spectral modeling and diagnostics in various astrophysical environments

33
Spectral modeling and diagnostics in various astrophysical environments Jelle Kaastra SRON

Upload: hertz

Post on 13-Jan-2016

29 views

Category:

Documents


0 download

DESCRIPTION

Spectral modeling and diagnostics in various astrophysical environments. Jelle Kaastra SRON. Topics. Multi- temperature structure Resonance scattering in groups of galaxies Foreground absorption Photoionised outflows from AGN Several examples using SPEX (www.sron.nl/ spex ). - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Spectral modeling and diagnostics in various astrophysical environments

Spectral modeling and diagnostics in various

astrophysical environmentsJelle Kaastra

SRON

Page 2: Spectral modeling and diagnostics in various astrophysical environments

Topics

• Multi-temperature structure

• Resonance scattering in groups of galaxies

• Foreground absorption

• Photoionised outflows from AGN

Several examples using SPEX

(www.sron.nl/spex)

2

Page 3: Spectral modeling and diagnostics in various astrophysical environments

I. Multi-temperature structure

A warning against over-simplification

3

Page 4: Spectral modeling and diagnostics in various astrophysical environments

4

The Fe bias

• 1T models sometimes too simple: e.g. in cool cores

• Using 1T gives biased abundances (“Fe-bias, Buote 2000)

• Example: core M87 (Molendi & Gastaldello 2001)

Multi-T 1T

Page 5: Spectral modeling and diagnostics in various astrophysical environments

5

Complex temperature structure I(de Plaa et al. 2006)

• Sérsic 159-3, central 4 arcmin

• Better fits 1Twdemgdem

• Implication for Fe: 0.360.350.24

• Implication for O: 0.360.300.19

Page 6: Spectral modeling and diagnostics in various astrophysical environments

6

Inverse iron bias: how does it work?

• Simulation: 2 comp, T=2 & T=4 keV, equal emission measure

• Best fit 1-T gives T=2.68 keV

• Fitted Fe abundance 11 % too high

• Due to different emissivity for Fe-L, Fe-K

Page 7: Spectral modeling and diagnostics in various astrophysical environments

7

Complex temperature structure II(Simionescu et al. 2008)

• Example: Hydra A• Central 3 arcmin:• Full spectrum: Gaussian

in log T (σ=0.2)• 1T fits individual regions:

also Gaussian• Confirmed by DEM

analysis (blue & purple)

Page 8: Spectral modeling and diagnostics in various astrophysical environments

II Resonance scattering in groups of galaxies

The importance of accurate atomic data

(Fe XVII)

8

Page 9: Spectral modeling and diagnostics in various astrophysical environments

Resonance scattering & turbulence

9

Page 10: Spectral modeling and diagnostics in various astrophysical environments

Resonance scattering(NGC 5813, de Plaa et al. 2012)

10

Page 11: Spectral modeling and diagnostics in various astrophysical environments

Measured and predicted line ratios(de Plaa et al. 2012)

11

Page 12: Spectral modeling and diagnostics in various astrophysical environments

Results

• NGC 5813:

vturb = 140-540 km/s (15-45% of pressure)

• NGC 5044:

vturb >320 km/s (> 40% turbulence)

12

Page 13: Spectral modeling and diagnostics in various astrophysical environments

III Foreground absorption

Nasty correction factors are interesting!

13

Page 14: Spectral modeling and diagnostics in various astrophysical environments

Interstellar X-ray absorption

• High-quality RGS spectrum X-ray binary GS1826-238 (Pinto et al. 2010)

• ISM modeled here with pure cold gas

• Poor fit

14

Page 15: Spectral modeling and diagnostics in various astrophysical environments

Adding warm+hot gas, dust

15

Adding warm & hot gas

Adding dust

Page 16: Spectral modeling and diagnostics in various astrophysical environments

Oxygen complexity

16

Page 17: Spectral modeling and diagnostics in various astrophysical environments

Interstellar dust

• SPEX (www.sron.nl/spex)

currently has 51 molecules with fine structure near K- & L-edges

• Database still growing (literature, experiments; Costantini & De Vries)

• Example: near O-edge (Costantini et al. 2012)

