1

MINOS

and and ee Physics in MINOS Physics in MINOS

Antineutrinos Overview Oscillations Systematics

e AnalysisNearest neighbors selectionBackground estimations

Summary

Alex Himmel, Pedro Ochoa

2

MINOS

Approx. 6% of our beam is made of muon antineutrinos.

Unique advantage: both MINOS detectors are magnetized.Allows us to separate neutrinos and antineutrinos

on an event-by-event basis.

1x1020 POT

Amplified spectrum

v

Difficulty: not many events in osc. peak region

MC

Antineutrinos in MINOS

Difficulty: not many events in osc. peak region

ELmvvP

4

22sin22sin1)( Δ−=→ θ

with SK parameters

15 30 0 E (GeV)0

0.5

1

3

MINOS

Very interesting physics can be done with antineutrinos:

Very strong involvement of Caltech group in these areas.

oscillation analysis: A large CPT-violating region still unexplored

90%, 95%, 99% and 3σ CPT violating regions still allowed by global fit (except LSND)

M.C. Gonzalez-Garcia, M. Maltoni and T. Schwetz (hep-ph/0306226)

→ transitions: have never been looked for before in atmos sector.Some models beyond the SM predict them

(i.e. Langacker and Wang, Phys. Rev. D 58 093004). Could fully explain the atmospheric neutrino results

(Alexeyev and Volkova, hep ex/0504282) If 10% or more of neutrinos that disappear transition to

antineutrinos then we will see them.

Antineutrino physics

3) Measurement of Beam e’s: important for e analysis

4

MINOS

MINOS could distinguish between Δm223 and Δm2

23 at 90% C.L. if Δm2

23 > 0.004 eV2 in ~1 more year, during normal “neutrino” running

But if CPT is conserved, the reach of antineutrino oscillation analysis would be relatively small:

~3 first years of data (6x1020 POT)(no systematics included)

)2(sin 232 θ

223mΔ

Preliminary MC

90% Tentative exclusion limit

only valid for high mixing angle

90% 95% 99% 3σ

Antineutrino oscillations

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MINOS

These difficulties can be overcome with a small amount of reversed horn current running (RHC).

In this case negative particles from the target are focused thus yielding an antineutrino beam:

Forward horn current (FHC)

Reversed horn current (RHC)

Peak reduction due primarily to cross-section

difference ()

1x1020 POT 1x1020 POT

Antineutrino running

6

MINOS

Combining FHC with RHC can obtain a measurement of Δm2

23 that rivals the first MINOS measurement of Δm2

23:

90% C.L. 68.3% C.L.

6x1020 POT (FHC) +1x1020 POT (RHC)(no systematics)

223mΔ

Only ~4 months of antineutrino running (plus ~1 more year of normal running)

are needed !

This data would considerably reduce our best current limits on neutrino CPT

Effort led by Caltech

90% Tentative exclusion limit

90% 95% 99% 3σ

Preliminary MC

Antineutrino running

)2(sin 232 θ

7

MINOSAntineutrino systematics

Systematic errors are a crucial question in combining FHC and RHC data.

~30% of antineutrinos produced outside of the target region While neutrinos are also produced outside the target, they are

negligible compared to those focused from the target. A large fraction of the difference between the near and far

detectors comes from decay pipe antineutrinos.

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MINOSAntineutrino systematics

Uncertainties in the decay pipe modeling could affect the far/near ratio creating a false signal.

Toy systematic model: 50% Scaling of the decay pipe componentThe other components of the flux unchanged

Preliminary results suggest that the effect is small compared to the expected statistical error at 1x1021 POT.

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MINOS

FluggNew Monte CarloOld Monte Carlo

Beam systematics

Working to update the beam Monte Carlo from Geant3 to Geant4.

Use Flugg to run the new geometry in Fluka, a more trusted physics simulation

Geant-Fluka Physics

Geant 4 Physics

FluggGeant 3

GeometryGeant 4

Geometry

Fluka Geometry

Fluka Physics

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MINOSMuon Scattering

Study shows Geant4 greatly overestimates the data, especially at lower muon momenta.

How well does Geant4 model multiple scattering? Compared Geant4 and some IHEP data (1986) of muons on

a Cu target.

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MINOSMuon Chopper

Another technique for assessing systematics associated with charge separation was developed at Caltech:

1) Identify stopping muons at the ND:

2) Remove everything but the last x GeV’s of energy:

3) Run reconstruction over muon chopped data and MC

4) Calculate ID efficiency & purity in data & MC for different values of x.

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MINOSMuon Chopper

The following sources of systematics are addressed by the Muon Chopper:

1) Magnetic field2) Multiple scattering3) Reconstruction / Backgrounds

Preliminary results indicate charge separation is reasonably well modeled by the MC:

@900 MeV

Data MC

P(-|μ-) %70.1±0.

265.8±0.

5

P(+|μ-) %

3.0±0.1 3.4±0.2

P(?|μ-) %25.5±0.

229.6±0.

5< 10% systematic in purity !

