −290 km s−1,

and < W > = −29 km s−1. We also calculate velocity dispersions: σ(U) = 219 km

s−1, σ(V ) = 177 km s−1, and σ(W ) = 100 km s−1.

Figure 4.3 plots the (U, V, W ) space motions as a function of [Fe/H]. There

appears to be almost no trend with metallicity in any of the three components. This

result is strikingly different from that of Chiba & Beers (2000), i.e., our sample

must be kinematically different from that of the Chiba & Beers (2000) sample,

which presumably is representative of the Galaxy as a whole. This is not surprising

since the present sample is kinematically-selected, and these types of samples have

notoriously misrepresented the kinematics of the Galaxy (e.g., Eggen, Lynden-Bell,

& Sandage 1962; Norris 1986). However, in this work we do not attempt to derive

Galactic quantities, simply to investigate the nature of the solar neighborhood.

To quantify this impression, we reproduce here Table 1 of Chiba & Beers (2000),

for their stars with |Z| <1 kpc, in Table 4.2 of this work and include the same

quantities for the present sample. Again, we note that these values are strikingly

different between this work and Chiba & Beers (2000). In particular, the mean

velocity in the V direction is nearly constant, and nearly non-rotating, for every

254

metallicity bin in the present sample, while in the Chiba & Beers (2000) sample it

varies from nearly corotating with the LSR for metal-rich bins to nearly non-rotating

for the most metal-poor stars. The Chiba & Beers (2000) sample is thought to be

largely representative of the Galaxy as a whole, and therefore reprents the generally

accepted trend that the thin disk, thick disk, and halo are composed of increasing

metal-poor stars, and go from rotating at VLSR to nearly non-rotating. The present

sample, on the other hand, as this table shows, is composed mostly of halo stars.

There is no trend in velocity with metallicity. The velocity dispersions in all three

components are also consistent with a halo velocity dispersion.

We will discuss the metallicities of these stars in greater detail in Chapter 5.

However, based on the kinematics derived in this paper, we confirm that our sample

is composed almost entirely of halo objects.

4.4. A Search for Moving Groups

The dataset presented in this work is ideal for looking for moving groups of

stars near the Sun. The simplest way to find a moving group is by inspection of the

U, V, W plots: close associations that share similar velocity components in (U, V, W )

space are likely to be moving groups.

Helmi et al. (1999) uncover moving groups in a sample of halo stars. They

look for substructure in the Galaxy using the angular momentum of the stars in

255

the Chiba & Yoshii (1998) data. They discover two separate moving groups in the

data, composed of nine and three stars, respectively. Chiba & Beers (2000) confirm

these findings using their own data. Helmi et al. (1999) interpret their finding as

the remnant of an accreted satellite merger and further conclude that ∼10% of the

Galactic halo is composed of the dissolution of an accreted structure similar to the

Sagittarius dwarf galaxy. This merger must have occurred long ago and the stars in

the structure have largely been assimilated into the halo population; however, some

of the original structure remains and can be observed in the kinematics of the halo

today.

We look for similar moving groups in our data in (U, V, W ) space. If a group of

stars are comoving, they should have similar (U, V, W ) velocity components.

We find at least two such moving groups in our data. The stars NLTT

33146, NLTT 57647, and NLTT 53480 form a group of stars moving with

(U, V, W ) = (348 ± 27,−62 ± 12,−1 ± 5) km s−1, where the errors represent the

standard deviation of the three stars’ velocities. These stars have [Fe/H] of −1.34,

−1.84, and −1.69, respectively. Their metallicities are consistent to 1 σ (given the

0.3 dex errors in metallicity) with all three stars having the same metallicity, which

is expected if the stars came from a single small and homogenous disrupted body

such as a globular cluster.

256

A second moving group is composed of NLTT 8034, NLTT 8227, and NLTT

8783. These stars have (U, V, W ) = (289 ± 15,−19 ± 28,−110 ± 5) km s−1. This

group has [Fe/H] = −1.84, −1.58, and −2.68; these values are consistent within 2 σ

of having the same metallicity.

Figure 4.4 shows the (U, V, W ) diagrams of the two moving groups compared

to the rest of the sample. The small scatter in (U, V, W ) velocity components and in

[Fe/H] between the three stars in each group imply that each group is real. Neither

of these groups has such extraordinary velocities to indicate that they might be

extreme members of the halo or groups of external stars passing through the Galaxy.

Rather, these stars are most likely further evidence that the Galaxy was formed, at

least in part, by accretion of satellite groups of stars as proposed by Searle & Zinn

(1978). We plan to search for further members of each of these groups in future

observing programs to further strengthen this claim.

Some work has been done toward understanding the composition of the Galactic

halo in terms of streams and moving groups. Helmi & White (1999) find that, if

the Galactic halo were composed entirely of merged satellites, the local halo should

contain 300-500 streams with velocity dispersions <5 km s−1. Similarly, Gould

(2003) finds a lower limit of 400 such streams in the local halo. Each of these

streams contains between 0.25% and 5.0% of the local stars. Helmi et al. (1999)

find that of order 10% of the local halo are associated with the remains of a single

merger even. These results are consistent with the present findings: each group of

257

three stars represents 1.3% of the 230 stars searched. Since our sample is not strictly

volume-limited, it is difficult to say with certainty how many halo stars are contained

in moving groups. We find a lower limit of six stars, or 2.6% of the sample, and with

further investigation may find more.

In particular, we note that these two moving groups were discovered simply

by visual inspection of the (U, V, W ) plane. It will almost certainly be fruitful to

continue this search for moving groups in the sample in a more systematic way.

4.5. A Search for Merger Remnants

In Chapter 2 we discuss the anomalous look of the reduced proper motion

(RPM) diagram constructed with new, accurate and precise photometry for 635

stars in the sample. The RPM diagram appears to have a higher-density region of

points forming a sequence to the left of the metal-poor main sequence region of the

diagram. Figure 4.5 is a reproduction of this diagram from Chapter 2. As discussed

in Chapter 2, such a high density region is not expected and can be only due to

either coincidence or to the presence of a group of stars with similar properties

moving through the solar neighborhood. The latter is an attractive explanation,

especially since it is unlikely that a structure of this sort would have been found

previously: few studies with accurate photometry have been conducted that select

stars to be solely in the halo, as does the current study. These stars could be the

258

result of a recent merger between the Galaxy and a smaller satellite galaxy; one

would expect to find such structures in the halo if the Galaxy is at least in part

formed via the hierarchical merging scenario of Searle & Zinn (1978). We will refer

to the group of stars found in the RPM diagram as the “proposed merger remnant”

(or PMR) in the discussion that follows.

We selected the stars in the proposed merger remnant simply by producing a

contour map of the RPM diagram and selecting stars in the region with the highest

density. Figure 4.6 reproduces the RPM diagram with the selected stars emphasized

by using larger points. We note that although we selected all of the stars in this

region, if this is indeed a comoving merger remnant there will certainly be some

contamination by other stars lying in the same region of the RPM diagram with

different space motions. Nonetheless, we proceed with the following analysis using

all of the stars selected in this way. Metallicity and kinematic information exists for

71 stars in this region.

The kinematic information for these 71 stars are presented in Row 2 of

Table 4.3. The space motions of this group of stars are somewhat different from

those of the complete sample; in particular the mean V velocity component of the

merger remnant has an offset of ∼40 km s−1 from the mean V of the rest of the

sample. We find (see § 4.3 above) < V > = −290 km s−1 and σ(V ) = 177 km s−1

for the entire sample. The proposed merger remnant has a mean < V > = −329 km

s−1 and σ(V ) = 126 km s−1.

259

We note that the stars with the lowest reduced proper motion,

HV = V + 5logµ + 5, in the sample have a larger fraction of stars that are

in the proposed merger remnant. This may effect the distribution of the velocities of

the sample as compared to the proposed merger remnant. In an attempt to remove

this effect, we recalculate the mean velocity components for only those stars with

HV > 15. With these criteria imposed, we find 15 stars in the proposed merger

remnant. Figure 4.7 presents the space motions of these 15 stars selected to be part

of the proposed merger remnant, the stars selected from the RPM diagram, as well

as all of the stars in the sample. Row 3 of Table 4.3 presents the kinematics of this

subset of 15 stars. This restricted sample has an even lower mean of < V > = −398

km s−1. We find that imposing this HV criterion only strengthens the conclusion

that these stars are kinematically distinct from the rest of the sample, but that

removing these stars from the rest of the sample does not change the mean velocity

distribution of the remaining stars significantly.

We emphasize that the kinematics of these stars imply that they are not

members of the thick disk, nor are they members of any known association or merger

remnant.

If a group of stars of this sort is indeed the remnant of a small merged satellite,

one might expect the metallicities of the stars in the group to be similar. This is not

the case in the proposed merger remnant. Figure 4.8 shows the (U, V, W ) velocity

components for the 15 stars in the proposed merger remnant. The metallicity

260

distribution of the stars in the proposed merger remnant is similar to that of the

sample as a whole.

There is very little discussion of this sort of structure in the literature. Gilmore,

Wyse, & Norris (2002) and Wyse et al. (2006) find, by comparing their data with

models, an excess of stars with < V > +VLSR ∼100 km s−1 in several lines of sight.

Fuchs et al. (1998) also finds a similar structure in an analysis of the Carney et

al. (1996) data; they also find a subset of stars with < V > +VLSR ∼100 km s−1.

Gilmore, Wyse, & Norris (2002) and Wyse et al. (2006) conclude that these stars

comprise “satellite debris” in the thick disk or halo, associated with the remains of

the satellite merger that created the thick disk, and that this merging satellite was

the last significant Galactic merger. This expanation might also fit the stars in the

proposed merger remnant.