1722 Ang 23.7 Ang

Tra

nsm

issi

on

Page 18: Spectral modeling and diagnostics in various astrophysical environments

Absorption edges: more on dust• optimal view O & Fe• Fe 90%, O 20% in dust

(Mg-rich silicates rather than Fe-rich: Mg:Fe 2:1 in silicates)

• Metallic iron + traces oxydes

• Shown: 4U1820-30, (Costantini et al. 2012)

Page 19: Spectral modeling and diagnostics in various astrophysical environments

Are we detecting GEMS?GEMS= glass with embedded metal & sulphides

(e.g. Bradley et al. 2004)

interplanetary origin, but some have ISM origin

invoked as prototype of a classical silicate

Mg silicate Metallic iron

FeS

Crystal olivine, pyroxeneWith Mg

Glassy structure +FeS

Cosmic rays+radiation

Sulfur evaporation GEMS

Page 20: Spectral modeling and diagnostics in various astrophysical environments

IV Photoionised outflows from AGN

The need for complete models

and excellent data

20

Page 21: Spectral modeling and diagnostics in various astrophysical environments

Why study AGN outflows?

21

Accretion

Outflows

• Feeding the monster: delicate balance between inflow & outflow onto supermassive black hole

• Co-evolution of black hole & host galaxy

• Key to understand galaxy formation

Page 22: Spectral modeling and diagnostics in various astrophysical environments

Main questions outflows

• What is the physical state of the gas? – Uniform density clouds in

pressure equilibrium?– Or like coronal streamers, lateral

density stratification?

• Where is the gas?– Where is it launched? Disk, torus?

– Mass loss, Lkin depend on r

– Important for feedback

22

Page 23: Spectral modeling and diagnostics in various astrophysical environments

23

Observation campaign Mrk 509(Kaastra et al. 2011)

• Monitoring campaign covering 100 days• Excellent 600 ks time-averaged spectrum• Observatories involved:

– XMM-Newton (UV, X-ray)– INTEGRAL (hard X-ray)– HST/COS (UV)– Swift (monitoring)– Chandra (softest X-rays)– 2 ground-based telescopes

Page 24: Spectral modeling and diagnostics in various astrophysical environments

Sample spectraRGS 600 ks, Detmers et al. 2011 (paper III)

24

Page 25: Spectral modeling and diagnostics in various astrophysical environments

Absorption Measure Distribution

25

Ionisation parameter ξ

Em

issi

on m

easu

re

Col

umn

dens

ity Discrete components

Continuousdistribution

Temperature

Page 26: Spectral modeling and diagnostics in various astrophysical environments

Discrete ionisation components?Detmers et al. 2011

• Fitting RGS spectrum with 5 discrete absorber components (A-E)

26

Page 27: Spectral modeling and diagnostics in various astrophysical environments

27

Continuous AMD model?Detmers et al. 2011

• Fit columns with continuous (spline) model

• C & D discrete components!

• FWHM <35% & <80%• B (& A) too poor statistics

to prove if continuous• E harder determined:

correlation ξ & NH

Discrete components

C

D

B

E

Page 28: Spectral modeling and diagnostics in various astrophysical environments

Pressure equilibrium? No!

28

Pressure Pressure

Tem

pera

ture

Page 29: Spectral modeling and diagnostics in various astrophysical environments

Differences photo-ionisation models

29

Page 30: Spectral modeling and diagnostics in various astrophysical environments

30

Density estimates: reverberation

• If L increases for gas at fixed n and r, then ξ=L/nr² increases

change in ionisation balance ionic column density changes transmission changes• Gas has finite ionisation/recombination

time tr (density dependent as ~1/n) measuring delayed response yields

trnr

Page 31: Spectral modeling and diagnostics in various astrophysical environments

Time-dependent calculation

31

Hard X

Soft X

Total

Page 32: Spectral modeling and diagnostics in various astrophysical environments

Results: where is the outflow?(Kaastra et al. 2012)

32

Page 33: Spectral modeling and diagnostics in various astrophysical environments

Conclusions

• We showed 4 examples of different & challenging astrophysical modeling

• All depend on availability reliable atomic data

• The SPEX code (www.sron.nl/spex) allows to do this spectral modeling & fitting

• Code & its applications continuing development (since start 1970 by Mewe)

33