1. Atmospheric Neutrino Event Reconstruction Andy Blake Cambridge University September 2003

2. Introduction Cambridge reconstruction software development is ongoing. New version of AtNuReco now in CVS. AtNuReco is a track + shower reconstruction package developed for use in atmos neutrino analysis. tracks + showers reconstructed concurrently. This talk presents a study of atmos neutrino reconstruction and separation.

3. Monte Carlo Studies 200,000 atmos neutrino events (~500 kT-yrs) 200,000 cosmic muon events (~0.05 kT-yrs) Study reconstruction efficiency/purity + signal/background separation. DetSim Cambridge Demultiplexer Cambridge Reconstruction Standard Reconstruction Analysis

4. Reconstruction Efficiency/Purity

5. Reconstruction Quality Problems arise from tracking errors + NC/ν e background Define track “quality” Poor tracks occupy phase spaces away from good tracks Make pre-cuts (also helps background rejection) C u t

6. Efficiency/Purity after Pre-cuts efficiency purity

7. Signal/Background Separation Can use track information to separate signal from background. Signal and background occupy separate regions of phase space. … e.g. cosmic muon events are downward-going, high angle, close to detector edge. Signal can be separated from background by cutting away these regions. Use likelihood to define a multi- dimensional threshold between signal and background. Try calculating likelihood from many 1D PDFs. (e.g. muon zenith angle) signal background

8. 1D PDFs Background Signal Rcos θ track direction

9. Likelihood calculation Cambridge ReconstructionStandard Reconstruction N cosmic /N atmos = 15,000 ( BUT VETO SHIELD IGNORED IN THIS NORMALIZATION ) zoomed in to see tails …

10. Results AtNuSR 100,000 48,600 15,10025,500 11,30013,000 6,9006,800 AtNuSR 100,000 60,700 49,00053,400 35,30037,000 25 atmos nucosmic mu Interactions Triggers Tracks Pre-cuts Signal (L>0.5) … but 4 reconstructed as upward-going …

11. Contained Background Events Cambridge ReconstructionStandard Reconstruction contained rejected

12. Signal Efficiency Some signal events are retained in all 1D phase spaces. Rcos θ track direction heavy loss of downward-going events (reduced by improving likelihood, fixing reco errors, using veto shield in normalization) very good with upward-going partially contained events (should also use vertex shower info)

13. Problems (1)1D projections ignore correlations between variables. (2)Reconstruction errors pollute the signal region. Cambridge ReconstructionStandard Reconstruction

14. Combining Reconstruction Algorithms Reconstruction algorithms with contrasting systematics can be combined to enhance separation. Try using AtNu AND SR to filter signal … AtNuSR 100,000 48,600 15,10025,500 11,30013,000 6,9006,800 AtNuSR 100,000 60,700 49,00053,400 35,30037,000 25 Interactions Triggers Tracks Precuts Signal AND 100,000 60,700 48,900 34,200 0 AND 100,000 48,600 15,000 9,800 4,200 atmos nucosmic mu … for this sample, the background goes away (but need much larger sample …)

15. Conclusion Cambridge reconstruction effort continuing. Signal separation could be carried out using likelihood techniques but … (i) need better likelihood functions. (ii) need improved reconstruction. Particularly promising for upward-going partially contained events. Reconstruction algorithms could be combined to improve background rejection. So much for Monte Carlo studies … … time to tackle the data too!