Whether or not these stars are members of the last major merger of the Galaxy,

they are certainly an interesting kinematic signature in the Galaxy. If the present

sample is indeed part of the same population as those discussed by Gilmore, Wyse,

& Norris (2002) and Wyse et al. (2006), members of this merged satellite have now

been found in several lines of sight in the distant halo (0.5–5 pc; Gilmore, Wyse,

& Norris 2002), as well as in the local halo. The implications for this discovery

are great; it may imply that a fourth component is needed to fully describe the

kinematics of the Galaxy.

261

It is still possible that these stars suffer from some sort of kinematic selection

effects due to the way in which the sample is composed. This possibility will be

investigated in greater detail.

4.6. Individual Stars of Interest

Several stars in this sample are kinematically distinct from the rest of the

sample. In particular, the sample includes eight stars with vrf >550 km s−1,

the canonical escape velocity of the Galaxy (Carney et al. 1988). While it is not

surprising to find many fast-moving stars in a kinematically-selected halo sample,

most of these stars are moving significantly faster than the escape velocity of the

Galaxy. Very few of these types of fast-moving stars, sometimes referred to as

high velocity stars (HVSs) are presently known; a recent survey for HVSs ejected

from interaction with the black hole at the center of the Galaxy has found only 5

candidates thus far (Brown et al. 2005, 2006).

We also note that previous, albeit non-kinematically-selected, samples such as

Chiba & Beers (2000) find only 0.5% of their sample to have VRF > 550 km s−1,

while we find 3% of this sample that meet this criterion. On the other hand we also

note, as did Chiba & Beers (2000), that some of these fast-moving stars may be

due to overestimated distances which result in overestimated tangential velocities.

262

Nonetheless, the presence of these high velocity stars may indicate that the Galactic

escape velocity is higher than previously thought.

Below we present the most likely HVS candidate in our sample and discuss two

pairs of very fast moving binaries. Finally, we discuss the remaining fast-moving

stars in the sample.

4.6.1. NLTT 9437, a Candidate HVS

NLTT 9437 is a very fast-moving star that is found to be at a very large

distance from the sun. We derive VRF = 780 km s−1± 205 km s−1 for NLTT 9437,

with a distance estimate of D = 911 pc. Using our secondary distance estimate (see

Chapter 3) provides D = 645 pc and VRF = 492 km s−1± 148 km s−1. In either case,

the star is moving very fast, either well above or nearly at the escape velocity of the

Galaxy.

Two distance estimates exist in the literature for this object. Beers et al. (2000)

find the distance to NLTT 9437 to be 680 pc, while Beers & Sommer-Larsen (1995)

find 900 pc. These estimates agree well with our two distance estimates. In any

case, this star is very far away and is moving very rapidly. In fact, if these distances

are correct, the star may be a bona-fide candidate HVS. A very high velocity for this

star would be interesting since the majority of its velocity is in the V component

(V +VLSR = −764 km s−1): since all known HVS stars are thought to be ejected

263

from interaction with the black hole at the Galactic Center, a different mechanism

would need to be devised to explain the trajectory of this fast-moving star.

4.6.2. NLTT 39456/7, a Fast-Moving Halo Binaries

We find one pair of binary star candidates (i.e., stars having common proper

motions) in the sample, NLTT 39456 and NLTT39457 This pair of objects is

extraordinary, not only because of its high velocity, but especially because it is a

binary moving at such a high speed. High velocity binaries should be extremely

rare: it is generally assumed that the mechanism for creating HVSs is gravitational

interaction with a massive star or ejection from the region near the black hole at

the center of the Galaxy. In either case, one might expect that a binary or other

association would be effected in such a way as that the pair would be separated from

each other. Hence, the existence of a fast-moving binary in the solar neighborhood

probably requires an alternative explanation for its formation.

NLTT 39456 and NLTT 39457 are a well established pair of stars. While not

meeting the HVS criterion of VRF > 550 km s−1, these are nonetheless interesting

objects. These stars are a well-known pair of stars moving with extreme velocity

through the solar neighborhood. We find VRF = 434 and 442 km s−1 for these stars;

other authors have found similar velocities. Carney et al. (1996) find distances of 28

and 27 pc and VRF = 404 and 400 km s−1 for these two stars, respectively.

264

4.6.3. Other Fast-Moving Stars

Additionally, we find five other stars with very high Galactic rest-frame

velocities. All of these stars appear to have an error in the distance estimate to the

star, resulting in an overestimate of the velocity. The distance to these stars depends

on the dereddened (B − V )0 color of each target, which is composed of the B − V

color (accurate to 0.02 mag, see Chapter 2), and the interstellar reddening we assume

towards each target (see Chapter 3). The error in the reddening is directly related

to the error in the distance, so an overestimate of the reddening by 0.2 mag results

in a 20% distance error. We expect this is the cause of the extraordinarily high

velocities in the five stars discussed below, especially since our velocities generally

do not agree well with previous measurements.

NLTT 3516

We derive a Galatocentric rest frame velocity for NLTT 3516 of VRF = 921 km

s−1± 220 km s−1. We note, however, that this extremely high velocity is largely due

to the high distance estimate of 650 pc. If we were to adopt the second method we

use as a check on the distance (294 pc, see Chapter 3 and Gould 2003), which is

perhaps more likely for a star in this sample, we find that the star is no longer an

HVS candidate and has VRF = 350 km s−1± 106 km s−1.

265

NLTT 3516 is in several previous studies of subdwarf stars. Carney et al. (1996)

reports a distance of 227 pc and a restframe velocity of VRF = 204 km s−1. Ryan &

Norris (1991) reports a distance of 253 pc and a restframe velocity of VRF = 247

km s−1. However, Ryan & Norris (1991) report a reddening value of E(B − V ) =

0.04, quite close to our value of E(B − V ) = 0.025. Clearly our distance estimate is

discrepant from previous estimates and suggests that this star does not have a very

high velocity after all.

NLTT 8230

We find VRF = 570 km s−1± 150 km s−1 for NLTT 8230. We again note that if

we adopt our secondary distance estimate for this star we find D = 123 and VRF =

242 km s−1± 71 km s−1.

This star is in the Yong & Lambert (2003) sample, which is drawn from the

rNLTT using a RPM diagram (as is the present sample). They find VRF = 268 km

s−1± 74 km s−1 for this star. Again, our distance estimate for this star may be

over-estimated.

NLTT 10850

We find that NLTT 10850 has VRF = 1327 km s−1± 313 km s−1. The distance

to this star, 433 pc, is within the expected range of the sample.

266

Carney et al. (1996) find a distance of 124 pc and VRF = 236 km s−1 for NLTT

10850. Sandage & Fouts (1987) find a distance of 109 pc, with VRF = 200 km s−1.

Here again we may have overestimated the distance to the target, inflating the

velocity estimate.

NLTT 15788

For NLTT 15788 we find VRF = 569 km s−1± 144 km s−1, using our distance

estimate of 334 pc. Ryan & Norris (1991) derive a distance to NLTT 15788 of 179

pc, and find VRF = 271 km s−1.

NLTT 17039

NLTT 17039 has VRF = 564 km s−1± 141 km s−1. Our distance estimate to

NLTT 17039 is 381 pc, in good agreement with our secondary distance estimate

of 372 pc, but both may be influenced by the high estimate for the interstellar

reddening (E(B − V )=0.1).

Two previous studies report kinematic information for NLTT 17039. Yong

& Lambert (2003) find VRF = 336 km s−1± 178 km s−1. Ryan & Norris (1991)

derives a distance of 233 pc, with E(B − V )=0.06, and a restframe velocity of VRF

= 345 km s−1. Again for this star our high reddening estimate may have caused an

overestimate of the distance to this star.

267

4.7. Conclusions

We have described the kinematics of a sample of stars presumed to be members

of the Galactic halo. We find that the entire sample is consistent with having halo

kinematics, regardless of metallicity. We thereby confirm that the stars in the sample

are halo stars, and produce the somewhat surprising result that a significant fraction

of the present sample have halo kinematics but relatively high metallicity.

We discuss the discovery of two moving groups in the sample. The stars in

each group have very similar (U, V, W ) velocity components and are likely to be

associated with each other. Perhaps these groups are the remaining signature of

the merging of an external satellite with the Galaxy. We also discuss the possible

discovery of a larger merger remnant moving through the solar neighborhood. These

stars might be associated with a more recent merger still in the process of being

assimiliated into the Galaxy.

Finally, we find one very good HVS candidate (NLTT 9437) as well as several

other possible high velocity stars. Interestingly, the HVS candidate is moving in

the direction of rotation of the Galaxy; this does not fit the only existing model for

creating HVSs of ejection from interaction with the black hole at the center of the

Galaxy.

268

Fig. 4.1.— (U, V, W ) of the entire sample of 295 stars.

269

Fig. 4.2.— (U, V, W ) of 290 subdwarfs.

270

Fig. 4.3.— (U, V, W ) vs. [Fe/H]

271

Fig. 4.4.— (U, V, W ) of the two moving groups found in the sample. The three stars

in one group are marked with filled triangles, while the three stars in the other group

are marked by filled circles.

272

Fig. 4.5.— Reproduction of Figure 9 from Chapter 2.

273

Fig. 4.6.— Reduced proper motion diagram of the sample. The stars in the proposed

merger remnant have larger points.

274

Fig. 4.7.— (U, V, W ) of the stars with measured velocities in the proposed merger

remnant. The 15 stars in the restricted sample are plotted as filled circles, the stars

selected from the RPM diagram are drawn as open triangles. The remaining stars in

the sample are plotted as crosses.

275

Fig. 4.8.— (U, V, W ) vs. [Fe/H] for the proposed merger remnant.

