n m and n e Physics in MINOS

1. nm and ne Physics in MINOS Alex Himmel, Pedro Ochoa • Antineutrinos • Overview • Oscillations • Systematics • ne Analysis • Nearest neighbors selection • Background estimations • Summary

2. 1 0.5 with SK parameters 0 E (GeV) 0 15 30 Antineutrinos in MINOS • Approx. 6% of our beam is made of muon antineutrinos. Amplified spectrum MC 1x1020 POT Difficulty: not many events in osc. peak region Difficulty: not many events in osc. peak region • Unique advantage: both MINOS detectors are magnetized. Allows us toseparate neutrinos and antineutrinos on an event-by-event basis.

3. Antineutrino physics • Very interesting physics can be done with antineutrinos: 1)noscillation analysis: A large CPT-violating region still unexplored 90%, 95%, 99% and 3σ CPT violating regions still allowed by global fit (except LSND) M.C. Gonzalez-Garcia, M. Maltoni and T. Schwetz (hep-ph/0306226) 2)n→n transitions: have never been looked for beforein atmos sector. • Some models beyond the SM predict them (i.e. Langacker and Wang, Phys. Rev. D 58 093004). • Could fully explain the atmospheric neutrino results (Alexeyev and Volkova, hep ex/0504282) • If 10% or more of neutrinos that disappear transition to antineutrinos then we will see them. 3) Measurement ofBeam ne’s: important for ne analysis • Very strong involvement of Caltech group in these areas.

4. Antineutrino oscillations • MINOS could distinguish between Dm223 and Dm223 at 90% C.L. if Dm223 > 0.004 eV2 in ~1 more year, during normal “neutrino” running • But if CPT is conserved, the reach of antineutrino oscillation analysis would be relatively small: 90% Tentative exclusion limit only valid for high mixing angle Preliminary MC 90%95%99% 3σ ~3 first years of data (6x1020 POT) (no systematics included)

5. Antineutrino running • These difficulties can be overcome with a small amount of reversed horn current running (RHC). • In this case negative particles from the target are focused thus yielding an antineutrino beam: 1x1020 POT 1x1020 POT Forward horn current (FHC) Reversed horn current (RHC) Peak reduction due primarily to cross-section difference (sn < sn)

6. 90% Tentative exclusion limit 90%95%99% 3σ Antineutrino running • Combining FHC with RHC can obtain ameasurement of Dm223 that rivals the first MINOS measurement of Dm223: 6x1020 POT (FHC) + 1x1020 POT (RHC) (no systematics) 90% C.L. 68.3% C.L. Preliminary MC Only ~4 months of antineutrino running (plus ~1 more year of normal running) are needed ! • This data would considerably reduce our best current limits on neutrino CPT • Effort led by Caltech

7. Antineutrino systematics • Systematic errors are a crucial question in combining FHC and RHC data. • ~30% of antineutrinos produced outside of the target region • While neutrinos are also produced outside the target, they are negligible compared to those focused from the target. • A large fraction of the difference between the near and far detectors comes from decay pipe antineutrinos.

8. Antineutrino systematics • Uncertainties in the decay pipe modeling could affect the far/near ratio creating a false signal. • Toy systematic model: • 50% Scaling of the decay pipe component • The other components of the flux unchanged • Preliminary results suggest that the effect is small compared to the expected statistical error at 1x1021 POT.

9. Beam systematics Old Monte Carlo New Monte Carlo Flugg Geant 4 Geometry Geant 3 Geometry Flugg Fluka Geometry Geant-Fluka Physics Geant 4 Physics Fluka Physics • Working to update the beam Monte Carlo from Geant3 to Geant4. • Use Flugg to run the new geometry in Fluka, a more trusted physics simulation

10. Muon Scattering • How well does Geant4 model multiple scattering?  Compared Geant4 and some IHEP data (1986) of muons on a Cu target. • Study shows Geant4 greatly overestimates the data, especially at lower muon momenta.

11. Muon Chopper • Another technique for assessing systematics associated with charge separation was developed at Caltech: 1) Identify stopping muons at the ND: 2) Remove everything but the last x GeV’s of energy: 3) Run reconstruction over muon chopped data and MC 4) Calculate ID efficiency & purity in data & MC for different values of x.

12. < 10% systematic in n purity ! Muon Chopper • The following sources of systematics are addressed by the Muon Chopper: Magnetic field Multiple scattering Reconstruction / Backgrounds • Preliminary results indicate charge separation is reasonably well modeled by the MC:

13. ne Appearance • At MINOS’ baseline of 735 km, • Expect ~14 ne CC events (E<10 GeV) appearing in the MINOS Far Detector for every 1x1020 POT of data if q13 is at CHOOZ limit • Main challenge at MINOS consists in distinguishing between EM and hadronic showers. • At Caltech concentrating on: • developing the best possible ne selection • measuring two of the main backgrounds.