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MINOS

E

LmvvP e 4

sinsin2sin)(2232

232

132 Δ

≅→ θθ At MINOS’ baseline of 735 km,

Expect ~14 e CC events (E<10

GeV) appearing in the MINOS Far Detector for every 1x1020

POT of data if θ13 is at CHOOZ

limit

e Appearance

At Caltech concentrating on:

developing the best possible e selection

measuring two of the main backgrounds.

Main challenge at MINOS consists in distinguishing between EM and hadronic showers.

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MINOS

For analysis need to have as good e selection as possible to

maximize signal.

Have been working on a nearest neighbors selection in collaboration with Cambridge University.

Most available selections use multivariate techniques that rely on reconstructed quantities.

But this analysis is a special case:

Number of reco variables ~ number of strips in event

Compare each input event to large libraries of simulated

e CC and NC events. Select N best matches

Basic idea:

Why not perform event ID using strip information alone?

Construct discriminant from N best matches information

(e.g. fracCC=fraction of N best matches which are e CC)

Nearest Neighbors Selection

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MINOS

Advantages:

Approach is in principle optimal. No loss of info from raw→reconstructed quantities

Largely reconstruction-free.

But only optimal if fully sample phase space

Need large libraries (~50-100 Million events of each type). So far have generated ~50 Million events at Caltech.

Determine how well two events match by asking:

( ) ( )∑∑∫∞

=pl st

dnPnP0

21 ,, λλλl

Poisson

“what is probability the two events come from same hit pattern at PMTs?”

Nearest Neighbors Selection

plane #

plane #plane #

plane #

Str

ip #

Str

ip #

Str

ip #

Str

ip #

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MINOS

Example of discriminant:

fracCC(y<0.5)=fraction of 20 best matches that were e with y<0.5

Already provides the best significance !

Information of N best matches is very rich:

Plenty of room for further improvement !

Library size:~1M e

~1.5M NC

NCCC e

Good separation

Nearest Neighbors Selection

datamcncνe

νμcc

Currently working hard to get selection fully operational in the Near Detector:

Using different background estimating techniques to understand data-MC discrepancy.

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MINOS

FD Performance

Selected events:

Sensitivity limited by statistical fluctuations of background.

Define figure of merit FOM=Signal/√Background

For 0 < Ereco < 6 GeV:

FOM=2.29

Our selection already has a FOM at least 15% higher than all the other selection methods.

sin2(2θ13) = 0.1, |Δm31|2 = 2.710-3eV2, sin2(2θ23) = 1, POT=4x1020

cut

Note: preselection includedPreliminary MC

CC e NC CC CC Beam e

7.98 6.98 2.20 0.97 2.00

antineutrinos muon removal

2 methods for addressing background have been developed at Caltech.

Library size:5M e

10M NC

~end of 2007

Selected events:

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MINOS

Apply muon removal (MR) to both data and MC

Apply e selection on both. Use differences in both samples to reweight the NC expectation

in the e analysis.

Use Muon Removal (MR) to assess the NC Background:

ND databefore MR

after MR

(NN selected events)

MCMCMR

DATAMR NN

NN =

# of NC events in e analysis

# of e candidates in MR data

# of e candidates in MR MC

# of e candidates that are NC in MC

MR reweighting removed the ~60% overall normalization discrepancy

NC Background

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MINOS

Need to tag antineutrinos coming from + decay. Use fact that antineutrino spectrum is practically the same independently of the beam configuration:

Irreducible background in e analysis: intrinsic beam e‘s

Nearly all come from +→ e+ + e +

Low energy (LE) pseudo-medium energy (pME) pseudo-high energy (pHE)

MC MCMC

Most antineutrino parents just go

through the center of both

horns

Beam e’s from antineutrinos

Work led by Caltech, in collaboration with BNL

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MINOS

Only + component changes significantly when running in pME or pHE !The Technique:

Scale pME (or pHE) and LE data to same POT and take the difference

from +

pME

parME×

from +

LE

parLE×

(pME-LE)TRUE at 1e18 POT

Fit with using shapes from the MC:

Corrections due to differences in the

antineutrinos from and K-

Expected sensitivity:

Sensitivity to beam e’s

Using 2.5x1019 POT of pME data 27%

Using 1.6x1019 POT of pHE data 25 - 30%

pHE data already taken!

Beam e’s from antineutrinos

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MINOS

The CHOOZ limit will be reached by end of 2007

Expect 1st MINOS e appearance result by

next year.

Summary & Ongoing Work

Very positive outlook. Working hard to:

Further improve selection Assess systematics.

Critical role played by Caltech group in these two areas.

e appearance:

Antineutrinos: Only ~4 months of antineutrino running are needed to make a

measurement of Δm223 with a precision that rivals the first MINOS

Δm223 result.

Will search for → transitions for the first time. Developing tools for beamline simulation.

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MINOS

Backup

23

MINOS

steel thickness: 2.54cm | strip width: 4.12cm (Molière radius ~3.7cm)

short event, often diffuse

1.8m

νμ CC Event NC Event νe CC Event

long μ track & hadronic activity at vertex

3.5m

short, with typical EM shower profile

2.3m

(MC)

e Appearance in MINOS Challenge: At MINOS, we lack the granularity to fully resolve

hadronic vs. EM showers:

n p

-

p p

W WZ

n p

e e-