276

NLTT ID U σ(U) V σ(V ) W σ(W )

(km s−1) (km s−1) (km s−1) (km s−1) (km s−1) (km s−1)

57 −288 58 −81 37 −230 40

341 332 70 −430 76 7 47

812 −343 59 −255 33 −51 51

1059 233 57 −294 46 2 34

1635 235 53 −451 90 −232 60

1870 −395 70 −127 20 −45 45

2045 184 42 −113 25 80 38

2404 −245 50 −313 71 −219 44

2427 −247 42 −219 36 13 44

3516 739 154 −769 153 16 38

3531 85 20 −118 32 −73 37

3985 165 38 −369 76 −28 39

4817 −199 39 −271 53 −219 60

5052 −10 10 −319 66 −39 39

(cont’d)

Table 4.1. Galactocentric Velocity Components

277




5193 −80 22 −102 20 −36 34

5222 76 27 −598 122 −38 39

5255 372 70 −289 62 −68 41

5404 68 25 −355 71 25 38

5506 40 26 −156 30 19 31

5711 −145 30 −212 44 −83 42

5881 80 29 −153 33 −14 29

6415 55 20 −368 75 32 39

6774 104 28 −141 30 55 38

7299 187 42 −288 59 86 41

7415 180 46 −223 45 122 38

7417 −102 19 −61 13 127 36

7966 −47 28 −198 37 −44 32

7968 −158 29 −208 31 −18 36

8034 303 42 −241 54 −115 38

8227 272 39 −267 49 −111 42

(cont’d)278




8230 −388 64 −631 130 76 40

8459 −145 31 −317 57 −120 48

8720 −191 34 −418 78 −163 58

8783 292 39 −210 55 −105 28

8833 −112 28 −126 27 −16 35

9026 −19 21 −288 59 44 35

9382 178 44 −214 47 74 30

9437 −156 37 −984 199 23 36

9578 −30 24 −297 59 −24 33

9597 −85 30 −413 84 −39 33

9628 −220 37 −250 56 86 35

10536 −93 34 −382 76 −69 32

10821 135 22 −585 105 −35 47

10850 277 62 −1518 305 25 26

11007 217 33 −357 63 40 49

11486 77 24 −65 9 −44 31

(cont’d)279




11515 −195 35 −318 70 97 30

11584 −269 49 −392 83 −22 34

11795 −102 35 −472 96 2 27

12017 −17 29 −121 23 −53 28

12103 −152 38 −229 47 −22 30

12350 316 51 −285 49 197 68

12845 377 42 −186 23 40 51

12856 −322 48 −243 60 34 30

12986 73 28 −375 65 55 40

13344 −256 35 −144 44 134 24

13660 85 38 −153 32 108 29

13770 −307 64 −359 75 −194 48

13811 −255 57 −381 79 −124 36

13899 −173 41 −337 71 99 28

14091 −136 38 −304 64 117 19

14131 −234 40 −301 71 118 22

(cont’d)280




14169 91 39 −344 69 −26 13

14197 118 38 −256 51 −61 13

14391 31 41 −365 73 −153 29

14606 −173 48 −343 70 13 21

14658 −107 40 −331 63 98 31

14805 −173 48 −446 91 43 17

14822 −146 36 −112 32 23 16

15161 131 29 −317 38 64 38

15183 30 37 −266 44 36 21

15218 −87 40 −245 53 −60 16

15529 107 37 −503 58 95 50

15788 −482 99 −479 98 −156 36

15939 −444 82 −306 75 −75 30

15973 −251 41 −275 65 112 20

16242 −10 39 −132 32 −27 7

16250 −201 55 −295 57 −12 15

(cont’d)281




16320 41 39 −58 21 −17 5

16444 −342 68 −363 80 143 27

16579 −33 42 −277 56 115 22

17039 −486 85 −463 109 150 29

17136 −161 46 −221 44 146 30

17234 −211 41 −129 43 11 3

17485 −69 41 −233 44 −94 23

17738 −82 33 −121 29 35 6

17786 −238 41 −303 74 −122 22

17872 7 37 −177 40 −82 24

18424 −87 37 −109 34 38 15

19550 −230 44 −57 33 63 18

20232 115 28 −96 29 −300 66

20691 −270 56 −193 49 −8 18

20792 −94 36 −241 33 16 17

20980 −142 42 −199 35 47 18

(cont’d)282




21084 −267 53 −198 52 −123 30

21744 213 28 −278 26 −28 36

22026 213 28 −332 51 −20 49

22520 −207 52 −245 42 45 24

24839 145 32 −79 31 −157 40

24984 203 45 −321 68 −220 59

25177 175 31 −263 47 −21 46

26482 −163 35 −259 37 70 36

26650 282 60 −146 59 −399 65

27436 126 28 −66 28 −80 35

27831 239 50 −52 24 −29 28

28199 −56 10 −219 40 −24 40

28459 60 19 −217 36 −28 39

28955 114 32 −323 47 −26 44

29551 201 43 −253 54 −35 42

29905 140 34 −377 72 −220 61

(cont’d)283




29933 −28 5 −335 65 13 43

30274 −141 24 −357 49 −24 52

30400 93 30 −427 74 −135 57

30462 162 32 12 20 −70 33

31233 117 29 −215 48 −107 39

32316 73 18 −314 65 −40 40

32648 −241 37 −332 55 −5 50

33146 321 67 −282 61 −6 36

33221 −108 27 3 14 −80 35

33371 217 61 −179 26 251 37

33823 101 31 −103 22 54 31

33971 −301 57 −348 68 −198 61

34051 123 42 −236 40 166 35

34628 112 21 −228 48 −82 39

35068 −440 70 −355 61 −102 66

35890 −185 28 −663 120 −228 80

(cont’d)284




36059 −222 40 −429 83 −180 60

36446 −27 28 −422 77 −47 40

36520 150 47 −330 64 33 27

36564 −65 26 −405 78 −149 50

37158 −176 30 −554 98 −16 52

37658 232 47 −302 66 4 30

37807 −16 21 −463 93 −19 35

37960 254 48 −216 46 62 41

38221 254 56 −334 70 115 38

38311 −326 59 −251 51 −156 56

38814 −58 30 −411 84 −86 36

39121 158 35 −158 39 −39 22

39456 −324 34 −503 88 −52 54

39457 −320 34 −517 91 −66 56

39670 94 34 −444 93 −138 32

40003 235 47 −170 38 147 45

(cont’d)285




40723 −12 38 −506 100 14 24

41218 −279 41 −182 35 −116 48

42183 −225 61 −551 106 −53 28

42301 −63 34 −363 68 54 34

43291 −69 38 −197 42 47 14

43887 −110 38 −271 59 71 16

43923 −280 38 −139 36 64 13

44039 −69 40 −422 74 109 39

44226 101 30 −362 47 30 37

44568 −285 53 −150 42 −54 28

44639 45 31 −247 37 55 30

44683 15 39 −96 23 −56 14

45026 45 39 −78 21 −42 10

45609 −203 53 −235 46 −96 22

45616 −280 51 −179 50 29 15

45754 −78 41 −314 67 −46 14

(cont’d)286




46039 −335 67 −254 59 −86 24

46730 −652 143 −1103 216 −250 56

46738 −831 157 −1196 249 83 43

47073 −89 42 −295 63 −33 12

47132 −137 35 −84 29 −11 8

47242 −75 38 −119 34 4 6

47257 33 41 −248 47 71 12

47331 −184 40 −98 34 6 5

47425 −248 48 −214 57 −31 12

47481 −183 44 −186 48 −86 20

47543 −89 41 −205 42 41 7

47711 −309 39 −155 53 −108 16

47811 −321 47 −246 67 50 25

47944 −102 38 −145 38 −14 10

47972 23 43 −304 46 74 10

48056 −316 53 −221 64 16 14

(cont’d)287




48062 −82 33 −50 29 −57 14

48133 −221 46 −209 54 99 27

48149 −147 38 −187 50 −63 17

48592 −480 103 −388 74 51 16

48866 −180 55 −297 46 −89 27

48925 −342 61 −440 101 −70 22

49226 −197 43 −118 39 78 26

49301 −100 36 −407 86 −223 51

49487 −112 29 −59 29 9 12

49618 −198 57 −383 72 5 21

49624 −138 41 −412 86 −85 30

49627 −245 49 −327 75 2 23

49821 −204 51 −307 64 −82 29

49872 −51 38 −393 72 −104 40

49949 −210 62 −471 87 −32 31

50185 −123 35 −191 47 −49 24

(cont’d)288




50190 −211 51 −258 57 20 22

50257 −161 43 −335 69 −193 49

50270 −139 41 −378 79 −76 31

50339 −290 61 −253 59 139 38

50474 −145 48 −387 66 −111 42

50556 −338 76 −252 43 65 18

50869 19 27 −181 34 51 25

50911 45 27 −190 52 −365 73

50937 382 54 −311 49 −198 79

51824 −233 41 −159 50 −90 28

51856 −441 97 −310 45 15 25

52398 −52 32 −516 96 −101 51

52456 −126 30 −195 49 −60 31

53274 −256 54 −377 78 −91 38

53480 375 56 −270 36 5 55

53707 43 17 −303 55 −21 42

(cont’d)289




53781 62 20 −237 48 −63 43

53801 −151 31 −204 50 −101 37

53823 64 20 −157 38 −62 39

54027 107 27 −338 69 −139 50

54730 340 72 −247 58 −321 70

55603 −177 36 −222 51 −21 36

55732 −199 39 −315 69 −77 38

55733 498 101 −281 35 −20 47

55942 197 37 −284 51 −52 48

56002 −173 34 −223 31 4 36

56290 −300 63 −372 70 14 40

56534 −165 40 −174 34 164 37

56774 −193 44 −382 74 59 39

56818 −90 15 −242 33 −23 39

56855 466 97 −234 54 −196 54

57038 41 17 −180 51 −207 43

(cont’d)290




57452 −148 28 −112 33 −56 37

57564 74 18 −258 55 −57 42

57631 −299 57 −176 44 −37 38

57647 348 68 −293 57 −1 46

57741 74 20 −310 66 −89 43

57781 180 38 −166 38 −50 40

57856 357 75 −478 100 −206 54

58071 202 49 −436 70 −160 63

291

[Fe/H] N < U > < V > < W > σ(U) σ(V ) σ(W )

