1. Atmospheric Neutrino Event Reconstruction Andy Blake Cambridge University June 2004

2. 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

3. This Talk Direction Reconstruction → Timing Resolution Charge Reconstruction → Separating / _

4. Direction Reconstruction

5. Up-Going Events Direction-Finding Algorithm: - consider distance vs time for track - force fits with β = ± 1 - calculate RMS about each fit - RMS down -RMS up > 0 for up-going tracks. up-going neutrinos UP-GOING EVENT !

6. MC/data Comparisons

7. Timing Resolution Timing resolution: Data = 2.75 ns MC = 2.40 ns RMS down for stopping muons: Try to understand this discrepancy: - refractive index - time walk - timing calibration

8. Refractive Index LmLm LpLp tmtm tptp t0t0 muon n reco =1.75 n data =1.82 n MC =1.73 Use double-ended strips on muon tracks:

9. Timing Calibration measured time difference - expected time difference between strips ends between strip ends define: Mean Δt tests goodness of calibration RMS Δt measures intrinsic timing resolution Use measured refractive indices

10. Timing Calibration ~3000 entries per plane September 2003 data Overall calibration good to <0.5 ns Poor calibration in last two crates Monte Carlo peaks at -0.3 ns (weird east-west asymmetry) Mean Δt ( → test calibration constants )

11. Timing Calibration September 2003 data MC slightly better than data. RMS Δt ( → measure intrinsic timing resolution ) Using n=1.82 instead of n=1.75 improves resolution by ~0.2 ns.

12. Time Walk Timing resolution depends on size of signal: RMS Δt (set Q m ≈ Q p )

13. Time Walk … but timing fits are charge-weighted so this effect gets suppressed. Signal rise time depends on size of signal:

14. Timing Resolution Monte Carlo : 2.4 ns 2.45 ns0.9 ns 0.25 ns2.45 ns 2.7 ns0.3 ns Data : Total resolution Intrinsic resolution Refractive index Calibration   = = Try to reproduce tracking resolutions by combining individual errors: use ΔL ~ 4m Time Walk 0.7 ns  0.5 ns 

15. Timing Drift ~5% degradation in 6 months

16. Timing Drift September 2003 data RMS Δt ( → intrinsic timing resolution ) 2% systematic variation across detector? Timing resolution per plane - SM1 slightly worse than SM2?

17. Timing Drift Current Timing Calibration: Overall calibration has degraded (~0.3 ns → ~0.4 ns) some structure + large displacements have developed.

18. Current Calibration Timing structure lines up with VARC + crate boundaries.

19. Current Calibration Large displacements are due to hardware changes. VFB swaps, VARC swaps, dynode threshold adjustments etc…

20. Up-Going Events Correlations between regions of poor calibration and up-going tracks ! 2.5 kT-yrs data PC up-going tracks after timing cuts

21. Up-Going Events Up-going candidate: planes 118 – 128 - real or badly calibrated ?

22. Up-Going Events Up-going candidate: planes 438 – 447 - real or badly calibrated ?

23. 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.

24. Charge Reconstruction

25. 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.

26. Charge Separation

27. Comparison with SR Compare: 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 better charge separation for AtNu

28. Comparison with SR AtNuSR AtNu89%90% SR84%86% FITTING TRACKING AtNu provides slightly better tracking for atmos nu events. SR provides slightly better fitting for atmos nu events. Look at all combinations :

29. Comparison with SR Charge separation in cosmic muons: AtNu better at lower energies SR better at higher energies

30. Comparison with SR

31. 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.