Atmospheric Neutrino Event Reconstruction
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Transcript of Atmospheric Neutrino Event Reconstruction
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Atmospheric Neutrino Event Reconstruction
Andy BlakeCambridge University
June 2004
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Introduction
Reconstruction- Track/shower finding- Track fitting (fast measurement of track curvature)
Analysis Modules- Raw Digit Dump. (raw digits, TPMT hits, dead chips etc…)- Cand Digit Dump. (positions, times, pulseheights, fibre lengths etc…)- Cand Track/Shower Dump. (track/shower parameters, analysis variables etc…)- Event Display.
Testing- Run over most of the data.- Used in Caius’ analysis.- Fast ( ~100 ms / event ).
AtNuReco
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This Talk
• Direction Reconstruction → Timing Resolution
• Charge Reconstruction → Separating /
_
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Direction Reconstruction
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Up-Going Events
Direction-Finding Algorithm:- consider distance vs time for track- force fits with β = ± 1- calculate RMS about each fit- RMSdown-RMSup > 0 for up-going tracks.
up-goingneutrinos
UP-GOING EVENT !
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MC/data Comparisons
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Timing Resolution
Timing resolution:
Data = 2.75 nsMC = 2.40 ns
RMSdown for stopping muons:
Try to understand this discrepancy: - refractive index - time walk - timing calibration
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Refractive Index
pmpm
p0p
m0m
LL nctct
nLctct
nLctct
Lm Lp
tm tp
t0 muon
nreco=1.75 ndata=1.82 nMC=1.73
Use double-ended strips on muon tracks:
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Timing Calibration
2
LLnctctΔt pmpm
measured time difference - expected time difference between strips ends between strip ends
define:
Mean Δt tests goodness of
calibration
RMS Δt measuresintrinsic timing
resolution
Use measured refractive indices
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Timing Calibration
~3000 entries per plane
September 2003 data
Overall calibration good to <0.5 ns
Poor calibration in last two crates
Monte Carlopeaks at -0.3 ns(weird east-west
asymmetry)
Mean Δt ( → test calibration constants )
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Timing Calibration
September 2003 data
MC slightlybetter than data.
RMS Δt ( → measure intrinsic timing resolution )
Using n=1.82 instead of n=1.75improves resolution by ~0.2 ns.
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Time Walk
Timing resolution depends on size of signal:
RMS Δt(set Qm ≈ Qp)
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Time Walk
… but timing fits are charge-weighted so this effect gets suppressed.
Signal rise time depends on size of signal:
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Timing Resolution
2cal
2PH
2
2222
trk ΔtΔtc
ΔLΔnΔtΔt
Monte Carlo : 2.4 ns
2.45 ns 0.9 ns
0.25 ns2.45 ns
2.7 ns 0.3 nsData :
Total resolution
Intrinsicresolution
Refractive index Calibration
=
=
Try to reproduce tracking resolutions by combining individual errors:
use ΔL ~ 4m
TimeWalk
0.7 ns
0.5 ns
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Timing Drift
~5% degradation in 6 months
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Timing Drift
September 2003 data
RMS Δt ( → intrinsic timing resolution )
2% systematic variation across detector?
Timing resolution per plane -SM1 slightly worse than SM2?
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Timing DriftCurrent Timing Calibration:
• Overall calibration has degraded (~0.3 ns → ~0.4 ns)• some structure + large displacements have developed.
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Current Calibration
• Timing structure lines up with VARC + crate boundaries.
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Current Calibration
• Large displacements are due to hardware changes.• VFB swaps, VARC swaps, dynode threshold adjustments etc…
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Up-Going Events
• Correlations between regions of poor calibration and up-going tracks !
2.5 kT-yrs data
PC up-going tracksafter timing cuts
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Up-Going EventsUp-going candidate: planes 118 – 128 - real or badly calibrated ?
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Up-Going EventsUp-going candidate: planes 438 – 447 - real or badly calibrated ?
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Conclusions• Far Det timing resolution is ~2.5ns - Monte Carlo and data agree to <5%. - Resolution in data degraded by calibration + larger time walk + choice of refractive index.
• Timing calibration vital for analysis of up-going atmospheric neutrinos.
- Calibration constants are drifting over time. - Hardware changes cause significant shifts. - Need to correct for these changes.
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Charge Reconstruction
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Charge Reconstruction
• Charge-Finding Algorithm:- need to measure curvature of muon track in magnetic field.- split track into overlapping 15 plane segments and parametrize each track segments using quadratic fit.- calculate Q/p and ΔQ/p for each segment.- combine the measurements to give an overall value for Q/p and ΔQ/p.
pQ
ks1.0
pQ
pQ
: k loss energy linear assuming
|Bp|0.3
Bpds
pd
CpQ
:charge give to rearrange
dsdp
pBp0.3Qds
pd
: by given momentum muon
0
2
loss
) 2.30.25
0.59correction gap airC
direction, track measuredp (
ˆ
ˆ
ˆˆ
ˆˆ
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Charge Separation
2.0ΔQ/PQ/P
for 90% exceeds separation theΔQ/PQ/P
usingout carried separation charge
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Comparison with SRCompare: SR tracker + SR fitter (total efficiency = 86%) AtNu tracker + AtNu fitter (total efficiency = 89%)
(atmos CC, >10 track planes, passed track fitter)
~20%
~30%slightly bettercharge separation
for AtNu
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Comparison with SR
AtNu SR
AtNu 89% 90%
SR 84% 86%
FITTING
TRACKING
AtNu providesslightly better tracking
for atmos nu events.
SR provides slightly better fittingfor atmos nu events.
Look at all combinations :
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Comparison with SRCharge separation in cosmic muons:
AtNu better at lower energies
SR better at higher energies
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Comparison with SR
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Conclusions
• AtNu charge reconstruction in good shape. - Algorithm is fast and robust. - Performs well at low energies, → ideal for FC atmospheric neutrino analysis. - Efficiency starts to drop away for E >20 GeV.
• Momentum from curvature good to ~30%. - plan to refine assumptions made in algorithm.