(dex) (km s−1) (km s−1) (km s−1) (km s−1) (km s−1) (km s−1)

Present Sample

−0.6 to −0.8 28 −87±10 −300±10 −55±10 232±10 205±10 96±10

−0.8 to −1.0 33 −74±10 −202±10 −5±10 172±10 90±10 75±10

−1.0 to −1.6 69 −53±10 −300±10 −28±10 228±10 152±10 102±10

−1.6 to −2.2 52 −54±10 −304±10 −31±10 225±10 158±10 107±10

≤ −2.2 25 0±10 −302±10 −37±10 191±10 293±10 114±10

(cont’d)

Table 4.2. Comparison between the present sample and that of Chiba & Beers (2000)

292


[Fe/H] N < U > < V > < W > σ(U) σ(V ) σ(W )

(dex) (km s−1) (km s−1) (km s−1) (km s−1) (km s−1) (km s−1)

Chiba & Beers (2000) Sample, |Z| < 1 kpc

−0.6 to −0.8 141 2±4 −30±5 −5±3 50±3 56±3 34±2

−0.8 to −1.0 79 7±10 −62±10 1±6 93±7 86±7 50±4

−1.0 to −1.6 194 8±9 −122±7 −1±6 122±6 104±5 81±4

−1.6 to −2.2 205 23±10 −178±8 −2±6 147±7 115±6 87±4

≤ −2.2 78 17±16 −187±12 −5±11 141±11 106±9 94±8

293

Sample N < U > σ(U) < V > σ(V ) < W > σ(W )


All 230 −53 219 −290 177 −29 100

PMR 71 −45 239 −329 126 −40 110

PMR, HV >15 15 39 315 −398 143 −57 108

NOT in PMR 167 −56 213 −276 191 −25 97

Table 4.3. Velocity components for subsets of the sample.

294

Chapter 5

Mapping the Local Galactic Halo. IV. The

Metallicity Distribution Function

5.1. Introduction

The metallicity distribution of the Galactic halo is currently well understood in

general but is poorly known in detail. For instance, since the work of Baade (1944)

it has been known that two populations of stars, i.e., metal-weak and metal-poor,

exist in the Galaxy. By the time of Eggen, Lynden-Bell, & Sandage (1962), it was

well-known that the Galactic halo shares the properties of Baade’s halo globular

clusters and is largely composed of stars with much lower metal abundances when

compared with the Sun and other disk stars. But exactly what is the true shape

of the metallicity distribution of the halo is difficult to measure: it is difficult to

separate cleanly different halo populations (i.e., disk from thick disk from halo), it

is difficult to fully sample the stars in the halo, especially since most halo stars are

very far away from the sun, and even if one studies the local halo, it is difficult to

construct an appropriate volume-limited sample.

295

The metallicity distribution function (MDF) provides information about the

chemical evolution of the Galaxy. Understanding the distribution of metallicities,

especially in the halo, allows us to understand the chemical make-up of the early

Galaxy. Particular important questions that remain to be answered include what is

the distribution of stars at very low metallicity, whether or not there is a mininum

metallicity below which stars do not exist, and what is the metallicity of the most

metal-poor star in the Galaxy.

The metallicity distribution function of the Galaxy has been studied by several

authors. A model for the MDF, now known as the “simple model”, was proposed by

Hartwick (1976), derived using observations of globular clusters. This model is still

used to explain the metallicities observed in studies of the Galactic halo.

There have been several surveys that have produced large datasets to study

the characteristics of the halo. The HK survey (Beers, Preston, & Shectman 1985,

1992) and the HES survey (Wisotzki et al. 2000) study large numbers of metal-poor

stars, although these surveys are focussed on finding the most metal-poor stars

in the Galaxy and as such have metallicity biases that prevent their use to study

the MDF. Ryan & Norris (1991) study the halo metallicity distribution using

kinematically-selected stars and find good agreement between their observations

and the simple model. Laird et al. (1988) isolate a halo star population from their

extensive dataset and note a paucity of very metal-poor stars as compared with the

296

simple model. They also investigate the metal-rich end of the halo MDF for the first

time.

More recently, Beers et al. (2005) discuss the importance of deriving the halo

metallicity distribution function. In particular, they focus on the huge database of

the SDSS survey and how it will undoubtedly change the way in which we study

and understand the Galaxy. The SDSS-II extension known as the Sloan Extension

for Galactic Understanding and Exploration (SEGUE) is composed of many surveys

studying different Galactic populations; however, none of the individual targeted

studies are focused on the study of the Galactic halo as a whole. This is not to

say that SDSS/SEGUE will be useless for studying the halo; on the contrary, the

overwhelming numbers of stars observed both photometrically and spectroscopically

by SDSS will provide an enormous database from which to cull a huge number of

Galactic halo stars.

In this work we present a study of the distribution of metallicities in the

local Galactic halo based on a sample of local halo subdwarfs. The data presented

by the current study are ideal for deriving at least the local halo MDF. While

this proper-motion–selected sample is strongly kinematically biased, it should be

unbiased in metallicity and should give an accurate representation of the local

MDF. The results presented here are based on data presented in Chapters 2 & 3.

Chapter 2 describes the sample selection and presents photometry for 635 candidate

297

cool halo subdwarfs. Chapter 3 presents the spectrophotometric data, including

derived metallicities of 254 candidate subdwarfs.

5.2. Metallicity Histogram

In Chapter 3 we present a histogram of derived metallicities for 254 stars. We

reproduce that figure here as Figure 5.1. However, the main goal of the present work

is to investigate the MDF of the halo; to this end, we now restrict this sample to

include only stars with halo kinematics. We follow the suggestion of Ryan & Norris

(1991) to kinematically select stars that are most likely to be halo members from

the sample. We constrain the set of halo stars to have a total velocity in the rest

frame of the Local Standard of Rest (LSR) to be VRF >250 km s−1 (see Chapter 4).

This constraint effectively excludes all stars with disk-like velocities, and is not

unlike the constraint imposed by Laird et al. (1988) of selecting stars with only

retrograde orbits to study the halo MDF. The velocities and selection criteria are

presented in Figure 5.2. Imposing these criteria yields a sample of 130 halo stars.

The MDF of the stars so selected is presented in Figure 5.3. The selection criteria

applied do not noticeably change the metallicity distribution of the sample. This

is not surprising, since the sample is composed to contain only halo members (see

Chapter 2). Nonetheless, we will continue with the 130 halo stars.

298

5.3. Metallicity Distribution Function

We derive the metallicity distribution function for the sample following Bond et

al. (1981). This formalization takes the form of a “generalized histogram”, in which

the bins are convolved with a Gaussian to take into account the uncertainty of the

observations. The metallicity distribution function is defined as follows:

φ(z) = N−1∑

K(z − zi) (5.1)

where z=10[Fe/H],

K(z − zi) = Cexp[−(logz − logzi)2/2σ2)] (5.2)

and

C = [(2π)1/2(ln10)ziσ]−1exp[−(σln10)2/2] (5.3)

For the present sample we assume σ=0.35, reflecting the error estimate on the

metallicities (see Chapter 3).

The derived MDF is presented in Figure 5.4. It is quite surprising to find

that the MDF peaks at [Fe/H]=−0.9. The mean metallicity of the Galactic halo

is generally taken to ∼ −1.5; indeed, both Laird et al. (1988) and Ryan & Norris

(1991) study the metallicity distribution of the halo and both find [Fe/H]∼ −1.6.

299

This low mean metallicity of the halo also agrees with the metallicity distribution

function of the Galactic globular clusters (Huchra et al. 1991; Harris 1996). There

are several possible explanations for this discrepancy. In Chapter 3 we note a ∼ −0.4

dex offset between the derived metallicities used by Laird et al. (1988) and our

determinations. This offset could explain a large amount of the discrepancy in the

peak of the MDFs. It is also possible, although unlikely, that the present sample

differs significantly from the samples of Laird et al. (1988) and Ryan & Norris (1991)

in such a way as to include large numbers of metal-rich halo stars. This would be

very surprising, however, since there should be very few metal-rich stars in the halo.

Finally, it is possible that the distance estimates in the present sample, and therefore

the kinematics of the present sample, have systematic errors that cause the stars

to appear to be halo stars when in fact they are disk stars. However, the initial

selection criteria were chosen to select only halo stars from the rNLTT. We conclude

that the high-metallicity peak in the derived MDF of the present sample is most

likely due to a systematic error in our metallicity estimates of order 0.4-0.6 dex.

5.4. Comparison to Models

Despite being several decades old, the so-called “simple model” of Hartwick

(1976) is still thought to best describe the chemical evolution of the Galaxy. The

model describes a closed system, starting with a gas cloud of zero metallicity. Star

300

formation begins as time passes, and massive stars evolve and enrich the initial

gas cloud with their metals; the gas is assumed to be well-mixed. The model is

parameterized by the ratio of the mass of metals produced by massive stars to

the mass locked into existing stars, called the yield (y). If the model is allowed to

proceed until all of the gas is processed, y =< [Fe/H] >. Low-mass stars formed in

the early Galaxy have ages longer than the age of the Galaxy, and will not evolve

off of the main-sequence. These stars form a tracer of the chemical composition

of the Galaxy in which they were formed. Stars that form later will be polluted

by metal enrichment by early massive stars. In the Hartwick (1976) model, star

formation ends either by consumption of all of the gas or by mass loss of gas from

the Galaxy. Metal enrichment by massive stars is assumed to occur instantaneously,

which implies that the yield is set by the initial mass function rather than the star

formation rate.

The form of the simple model is an exponential metallicity distribution,

f(z) = y−1exp(−z/y), (5.4)

where y is the yield and z=10[Fe/H].

