Identification of neutrino oscillations in the MINOS detector Daniel Cole djc56@cam.ac.uk

1. Identification of neutrino oscillations in the MINOS detectorDaniel Coledjc56@cam.ac.uk

2. Aims • Use likelihood methods to investigate separation of CC muon neutrino events from background of NC and electron neutrino events. • Focus on improving separation of low energy (<2GeV) neutrino events.

3. 120 000 MC beam neutrino events (generated at Cambridge using NuMI low-energy beam (PH2LE) flux file) 4/5 data used to generate PDFs of 3 variables 1/5 data used as sample DetSim Cambridge demultiplexer Cambridge Standard Reconstruction Reconstruction Analysis Code

4. i) track strips / total strips ii) track pulse height per track plane track planes For each event in sample: pcc = pcc1×pcc2 ×pcc3 pnc = pnc1×pnc2 ×pnc3 i) ii) iii) Formation of the Likelihood

5. Standard likelihood: efficiency = CC events above PID threshold / total CC events purity = CC events above PID threshold / total events above PID threshold Standard Likelihood

6. Super-K Likelihood • Attempt to reproduce David Petyt’s results using likelihood based on S-K analysis: • S-K likelihood: • Improvement due to updated reconstruction code

7. Likelihood Function Comparison • Comparison of standard and Petyt’s likelihood functions (using SR): • Little difference in performance. Standard likelihood used from now on. • Attempt to develop analysis…

8. Track Plane Cut • First new cut: any events with ≥60 track planes must be CC so put into likelihood at PID = 1 Negligible gain in efficiency but pre- likelihood cut simplifies the procedure

9. Comparison of Reco Algorithms • Comparison of SR and Cambridge (AtNu). reconstruction codes (using the track plane cut):

10. Visible Energy Comparison • CC: visible energy = true neutrino energy • NC: visible energy = true hadronic energy • Sample split into 4 visible energy ranges: energy < 2GeV energy = 2-5GeV energy = 5-10GeV energy > 10GeV

11. Low Energy Events • <2GeV visible energy range performs poorly due to low number of reconstructed tracks and high background. • Sample of 20 000 <2GeV events generated and added to previous data. • Define: reconstructed energy = reconstructed track energy + reconstructed hadronic energy • New set of PDFs constructed from low reconstructed energy events only. Previously used all events.

12. PDFs for Low Energy Events • New set of variables: i) ii) iii) i) track strips / total strips • track planes • reconstructed track velocity • (Also tried: • track pulse height per track plane • track end plane – shower vertex end plane) • Further cut: events with track end plane - shower vertex end plane ≥40 identified as CC.

13. Separation of Low Energy Events • original variables, all events used in PDFs • new variables, all events used in PDFs • new variables, only low reconstructed energy events used in PDFs • 5% improvement in efficiency at 95% purity for low energy events – but even better at higher purities.

14. Conclusions • used new likelihood • separated events by reconstructed energy • chose suitable variables for energy range (for low energy events: i) track strips / total strips ii) track planes iii) reconstructed track velocity) • performed pre-likelihood cuts when: track planes ≥60 track end plane - shower vertex end plane ≥40 • achieved improvements in signal separation