1. CC ANALYSIS STUDIES Andy Blake Cambridge University Fermilab, September 2006

2. Overview Andy Blake, Cambridge UniversityCC talk, slide 2 Have started to look at some CC analysis issues. – Validation of R1.24. – Study the current reconstruction + analysis. Long term goal is to optimize the measurement of sin 2 2  23. – Need to accurately resolve the size of the oscillation dip. – Need a clean event sample. (good CC/NC separation, good energy resolution, few reconstruction errors etc…) This talk is divided into the following topics: (I) energy reconstruction. (II) CC/NC separation.

3. Data Selection Andy Blake, Cambridge UniversityCC talk, slide 3 Far Detector beam Monte Carlo SR ntuples (R1.24c). ~75,000 beam events. Apply simple pre-selection to reconstructed events: 1 event per snarl (avoid split events for now). >10 digits per event (below tracking threshold). signature of  CC interaction is reconstructed track. Define fiducial volume: 50 cm from edge of detector. 40 cm from centre of coil hole. 5 planes from beginning of detector 5 planes either side of super-module gap. 20 planes from end of detector.

4. (I) Energy Reconstruction

5. Event Reconstruction Andy Blake, Cambridge UniversityCC talk, slide 5 Muon Reconstruction: Define longest track to be primary track. FC events: both vertex and end inside fiducial volume. use momentum from range. PC events: vertex inside fiducial volume. end not inside fiducial volume. use momentum from curvature. Shower Reconstruction: Collect up all sub-showers close to the event vertex. Add in unassigned strips not along primary track. Neutrino Energy: neutrino energy = muon momentum + shower energy.

6. Shower Reconstruction Andy Blake, Cambridge UniversityCC talk, slide 6 associated with hadronic shower associated with muon track a sub-shower is associated with vertex shower if: Z shw -Z evt 0.5 GeV OR shower not on track.

7. Shower Reconstruction an unassigned strips are associated with vertex shower if: PH east +PH west >200 ADCs AND strips not adjacent to track. ( Approximate 10,000 SigCor ~ 1 GeV for these strips). Andy Blake, Cambridge UniversityCC talk, slide 7

8. Reconstruction Efficiencies Andy Blake, Cambridge UniversityCC talk, slide 8 MUON TRACK RECONSTRUCTIONSHOWER RECONSTRUCTION # events with tracks # events efficiency = # events with shower energy # events with tracks efficiency = Reconstruction efficiencies for  CC events (true vertex inside fiducial volume):

9. Reconstruction Efficiencies Event (1) P  = 500 MeV Event (2) P  = 500 MeV Event (3) P  = 700 MeVEvent (4) P  = 600 MeV Examples of  CC events without reconstructed tracks: blue line = true muon direction

10. Muon Momentum From Range Andy Blake, Cambridge UniversityCC talk, slide 10 0-1 GeV 1-2 GeV 2-3 GeV 3-4 GeV 4-5 GeV bias towards high energies due to track reconstruction (N.B: used to be much worse!) bias towards low energies due to track containment and showers at end of track. momentum reconstruction consistent with ~5% error. reco - true muon momentum for 1 GeV wide bins: MUON MOMENTUM FROM RANGE

11. Muon Momentum From Range R1.18.2R1.24c The bias at low muon energies has always existed! Caused by over-tracking and/or mis-tracking (track finder prefers longer tracks) Bias is reduced by the introduction of the new track finder in R1.24c. Bias is worse in shower-like events, so will be correlated with PID parameter. Andy Blake, Cambridge UniversityCC talk, slide 11

12. Muon Momentum from Range Andy Blake, Cambridge UniversityCC talk, slide 12 true muon direction = blue line (3) wrong track picked(4) wrong track picked (2) track extended past vertex(1) track deviates off course

13. Muon Momentum from Curvature Andy Blake, Cambridge UniversityCC talk, slide 13 0-1 GeV 1-2 GeV 2-3 GeV 3-4 GeV 4-5 GeV reco - true muon momentum for 1 GeV wide bins: MUON MOMENTUM FROM CURVATURE Muon momentum resolution is ~ 10-20%, but there are low/high energy tails

14. Muon Momentum from Curvature Feed down of high energy neutrinos into low energy bins: Andy Blake, Cambridge UniversityCC talk, slide 14 PC events with: P reco < 3 GeV Out-lying tail of high energy muons reconstructed with a low energy (true muon momentum)