Laird et al. (1988) fit a simple model to their data which constitutes a sample

similar to the present sample. They find a best fit for logy = −1.49. We plot

this simple model with the derived MDF of the present sample in Figure 5.5. As

301

discussed above, there is a large mismatch between the peaks of the distributions.

We suspect that the metallicities derived here are overestimated by several dex. If

we disregard this offset, the distribution functions of the two samples appear very

similar. This is further confirmation that the metallicities of the present sample are

slightly overestimated.

5.5. The Metal-Weak Tail

We now turn to the metal-weak tail of the distribution. The most metal-poor

stars in the sample are arguably the most interesting, since not only are they most

certainly members of the halo and provide information about the character of the

local halo, but also the metal-poor stars in this sample are very old and therefore

tell us about the conditions of the early Galaxy.

We compare the most metal-poor stars in the present survey to those found

by the (non-kinematically–selected) HK Survey (Beers, Preston, & Shectman 1985,

1992). Figure 5.6 shows a histogram of the metallicity estimates of the present

survey compared with those of the HK Survey. As mentioned above, this survey

was constructed in order to discover very metal-poor stars; as such, it is biased in

metallicity. Consequently, it is slightly surprising that these two distributions are so

similar.

302

Figure 5.6(a) gives an enlarged version of the metallicites derived in this

study, focusing on the low-metallicity tail. Figure 5.6(b) gives the a histogram of

metallicities of the metal-poor stars in the HK survey (Beers, Preston, & Shectman

1985, 1992) for comparison.

The slightly less metal-poor peak of the present work compared to the HK

survey (at [Fe/H]∼ −1.8 in the present sample compared to [Fe/H]∼ −2.1 in the

HK survey) is slightly surprising, since the present sample should have a large

fraction of true halo stars with very low metallicities. However, the HK Survey was

constructed to select stars specifically with [Fe/H]< −2.5, slightly more metal-poor

than the average halo population ([Fe/H]∼ −1.6) and therefore preferentially selects

very metal-poor stars. The peak at higher metallicity may again be due to the

metallicities derived in Chapter 3 being overestimated.

5.6. Conclusions

We have presented the metallicity distribution function of a sample of local

halo subdwarfs. We find that the metallicity distribution of the sample peaks

at [Fe/H]∼ −0.9, significantly higher than the expected mean halo metallicity of

[Fe/H]∼ −1.5. We also find that the MDF is not well fit by the simple model of

Hartwick (1976), and is skewed to higher metallicity than expected. We conclude

303

that this offset in metallicity may be due to errors in our method for calculating

metallicities.

304

Fig. 5.1.— Metallicities of 254 stars with metallicity estimates, recalled from

Chapter 3.

305

Fig. 5.2.— Rest-frame space velocities for the stars with metallicity estimates. We

impose the criteria VRF >250 km s−1 to select a “pure” halo population.

306

Fig. 5.3.— The MDF for only the halo stars in the sample.

307

Fig. 5.4.— Metallicity distribution function for the sample.

308

Fig. 5.5.— Metallicity distribution function of the sample (solid line) compared to

the best-fit simple model of Laird et al. (1988) (dashed line).

309

Fig. 5.6.— Comparing the low-metallicity tail of this work to that of the HK Survey.

310

Chapter 6

An Image Motion Compensation System for the


6.1. Introduction

Large telescopes working near the seeing limit or over large angular fields

generally require large instruments. This is particularly true of instruments that

need collimated beam space for gratings or other dispersing elements. For example,

the Large Binocular Telescope (LBT; Hill & Salinari 2000) delivers an f/15 beam to

the Gregorian focus, so the collimator for even a modest field of view is large and

has a long focal length. Furthermore, additional optics that could be used to fold

the instrument are undesirable when the goal is to maintain the highest possible

throughput, since every photon from a large, expensive telescope is precious.

The Multi-Object Double Spectrograph (MODS; Osmer et al. 2000) that the

Imaging Sciences Laboratory in the Department of Astronomy at The Ohio State

University is building for the Gregorian focus of the LBT. The design requirement

for MODS to have high throughput eliminates any folds of convenience in the

311

instrument, and therefore forces the instrument to be physically quite large (∼2.5

meters wide by ∼4 meters long; ∼2000 kg); this large size, and in particular the

extreme length, suggests that some sort of flexure compensation is required.

The large size of the instrument causes a variety of problems. In particular,

despite careful structural design and analysis, the measured motion of an image at

the MODS focal plane due to structural flexure, temperature gradient induced shifts,

and other similar behavior is unacceptably large, on order 600 µm (∼40 science CCD

pixels) when the instrument is moved through 90 degrees of the sky. Two types of

compensation solutions are available to correct for this image motion: open-loop

and closed-loop. Open-loop systems are undesirable for this application due to

their reliance on the repeatability of flexure; they intrinsically cannot compensate

reliably for unpredictable changes in the instrument, especially when motion control

requirements are tight. Open-loop systems generally rely on a pointing model that

must be physically updated often (at least monthly), a labor-intensive procedure.

However, real-time active closed-loop compensation systems operate continuously

and correct for any image motion (no matter the cause) and with adequate feedback

can be made extremely precise. MODS will incorporate a closed-loop system image

motion compensation system.

An example of a closed-loop system to control image motion is familiar to all

astronomers. Standard autoguiders based on imaging detectors (ISITs, CCDs, eyes,

etc.) are available on almost all modern telescopes. Such autoguiders are often part

312

of a telescope control system that includes tracking correction for telescope flexure

based on a model of the telescope structure (an open-loop component); feedback is

established by locking the position of a star on a detector at a particular fiducial

location and using small telescope movements to compensate for any small motion

of the stellar image. The feedback mechanism can be as diverse as digital signals

generated by analysis of an image directing the speed and direction of the telescope

optical axes (using a tip-tilt secondary, for example; see Probst et al. 1998; Elston

et al. 1997). to fingers pressing buttons on a guide paddle. In either case, an active,

closed-loop system can readily compensate for all sources of image motions.

The IMCS is an innovative closed-loop flexure compensation system for the

MODS spectrograph, the workhorse optical spectrograph at the Gregorian focus of

the Large Binocular Telescope. The IMCS actively compensates for image motion

in the instrument focal plane caused by temperature fluctuation, mechanism flexure,

and large scale structural bending due to gravity. The IMCS has been designed

(Marshall et al. 2003) and fully prototyped in the lab (Marshall et al. 2004), and is

now installed in the MODS instrument (Marshall et al. 2006). The IMCS utilizes an

infrared laser as a reference beam that shares a light path with the science beam

and is detected by an infrared reference detector adjacent to the science detector.

The reference detector is read out at 10 Hz and detects any image motion in the

focal plane. The IMCS compensates for this motion during a science exposure by

adjusting the tip and tilt angles of the collimator mirror at 1 Hz. Note that the

313

IMCS is not intended to compensate for rapid image motions such as those due to

atmospheric disturbances (seeing); the LBT will be equipped with fully adaptive

secondary mirrors that will perform this task.

In this Chapter I describe the design, lab testing, and on-instrument testing of

the IMCS on the MODS spectrograph. In Section 6.2 I describe the design concept,

initial component selections, and tests of the IMCS. Section 6.3 discusses the tests

of the system and components in the laboratory, and Section 6.4 presents results

from the IMCS as installed on the MODS instrument. Section 6.5 is a summary

of the final performance of the IMCS and the deployment schedule for the MODS

instrument.

6.2. System Design, Specifications, and Operations

6.2.1. System Design

The IMCS functions as an active, real-time compensator for image motion in

the plane of the science detector in MODS. A design requirement of the IMCS is that

the IMCS lightpath traces the science lightpath and uses the science optics wherever

possible. Motion of the reference beam is monitored and nulled by active movement

of the instrument collimator mirror, thereby nulling image motion of the science

beam as well. The compensation occurs simultaneously with science operation, to

314

minimize image motion effects on the quality of the science data. Figure 6.1 shows a

schematic of the system.

6.2.2. Optical Layout

A key to successful operation of the IMCS is that the reference beam follows an

optical path nearly identical to the science beam. The IMCS uses the same optical

elements as the science light whenever possible.

The 1.55 µm reference beam originates at the telescope focal plane, just outside

the science field. Reference beam projection optics produce an f/500 beam that will

only partially fill the MODS optics. In dual-channel mode, the reference beam passes

through the dichroic and is split into the red and blue channels (see Figure 6.1).

The MODS dichroic transmits 40% and reflects 60% of the 1550 nm light, hence the

same reference beam is used for both channels. In each channel, both science and

reference beams are reflected by the collimator mirror to the grating. The collimator

mirror will tip and tilt to correct for image motion (see discussion below).

The telescope pupil image formed at the MODS grating has a central shadow

due to the telescope secondary. A bypass grating, tuned for optimal use at 1.55 µm,

will be placed in this shadowed position on the science grating. There will be no

vignetting of the science beam, since the secondary shadow is 25 mm in diameter

and the bypass grating measures 12.5 mm in diameter. The bypass grating will be

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mounted in a hole in the science grating corresponding to the secondary shadow,

and tilts with the science ruling. When installed in the science grating, the bypass

grating tilt can be adjusted to place the reference spot on the reference detector.

The bypass grating will disperse the beam into many orders, which will be separated

by a distance in the science focal plane small enough to allow at least one image of

the reference beam to be on the reference detector at all times.

The dispersed beam is reflected to the off-axis Maksutov-Schmidt camera (see

Byard & O’Brien 2000). The camera presents no problem for propagation of infrared

light, since the mirrors and lenses in each channel transmit infrared light. The filters

used in the science beam must be opaque to infrared light and therefore will not

transmit the reference laser light at 1.55 µm. A bypass hole is located on one side

of the filter at each position of the wheel through which the infrared reference beam

will pass. The bypass holes will be fitted with infrared filters to prevent any light

leaks into the science beam.

