1. CC analysis progress This talk: –A first attempt at calculating CC energy sensitivity using the Far Mock data MC files with full reconstruction. –Quite a few changes from Five year plan plots: “Real” events used rather than fast MC with histogrammed flux and y distributiuons Reconstructed track and shower energies used rather than Gaussian-distribution resolution functions Nuclear effects accounted for including intranuclear re- scattering Neugen 3 used with flatter y-distribution –This analysis is not optimised yet – should be able to improve energy resolution and event selection efficiencies D.A. Petyt June 2004

2. Event ID – PDFs (top row – CC, bottom row – NC) Require that all events contain at least 1 reconstructed track Event length (planes) Track p.h./event p.h track p.h./plane (siglin ADC)

3. Event ID – PID parameter NC CC

4. Selection efficiencies Cut here Event reconstruction efficiencies are included in these numbers

5. CC efficiencies – Reco and PID chain Should be better in R1.8 First 5 efficiency plots are sequential, last plot is cumulative

6. Energy reconstruction E reco =E   E had Use track fitter to provide muon momentum: range for contained tracks, 1/(q/p) for exiting tracks (min 3m track length) How to estimate E had ? –Test some ideas on NC events: E had = Shower ph*scale factor? E had = Event ph * scale factor –Using event ph works better: ph/GeV distribution has 15% higher mean and narrower width True NC events Number of reco tracks and showers Fraction of event p.h. in reco shower(s) Shower p.h./E had (siglin ADC units) Event p.h./E had (siglin ADC units)

7. Showers in CC events Attempt to use same algorithm to estimate shower energies in CC events Must account for pulse height contribution of muon track in shower region. Can’t use SR trk.ph.siglin, as this includes shower ph for strips in which tracks and showers overlap Estimate track pulse height as trk.ndigit*295, where scaling factor is determined from long muons Subtract estimated track p.h. from event ph to yield shower energy Scaling factor obtained: 10500 siglin ADC/GeV True CC events Numerator: shw p.h. Denominator: event ph – estimated track ph. Shower p.h./E had (siglin ADC units) Estimated shower p.h./E had (siglin ADC units)

8. Resolution functions Asymmetric tails caused by shower fluctuations Small negative bias. Tails mostly due to q/p errors All (reco-true)/true

9. P  reconstructed high - Exiting muon with little or no curvature

10. P  reconstructed high - Exiting muon with kink

11. E had reconstructed high – high ph digits

12. E had reconstructed high – lego plot of snarl 81

13. Comparison of true and reconstructed E spectra True CC events True NC events Identified CC-like events: PID >-0.3 True Reconstructed

14. Energy spectra and spectrum ratios Unoscillated NC Oscillated Identified CC-like events:  m 2 =0.002, sin 2 2  =1, scaled to 16e20 p.o.t No NC subtraction in ratio plot

15. Unoscillated NC Oscillated Identified CC-like events:  m 2 =0.002, sin 2 2  =1, scaled to 16e20 p.o.t Energy spectra and spectrum ratios NC contribution subtracted with 20% error

16. Allowed regions  m 2 =0.002 eV 2, sin 2 2  =1, 16e20 p.o.t “Rise” in spectrum ratio not seen here

17. Allowed regions - 2  m 2 =0.00295 eV 2, sin 2 2  =1, 16e20 p.o.t “Rise” in spectrum ratio is observed here

18. Comparison of old and new 5 year plan analysis

19. Comparison of old and new This analysis

20. What happened to the low energy rise? I can think of 4 likely reasons: Energy smearing due to nuclear/mass/pion absorption effects in NEUGEN. Already saw some evidence of this when I compared toy MC event generator with NEUGEN last June

21. Additional smearing caused by non-Gaussian tails in resolution functions. Andy Culling’s E had method should help here Toy MC used a binned FarDet energy spectrum with linear interpolation between bins. Will tend to over-estimate event rate in lowest energy (0-1 GeV) bin Track finding efficiency is lower, especially at low E What happened to the low energy rise?

22. Track finding efficiency, old and new Track finding efficiency is much higher in the old ntuple. I suspect that this is because the reconstruction was configured with cosmic parameters which contain much looser cuts on what constitutues a “track” plane. Tracks are also found in most NC events, but these can be suppressed with the PID cut. “NEW” efficiency is set to improve with R1.8 (low p  tuning by Niki, bug fixes by Jim) Old (NEUGEN2) MC file, tracker run with cosmic mu parameters? Mock Data MC files, tracker run with R1.7

23. QEL p  distribution All events Reco track PID cut How many of these can we recover?

24. What next? Re-do analysis with R1.8, which will contain a number of reco improvements. How much does this help? Look into incorporating Andy Culling’s E had prescription to improve shower energy resolution Look at events that do not have a reconstructed track. Are there usable CC events in this sample? How can we extract them?