14. Nearest Neighbors Selection • For analysis need to have as good neselection as possible to maximize signal. • Most available selections use multivariate techniques that rely on reconstructed quantities. • But this analysis is a special case: Number of reco variables ~ number of strips in event • Why not perform event ID using strip information alone? • Have been working on a nearest neighbors selection in collaboration with Cambridge University. • Basic idea: • Compare each input event to large libraries of simulated ne CC and NC events. • Select N best matches • Construct discriminant from N best matches information (e.g. fracCC=fraction of N best matches which are neCC)

15. Nearest Neighbors Selection • Advantages: • Approach is in principle optimal. No loss of info from raw→reconstructed quantities • Largely reconstruction-free. • But only optimal if fully sample phase space • Need large libraries (~50-100 Million events of each type). • So far have generated ~50 Million events at Caltech. • Determine how well two events match by asking: Strip # Strip # “what is probability the two events come from same hit pattern at PMTs?” plane # plane # Strip # Strip # Poisson plane # plane #

16. Nearest Neighbors Selection • Example of discriminant: fracCC(y<0.5)=fraction of 20 best matches that were ne with y<0.5 Library size: ~1M ne ~1.5M NC NC CC ne • Already provides the best significance ! • Information of N best matches is very rich: • Plenty of room for further improvement ! Good separation • Currently working hard to get selection fully operational in the Near Detector: data mc nc νe νμcc • Using different background estimating techniques to understand data-MC discrepancy.

17. sin2(2q13) = 0.1, |m31|2 =2.710-3eV2, sin2(2q23) = 1, POT=4x1020 FD Performance • Selected events: ~end of 2007 • Sensitivity limited by statistical fluctuations of background. Define figure of merit FOM=Signal/√Background Note: preselection included Preliminary MC Library size: 5M ne 10M NC cut • Our selection already has a FOM at least 15% higher than all the other selection methods. Selected events: For 0 < Ereco < 6 GeV: FOM=2.29 2 methods for addressing background have been developed at Caltech. antineutrinos muon removal

18. NC Background • Use Muon Removal (MR) to assess the NC Background: • Apply muon removal (MR) to both data and MC • Apply ne selection on both. • Use differences in both samples to reweight the NC expectation in the ne analysis. # of ne candidates in MR data # of NC events in ne analysis ND data before MR after MR (NN selected events) # of ne candidates that are NC in MC # of ne candidates in MR MC • MR reweighting removed the ~60% overall normalization discrepancy

19. Beam ne’s from antineutrinos • Irreducible background in ne analysis: intrinsic beam ne‘s Nearly all come from m+→ e+ + ne + nm • Need to tag antineutrinos coming from m+ decay. Use fact that antineutrino spectrum is practically the same independently of the beam configuration: Most antineutrino parents just go through the center of both horns pseudo-high energy (pHE) pseudo-medium energy (pME) Low energy (LE) MC MC MC • Work led by Caltech, in collaboration with BNL

20. n from m+ nfromm+ Beam ne’s from antineutrinos • Only m+ component changes significantly when running in pME or pHE ! The Technique: (pME-LE)TRUE at 1e18 POT • Scale pME (or pHE) and LE data to same POT and take the difference • Fit with using shapes from the MC: LE Corrections due to differences in the antineutrinos from p- and K- pME • Expected sensitivity: pHE data already taken!

21. Summary & Ongoing Work • Antineutrinos: • Only ~4 months of antineutrino running are needed to make a measurement of Dm223 with a precision that rivals the first MINOS Dm223 result. • Will search for nm→nm transitions for the first time. • Developing tools for beamline simulation. • ne appearance:  The CHOOZ limit will be reached by end of 2007 Expect 1st MINOS neappearance result by next year. • Very positive outlook. Working hard to: • Further improve selection • Assess systematics. • Critical role played by Caltech group in these two areas.

22. Backup

23. 3.5m 1.8m 2.3m short event, often diffuse short, with typical EM shower profile neAppearance in MINOS • Challenge: At MINOS, we lack the granularity to fully resolve hadronic vs. EM showers: steel thickness: 2.54cm| strip width: 4.12cm (Molière radius ~3.7cm) νμ CC Event νeCC Event NC Event ne e- nm m- nm nm W W Z n p p n p p (MC) long μ track & hadronic activity at vertex