6.2.3. Specifications

The IMCS is required to control image motion over one hour to a tenth of a

resolution element, or 6 µm (±1 standard deviation; ±1 σ) for a 0.′′6 slit on the

LBT. Ideally the IMCS will perform much better than this, and the system goal

is to control image motion to 1.5 µm over one hour (∼0.1 pixel). The IMCS must

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not interfere with the science beam; contamination of the science light is avoided

by choosing an infrared laser to use as the reference beam. In order to meet these

requirements, our design strategy is to require that the IMCS accurately track the

motion of the science beam. This is accomplished by having the reference beam

share the science beam path and as many optical components as possible.

These specifications should ensure that there is no significant degradation of

the science data, based on experience with previous spectrographs. Finite element

analysis of the MODS structure indicates that motions of ∼200 µm are expected as

the instrument is pointed over the entire sky.

6.2.4. Operations

The IMCS will be operated at the telescope in an on/off mode, with virtually

no input from the observer. The IMCS is automatically aligned at the beginning of

each night so that a laser spot is detected by and centered on the reference quad

cell detector. Before beginning an observation the observer will turn on the IMCS,

the IMCS will open the shutter, center a spot on the quad cell detector, close the

shutter, and will signal the observer that the system is ready to start the observation.

The observer will start the observation and the IMCS will guide on the spot during

the entire observation. At the end of the observation the shutter will close and the

IMCS will remain idle until the observer begins the next observation.

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6.2.5. System Component Selection

Reference Beam Source

MODS is an optical spectrograph designed to work over wavelengths from

320-1000 nm using CCDs as the science detectors. The requirement to operate the

IMCS during science exposures without compromise of the science data quality led

us to select an infrared laser as the IMCS reference light source.

The IMCS uses two lasers, one optical (633 nm) and one infrared (1550 nm).

The final implementation of the IMCS will use commercially available Thor Labs

lasers because of their modular design and ease of replacement in case of failures.

Each laser unit consists of a box, including a power supply, which contains the

laser diode. The laser is output through a fiber port on the front of the box.

A fiber connects to the box and transfers the beam to the desired location. A

laser collimator lens mounts to the fiber head to collimate the beam; this usage is

modified slightly, placing the lens slightly further from the fiber tip to produce not a

collimated beam but rather an approximately f/40 beam, which is of the appropriate

diameter to fill the IMCS prototype optics (the same technique will be used in the

MODS instrument, but instead will produce an f/500 beam, yielding a spot that

fills the bypass grating). The 1550 nm infrared laser will be used to measure image

motion; the 633 nm visible laser is for alignment purposes only and will be turned

off whenever MODS is performing science observations.

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The reference laser beam cannot contaminate the science beam. Lab tests

demonstrate that at 1550 nm a standard CCD (SITe SI-003AB) has a quantum

efficiency of ∼10−10. Since the reference beam does not focus directly onto the CCD

in the IMCS, the science detector cannot detect the reference beam. Furthermore,

observations of the laser through a series of optical filters confirm that the laser

produces only 1.55 µm light.

Laser combination block

The laser fibers mount to the combination block at right angles to each other.

The laser combination block uses a dichroic beamsplitter to combine the two laser

beams, producing a beam that is detectable by the infrared quad cell and a CCD

camera, as well as by eye. Again, this capability is for alignment purposes only,

and the optical laser will be turned off separately from the infrared laser during use

to avoid contamination of the science beam with scattered visible laser light. The

infrared laser passes straight through the prism to minimize possible image motion

due to possible movement of the prism. The combination block is the same unit that

will be deployed in MODS. Figure 6.9 shows a photograph of the block mounted to

the lab optical bench.

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Control Software

The control software must locate the reference spot on the reference detector,

compute the centroid of the spot, compare to a reference position, and send the

appropriate signals to the collimator actuator control system. These measurements

will be made at 10 Hz, with collimator corrections (made of the average of the

previous 10 measurements, in order to remove “seeing” effects) made every 1 second,

to ensure minimal science image motion on the science detector. The software will

be invisible to the observer; operation of MODS will include only an on or off state

of the IMCS.

Laser Power and Beam Profile

The IMCS laser will be operated at 1.5 mW, providing more than enough power

in the laser spots at the reference detector. Figure 6.3 shows the beam profile of the

IMCS laser, measured in the plane of the MODS science grating.

The f/500 beam produced by the laser combination block optics produces a

∼6.5 mm D80 spot (the radius at which 80% of the energy is encircled) at the bypass

grating.

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Bypass Grating

The bypass grating is a 12.5 mm diameter diffractive optic that is designed

to produce 27 orders (13 orders on either side of zeroth order) of nearly equal

intensity from the 1550 nm laser. A diffractive optic is a reflection grating with

a modified groove profile to give a large number of orders of approximately equal

intensity (sometimes known as a fan-out element). The grating was designed by and

purchased from Holo Or Ltd. (http://www.holoor.co.il/), a company that specializes

in holographic gratings. Figure 6.4 shows the measured peak intensity of the 27

orders. The 6.5 mm beam diameter of the infrared laser sufficiently fills the 12.5

mm bypass grating; i.e., the bypass grating need not be fully filled by the laser to

function as designed.

The bypass grating is positioned in the center of the science grating, which

coincides with the shadow of the telescope secondary mirror. A hole has been made

in the center of each MODS science grating and the imaging flat. The bypass grating

is mounted in this hole with adjustable tip and tilt with respect to the surface of the

science grating. This allows the bypass grating to direct the IMCS beam onto the

IMCS detector (adjacent to the science detector) while the science beam is centered

on the science detector.

The bypass grating produces a line of spots in the plane of the reference

detector (see Section 3.2). The IMCS operates by centering one of these spots on

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the quad cell, and guides on this spot for the duration of the observation. The spots

are spaced at 5mm intervals; a consequence of this is that only quantized grating

settings are allowed, i.e., that the central wavelength on the science detector can

be adjusted in intervals of 5mm (which translates to 333 unbinned pixels on the

science detector). This affects the science observations in that the observer does not

have complete freedom over what wavelength lies at the center of the detector. This

feature affects observations at various resolutions in different ways: since MODS

fully illuminates a detector as long as 123mm (8K x 15 µm pixels), resolutions lower

than R∼3000 are not affected. Higher resolutions, up to the MODS maximum of

R∼15000, will be affected. The grating is adjustable in 333 pixel increments, or by

about 4% of the wavelength coverage of the detector. First light MODS observations

will be done with a R∼2000 grating, so this will not be a consideration initially.

Laser Spot Size

The proportional gain of the on-instrument IMCS control loop is determined

by the final reference spot size on the reference quad cell. The measured spot

diameter on the 5mm quad cell detector is 0.25 mm (D80). The position sensitivity

is proportional to the spot size on the detector.

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Infrared Quad Cell Detector

The reference detector is an infrared-sensitive germanium quad cell detector.

The quad cell has four adjacent pixels whose sensitivity peaks near the wavelength

of the reference beam. The nature of this detector simplifies the measurement of the

position of the laser spot and is easy to read out with simple software or even an

oscilloscope.

Compensation Mechanism

The IMCS control loop is closed by tilting the MODS collimator mirror

to compensate for motion of the reference beam on the infrared detector. The

collimators are mounted in a support structure that is moved by three linear

actuators. The actuators each consist of a stepper motor, a 100:1 harmonic gear

reducer, and a linear lead screw slide. The actuator is coupled to the collimator cell

support via a blade flexure and a torsion flexure in series. This flexure combination

acts kinematically like a ball joint and the combination allows the collimator mirror

to move on three axes: focus (z-axis translation), tip (rotation about the x-axis),

and tilt (rotation about the y-axis), while constraining the remaining three degrees

of freedom: x- and y-axis translation and z-axis rotation (twist). See Figure 6.5 for

a diagram of actuator placement.

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Three characteristics affect actuator performance: hysteresis in the actuator,

homing repeatability, and targeting repeatability. Hysteresis tests the accuracy

with which the actuator returns to a target position, when approaching that target

position from opposite directions. Homing and targeting motions are those used

to move the collimator mirror to a particular absolute focus or angular position.

Collimator hysteresis and positioning repeatability must be accurate enough to

induce << 1.5 µm of image motion on the science detector. Lab tests demonstrate

that all three actuator performance characteristics meet this specification.

The collimator support frame was mounted onto an optical bench for the

actuator performance tests. A mirror was attached to the frame and the laser

beam reflected off the mirror and onto a lens and quad-cell detector. The lens

provides the same plate scale at the quad cell as in the MODS optics. One

actuator was motorized while the other two were held fixed for the tests. The

active actuator was equipped with a Renishaw 0.1 µm resolution encoder to provide

measurements of actuator linear position. See Figure 6.6 for the lab setup, and see

http://www.astronomy.ohio-state.edu/LBT/MODS for more details.

Tests of the actuator showed adequate resolution to make 0.05 pixel corrections

at the MODS detectors with no measurable motor backlash. There was some

measurable hysteresis which is likely due to mechanical effects (e.g., elastic wind-up),

but it amounts to no more than about 0.3 µm of linear actuator position error,

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equivalent to ∼0.04 pixels on the MODS CCD. See Figure 6.7 for the hysteresis test

plot.

Homing repeatability tests the accuracy of the actuator when moving to a

home position defined by the trip point of the inductive proximity switches used as

the home position datum. The measured homing repeatability is ±0.5 µm. Target

repeatability measures how well the actuator can move forward to a target position

from the home position using open loop control of the stepper motor. The target

repeatability was also within ±0.5 µm.

Optical misalignment of the instrument is one drawback of using the collimator

mirror to correct for image motion. Extensive simulations have been done of the

effect on the final optical quality after moving the collimator mirrors to compensate

for image motions. Even collimator vertex changes of 1000 µm and 15 microradians

(much larger than those that are needed for the IMCS) introduce negligible changes

in the image point-spread-function. The change in the D80 of the images, for

example, is <1%.