15. Muon Momentum from Curvature Andy Blake, Cambridge UniversityCC talk, slide 15 (1) (2)(3) Feed down of high energy neutrinos into low energy bins for PC events: P true = 9.9 GeV P reco = 0.5 ± 0.1 GeV P true = 8.4 GeV P reco = 1.8 ± 0.8 GeV P true = 14.3 GeV P reco = 1.5 ± 0.5 GeV

16. Shower Energy Andy Blake, Cambridge UniversityCC talk, slide 16 0-1 GeV 1-2 GeV 2-3 GeV 3-4 GeV 4-5 GeV Reconstructed energy peaks in correct place and resolution is consistent with 55%/√E reco - true shower energy for 1 GeV wide energy bins: RECONSTRUCTED SHOWER ENERGY

17. Neutrino Energy Andy Blake, Cambridge UniversityCC talk, slide 17 0-1 GeV 1-2 GeV 2-3 GeV3-4 GeV 4-5 GeV RECONSTRUCTED NEUTRINO ENERGY reco - true neutrino energy for 1 GeV wide energy bins:

18. Neutrino Energy Andy Blake, Cambridge UniversityCC talk, slide 18 R1.24c R1.18.2

19. Neutrino Energy Andy Blake, Cambridge UniversityCC talk, slide 19 Look at feed down of high energy neutrinos into low energy bins: All events with E reco < 3 GeV The feed down from high energy PC events well below 1% level.

20. Energy Resolution Andy Blake, Cambridge UniversityCC talk, slide 20 FC events:  E = 5% P   55%/√E shw PC events:  E =  q/p /(q/p) 2  55%/√E shw define an approximate resolution function for FC and PC  CC events: FC PC

21. Neutrino Energy Resolution Andy Blake, Cambridge UniversityCC talk, slide 21 Divide up events by estimated neutrino energy resolution:

22. Energy Resolution Andy Blake, Cambridge UniversityCC talk, slide 22  E /E < 15%15% <  E /E < 30% 30% <  E /E < 60%  E /E > 60% oscillations close to zero!  m 2 = 2.74 eV 2 sin 2 2  = 1.0 Note: NC background not included!

23. (II) CC/NC Separation

24. CC/NC Separation (1) Andy Blake, Cambridge UniversityCC talk, slide 24 Start with standard PID variables. Track PlanesTrack PH / Event PHTrack PH / Track Planes CC NC

25. CC/NC Separation (1) Andy Blake, Cambridge UniversityCC talk, slide 25 100% CC entries Form the PID using standard prescription: CC NC

26. CC/NC Separation (1) Andy Blake, Cambridge UniversityCC talk, slide 26 3 variables PID = - 0.2

27. CC/NC Separation (2) Andy Blake, Cambridge UniversityCC talk, slide 27 “Track-like” planes (number of planes with little shower activity) Error in track fit | Q/p | /  Q/p (test of consistency with muon track fit) CC NC Choose some additional variables: (i) Reasonable physics motivation. (ii) Good separation of CC and NC events. (iii) Fairly similar in Near and Far Detector (e.g. can’t use timing). 50 planes CC NC

28. CC/NC Separation (2) Andy Blake, Cambridge UniversityCC talk, slide 28 5 variables 3 variables PID = - 0.2

29. CC/NC Separation (3) Divide up PID distributions by track length. (i) track planes < 25 (ii) 25 < track planes < 50 (iii) track planes > 50 Use the difference in the shape of the PID distributions as a function of track length to enhance the CC/NC separation at low neutrino energies. (i) ~100% of tracks with >50 planes are CC events. (ii) distributions of track PH / event PH change markedly for short tracks. (iii) track-like planes + fit error provide some separation at low energies. Andy Blake, Cambridge UniversityCC talk, slide 29

30. CC/NC Separation (3) Andy Blake, Cambridge UniversityCC talk, slide 30 CCNC separation from pulse height has almost all gone PID variables for muon tracks spanning less than 25 planes: Some separation from track-like planes some separation from track curvature

31. CC/NC Separation (3) Andy Blake, Cambridge UniversityCC talk, slide 31 5 variables 3 variables 5 variables + separation by event length PID = - 0.2 Events with: E reco < 3 GeV

32. Summary Andy Blake, Cambridge UniversityCC talk, slide 32 Reconstruction appears to be in pretty good shape. – Energy reconstruction is accurate with good resolution. – Some small problems and biases, but very hard to handle. – Only a small number of outlying events fall into oscillation region. Oscillation dip is better resolved by dividing events by resolution. – This may improve the measurement of sin 2 2  23. Some improvement possible in CC/NC separation. – ~10% improvement in selection efficiency at low energies. Lots more work for me to do!