6.3. Description of Lab IMCS Tests

A prototype of the IMCS was set up on an optical bench in the lab in order

to test each component of the IMCS as well as to measure the performance of the

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complete system. These tests were done as preliminary work before installing the

IMCS in the MODS instrument.

6.3.1. Components of Lab Setup

The IMCS lab prototype is as similar to the IMCS that will be deployed with

MODS as possible. To that end, each component in the IMCS prototype is the

actual part that will be used in the MODS instrument except where noted below. It

is important to note that although the prototype IMCS is not physically the same

size as the final version of the IMCS (it would not fit on the lab optics bench), it does

preserve the angles, camera focal length, and final plate scale of the MODS IMCS.

This will minimize changes between the prototype and the system as deployed with

MODS. Figure 6.8 shows a photograph of the system as set up in the lab.

Lasers

The lasers described in Section 6.2 above were used in the lab tests. The laser

combination block was used to combine the infrared reference laser with the optical

alignment laser. The optical laser was used in the lab tests for alignment purposes

only; the tests described below were run using only the infrared laser.

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Collimator lens

The collimator lens in the IMCS prototype produces a collimated laser beam.

This lens in the prototype IMCS takes the place of the collimator mirror in MODS.

Fold prism/flat mirror

The collimated beam is reflected vertically by a 45-degree fold mirror onto a flat

mirror mounted on the bottom of the collimator cell. The angled mirror is oriented

such that it redirects the reflected beam toward the detectors. This arrangement

allows for two-dimensional correction of the reference beam by directing the laser

beam toward the collimator cell at right angles.

TTF motors/collimator structure

The flat mirror is mounted to the underside of the MODS collimator cell:

this is the actual cell that will be used in the MODS instrument to support the

collimator mirrors, although it will be used in a different orientation. The steel cell

incorporates three flexures each connected to stepper motor-driven linear stages,

allowing for three axes (tip, tilt, and focus) of motion. Note that in MODS this

collimator lens/fold mirror combination is replaced by the instrument’s collimator

mirror, which is mounted to the collimator cell and is moved by the TTF motors to

compensate for image motion. Refer to Section 6.2 for detailed performance data

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on the TTF actuators; see Figure 6.10 for a photograph of the orientation of this

structure in the lab prototype.

Camera lens

The camera lens focuses the collimated beam onto the detectors. Its focal

length is identical to that of the MODS camera. In MODS, this simple lens is

replaced by the Maksutov-Schmidt camera (Byard & O’Brien 2000).

Dichroic prism

Another dichroic (identical to that used in the laser combination block) divides

the infrared and visible laser light back into their respective beams, passing them

to the infrared quad cell and to a CCD camera. This prism will not be present in

MODS.

Neutral density filters

To control beam intensity at the quad cell and CCD, absorptive neutral density

filters are inserted into the beam directly in front of the detectors. These will not

be present in the final version of the IMCS, where the infrared laser power will

be adjusted to give the optimal signal level for the quad cell. The MODS camera

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includes a filter wheel with bypass holes made adjacent to each filter position through

which the infrared IMCS reference beam will pass.

Infrared quad cell

The lab tests of the IMCS use quad cell detector that will be used in the

on-instrument IMCS system. See Section 6.2 for a description of the quad cell

selected, and Figure 6.11 for a picture of the setup of the detectors in the lab.

CCD camera

A CCD camera is introduced into the prototype IMCS as a cross-check on

the image motion detected in the quad cell. The CCD was used in the lab to

confirm predicted calibrations of the system, as well as for alignment and inspection

purposes. There will be no CCD associated with the MODS IMCS.

A/D converters

Twelve-bit A/D converters read the output of the quad cell and relay the

signals to the motor control software.

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Motor control software

The lab motor control program reads the signals from the quad cell, calculates

the position of the reference beam on the quad cell, and computes the tip-tilt offset

moves required to re-center the reference beam on the quad cell. It then sends

this motion command to the TTF motors to null the offset, thus actively closing

the loop. In the final MODS implementation a more sophisticated program will

replace the simple BASIC program running in these lab tests. The lab prototype

IMCS samples the quad cell voltages and moves the motors every 2 seconds. This

bandwidth suffices for system tests; however, it is too slow to remove rapid image

motions such as those caused by air currents in the room (seeing).

6.3.2. System Tests

The prototype IMCS has been set up on an optics table in an interior lab

to avoid light contamination by outside sources. A thermostat with a cycle time

of about 30 minutes controls the temperature in the lab in which the tests were

run. The optics bench to which the lab IMCS was mounted suffered noticeable

temperature effects due to this ∼ 2 oC temperature variation in the room. In an

effort to control this room seeing cardboard tubes are placed on the lab bench,

through which the reference beam passed. This helped to control the problem to

some degree but in the end all of the lab tests have a small unavoidable temperature

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effect versus time. Fortunately, this relatively small-scale disturbance provided a

good test of IMCS performance.

Quad Cell Electronic Noise and Stability

It is important that each individual channel of the quad cell detector be stable

over time. Any instability will be counted as noise in the error budget. The quad

cell stability has been tested by looking at a fluorescent light source through a

diffuser. Figure 6.12 shows the data from this experiment. Each channel is stable

over about 2 hours to ∼0.001 mV, or an equivalent image motion of ∼0.2 µm. It

should be noted that although the quad cell output is a voltage these voltages have

been converted throughout this paper into equivalent microns of image motion. The

spot locations are measured by the quad cell, and are calculated from the output

voltages of the quad cell: “dx” is the sum of the two left quadrants minus the two

right quadrants divided by the sum of all four quadrants, “dy” is calculated similarly

with the top two and bottom two quadrants.

Small-scale Image Motion Compensation

The IMCS lab prototype compensates for image motion in two dimensions. One

axis of motion is simply obtained by attaching a TTF motor to the motor controller

that moves the collimator cell perpendicular to the tabletop (y-axis). The second

axis of motion (x-axis) is achieved by attaching the two remaining TTF motors to

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one motor controller, inverting the sign of one motor to produce negative motion

relative to the first. In the MODS instrument, the three axes will be controlled

independently with more sophisticated software so as to provide collimator mirror

focus in addition to tip and tilt. Since focus is not an issue in the prototype IMCS

this control mode is acceptable.

In the tests discussed below the prototype IMCS was required to correct for

varying scales of two-dimensional image motion. The tests were run with the

disturbance turned on for the duration of the experiment; the IMCS was only

turned on after ∼2 hours. This allows the test data to show the magnitude of the

disturbance as well as the degree to which the IMCS was able to correct for it.

The prototype IMCS functions for small disturbances. By allowing the room

temperature to vary as controlled by the thermostat in the lab, the small-scale

compensation abilities of the IMCS are tested. This produces image motions of

order 25 µm. Figure 6.13 shows the room temperature (as measured by a thermistor

placed on the optics bench), horizontal infrared reference spot location (dx) and

vertical spot location (dy).

Large-scale Image Motion Compensation

To obtain disturbances of the order expected in MODS when it is on the

telescope an additional disturbance is introduced in the form of a microscope slide

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rotating slowly in the beam. As the slide moves it translates the laser beam image

on the quad cell, accurately simulating flexure in the instrument in both magnitude

and rate. The slide produces ∼130 µm of image motion in a sawtooth pattern with

a time period of ∼1 hour. The slide is oriented at a 45-degree angle to the tabletop

producing image motion in both the x- and y-axes. Figure 6.14 shows the results of

these tests.

6.3.3. Results of Lab Tests

The prototype IMCS exceeds the specifications given above. The IMCS must

correct for both small- and large-scale image motions. In the small-scale tests (with

disturbances given by room temperature variations) the IMCS has compensated

for all of the ∼25 µm of image motion caused by the changing room temperature.

Specifically, in the region 2.2 to 3.2 hours after the test began the IMCS held the

laser spot at a constant location to ±0.45 µm (±1 σ) in both axes (x and y). During

this time the temperature in the room (for reasons unknown) varied by only ∼0.1

degrees/hour. After this time the room temperature was varying by ∼1 degree/hour

and the spot location was constant to 0.81 µm in the horizontal direction and

±0.70 µm in the vertical. The reason for this increase is being investigated, but it

is expected that the change was due to short-timescale fluctuations in the image

position (seeing) from air currents in the room generated by the HVAC system.

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It is important that the zero point of the image correction not drift over the

expected timescales of motion compensation. Once the IMCS was turned on, the

slope seen in the data in the horizontal direction was ∼0.014 µm/hour; in the vertical

direction the slope was ∼0.0005 µm/hour. This very small slope in both directions

is negligible.

The IMCS also corrects for large-scale motions. When the microscope slide

was introduced into the system, producing image motions 5 times as large as the

room temperature-induced disturbances, the IMCS held the laser spot at a constant

location to ±0.52 µm horizontally and ±0.59 µm vertically. Though the slide was

rotating for the duration of the experiment, there was little temperature variation in

the room during this time. Consequently, the effect of room seeing was minimized

in this test while the IMCS was turned on. With the rotating slide in the beam, the

slope seen in the data in the horizontal direction is ∼0.0081 µm/hour; in the vertical

direction the slope was ∼-0.025 µm/hour. Again, these small slopes are negligible.

The lab tests indicate that the IMCS works well. The system can null image

motions that approximate what is expected in MODS (i.e., ∼100 µm/hour) to

within <1 µm. This is well within our goal of 0.1 pixel stability and suggests that

the system is ready for installation into the spectrograph.

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6.4. On-Instrument IMCS and the IMCS as a Diagnostic

Tool

In this Section the on-instrument performance of the IMCS is described, in

particular the specific operational modes, the final system parameters, and the final

measured system performance of the IMCS. Additionally, the fortuitous usage of the

IMCS as a diagnostic tool to measure other instrument parameters and performance

metrics is discussed. Note that the tests presented in this paper have been done

on the blue channel of MODS1; similar results are expected for the red channel.

Figure 6.15 shows a photograph of the IMCS installed in the MODS instrument in

the OSU Astronomy Department instrument assembly area.

6.4.1. IMCS On-Instrument Performance

Performance: IMCS Spot Position vs. Time

The IMCS specification for operation is to hold the science spectrum steady

to 0.1 pixel (1.5 µm) over the typical science integration time of about one hour.

In Section 6.3 it is demonstrated that the lab IMCS met this goal: the lab IMCS

held simulated image motion steady to < 1.0 µm (±1 σ). The on-instrument IMCS

system performs nearly as well as the lab IMCS, most likely due to reduced seeing

effects in the on-instrument system as compared to the lab IMCS setup.

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The tests of the on-instrument IMCS are run on the MODS handling cart, a

fixture that holds the MODS instrument parallel to the floor (horizon-pointing), and

allows for instrument rotation from −20o to +73o (i.e., from pointing 20o above the

horizon to nearly upside-down). This setup allows for tests of the on-instrument

IMCS performance, but does introduce some noise. The primary source of noise is

introduced by the motor used to rotate the instrument on the cart: as the instrument

is rotated to the downward-looking direction, the system becomes more unbalanced

and more strain is placed on the motor. This causes a noticeable increase in the

noise pattern of the data, apparent in the last third of the data shown in Figure 6.16.

This will not be a problem once the instrument is mounted on the telescope.

Figure 6.16 shows a typical on-instrument IMCS test run. During this test the

instrument was rotated from −20o to +70o. This figure plots 10 points per second

with corrections made every 1 second based on the average of the previous 10 points.

A consequence of the way the commands to send to the collimator actuators

are computed is seen in the closed-loop X and Y positions shown in the top panel of

Figure 6.16. The linear nature of the residual, of opposite sign in X and Y, is directly

related to the derivative of the X or Y motion of the spot, which is proportional

to the speed at which the instrument is rotated. The test presented in Figure 6.16

is run at 17 times the sidereal rate, so the slope here is 17 times that expected

in normal use. When the instrument is rotated at the sidereal rate, this effect is

negligible.

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Figure 6.17 shows the seeing disk of the IMCS test run presented in Figure 6.16,

again plotting 10 points per second with corrections made every 1 second. The

size of the box in this figure is the size of one MODS 2x2 binned pixel (30 µm).

Noticeable outliers are observed, but are corrected for within one correction cycle (1

Hz). The RMS error of these data is 1.1 µm in the X direction and 1.3 µm in the Y

direction. The system performs within specifications in the lab.

The IMCS system installed on the MODS instrument performs to within the

specifications. Specifically, it controls image motion to about 1.2 µm (±1 σ) over

the equivalent of six hours of tracking at the sidereal rate. This result includes all

of the sources of error unique to the system as mounted on its cart in the lab. Even

though MODS instrument flexure is larger than expected (i.e., ∼300 µm/hour when

rotated at the sidereal rate, rather than ∼100 µm/hour; see Section 6.3), the system

still meets the performance specifications.

Differential Image Motion

The largest source of error in a closed-loop image motion nulling system such as

the on-instrument IMCS is differential image motion between the science beam and

the reference beam. Differential image motion may be introduced at any point at

which the two beams contact separate surfaces in one plane; however, in the MODS

instrument this happens relatively infrequently. Differential image motion might be

introduced in the focal plane by motion of the reference beam launch point with

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respect to the incoming science light. This concern has been addressed by creating

a very stable laser mount with a close structural connection to the instrument and

have epoxied the laser fiber into the combination block to eliminate reference beam

motion with respect to the launch optics. The grating assembly might introduce

differential motion between the science grating and the bypass grating. The bypass

grating has been kinematically referenced to the science grating to minimize this

motion. Finally, differential motion is eliminated in the detector plane by mounting

both the science and the quad cell detectors to a common mounting plate and

placing them both in a temperature-controlled environment. Consequently, negligible

differential image motion is expected between the science beam and the reference

beam inside the instrument.

6.4.2. The IMCS as a Diagnostic Tool

An important benefit of the IMCS is its utility in testing many aspects of

instrument performance, including elements that are not specifically part of the

IMCS itself. Because the IMCS uses the entire lightpath of the MODS instrument, it

may be used in open-loop mode (i.e., with the IMCS correction routine turned off) as

a diagnostic tool to test the stability of every optical element and associated optical

mounts and mechanisms in the instrument. Furthermore, the IMCS interface and

data-logging system provides a simpler interface than the science CCD, especially

for quick engineering tests.

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The IMCS, run in open-loop mode, may be used for any number of diagnostic

instrument tests within the MODS instrument. In particular, the open-loop IMCS

may be used to test the repeatability of the dichroic select mechanism, and the

collimator TTF actuator performance. It will also be used to test the grating select

turret repeatability, to look for hysteresis in the grating tilt mechanism, and to

measure image motion caused by the camera focus mechanism. The IMCS will

be able to measure the long-term stability of MODS, both in the lab and at the

telescope. Perhaps most importantly, the open-loop IMCS is an excellent tool to

measure the instrumental seeing, or the internal air stability within the MODS

instrument (with the dark slide closed). This will be an ideal tool when determining,

for example, whether a new electrical component has any thermal effect on the

internal environment of the instrument.

To give one example, the open-loop IMCS has been used to measure the

repeatability of positioning the grating select mechanism. By moving the imaging

flat in the grating turret into and out of the beam repeatedly, it is determined that

the grating select mechanism is repositionable with a random error of about 50

µm. More importantly, this demonstrates that the IMCS is a very useful tool to

accurately measure the performance of almost any MODS instrument mechanism in

the lab.

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6.5. Summary

The IMCS has been fully designed, prototyped in the lab, and installed in the

MODS instrument. It is an innovative new solution to the common problem of

flexure in instruments for large telescopes, and performs to within specifications.

The IMCS controls image motion to about 1.2 µm, or about as well as the lab version

of the IMCS. Even better performance is expected once the MODS instrument is

mounted on the LBT telescope. A complete MODS1 will be installed on the LBT in

late 2007; MODS2 should follow shortly thereafter.

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Fig. 6.1.— Schematic drawing of the IMCS system optics and components. Note:

figure is not to scale.

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Fig. 6.2.— Change in mean wavelength of laser emission versus temperature. The

laser output changes by 0.1 nm oC−1.

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Fig. 6.3.— Beam profile of the IMCS reference laser beam measured in the plane of

the bypass grating.

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Fig. 6.4.— Peak intensity vs. order number for the bypass grating. Nearly all of the

power is distributed in orders −13 through +13, with very little light contamination

between orders.

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Fig. 6.5.— Collimator mount and actuator schematic. A blowup of the actual motor

and stage arrangement is also shown.

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Fig. 6.6.— Lab test setup for tip/tilt/focus tests.

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Fig. 6.7.— Actuator hysteresis test data. One 15 micron pixel is equivalent to 0.0164

motor steps; the length of the y-axis is equivalent to about 1 pixel.

347

Fig. 6.8.— Photograph of prototype IMCS setup in the lab. Note that the prototype

IMCS is significantly smaller than it will be when deployed in MODS. Instead of

creating a full-size model, the prototype has been set up so that it preserves the

angles and plate scales in MODS, creating an accurate representation of the system.

348

Fig. 6.9.— Photograph of the laser combination block mounted to the optics bench.

The infrared and visible laser fibers are attached. The beam combining prism is

located beneath the surface shown.

349

Fig. 6.10.— Photograph of the collimator structure showing the TTF motors, the

collimator frame and cell with flexures, and the fold mirror. The collimator lens is

mounted to the optics bench beneath the collimator cell.

350

Fig. 6.11.— Photograph showing the beamsplitter, infrared quad cell, and CCD

detector, both with ND filters. The CCD is included in the prototype IMCS for

inspection purposes only, and will not be present in MODS.

351

Fig. 6.12.— Output of each quad cell channel voltage, as well as the equivalent

horizontal (dx) and vertical (dy) motions. The quad cell is aimed at a fluorescent

light source and a diffuser has been placed in front of all four quadrants. Some of the

noise in the data may be due to instability of the light source.

352

Fig. 6.13.— IMCS prototype performance for small-scale image motion due to

variations in room temperature. The test was run first with the IMCS off to

demonstrate the magnitude of the disturbance. The IMCS was then turned on,

compensating for the image motion. The dashed lines separate these two regions.

353

Fig. 6.14.— IMCS prototype performance for small- and large-scale image motions

due to both room temperature variation and beam displacement by a rotating

microscope slide. The reference beam displacement by the rotating slide simulates

the expected MODS instrument flexures in both magnitude and rate.

354

Fig. 6.15.— Photograph of the MODS1 instrument on its handling cart in the OSU

Astronomy Department instrument assembly area. The photograph shows the entire

MODS structure with all of the blue channel optics and mechanisms installed. The

instrument is rotated on the axis of its handling cart, and as pictured is pointed about

20o above the horizon.

355

closed-loop X positionclosed-loop Y position

open-loop X positionopen-loop Y position

Fig. 6.16.— Results of an IMCS rotation test, showing the instrument moving from

−20o to +70o (nearly horizon-pointing to nearly upside-down) in about 20 minutes.

The top panel shows the measured spot position on the quad cell; the lower panel

shows the spot position if the system were run in open-loop mode. The closed-loop

on-instrument IMCS controls image motion to about 1.2 µm, or less than 0.1 pixel

on the science detector.

356

Fig. 6.17.— The seeing disk of the IMCS test presented in Figure 6.16. The RMS error

of these points is 1.1 µm in X and 1.3 µm in Y. Note the slight diagonal elongation

of the disk, due to the slope errors discussed above.

357

Appendix A

Spectra of 319 Candidate Subdwarfs

The following pages show the spectra obtained as a part of this dissertation of

319 candidate metal-poor subdwarfs, as described in Chapter 3.

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