1. 1 MiniBooNE Update and Extension Request Richard Van de Water and Steve Brice for the MiniBooNE Collaboration Nov 2, 2007

2. 2 Overview 1.Brief reminder of oscillation result 2.Update on low energy excess 3.Sampling of other analyses 4.Run request for an electron anti-neutrino appearance search “MiniBooNE requests an additional 3.0 x 10 20 POT in anti-neutrino mode to give the experiment a total of ~5.0 x 10 20 POT in this configuration and enable a powerful check of the LSND result in anti- neutrinos. The experiment further requests that these POT be delivered in FY2008 and FY2009.”

3. 3 track-based analysis: Counting Experiment: 475<E <1250 MeV data: 380 events expectation: 358  19 (stat)  35 (sys) significance: 0.55  oscillation analysis: Results in April 2007 No evidence for   e appearance in the analysis region 96 ± 17 ± 20 events above background, for 300< E QE <475MeV However, at low energy Phys. Rev. Lett. 98, 231801 (2007)

4. 4 Status of Low Energy e Candidate Analysis Since Oscillation Publication Have observed a ~4 sigma excess down to 200 MeV (including systematic errors). Confirmed excess is electromagnetic (electron or gamma- ray), i.e. particle ID is working at low energy. MiniBooNE has no ability to distinguish gammas from electrons Events have normal reconstruction, e.g. Visible energy, radius, x,y,z, beam angle, etc. Major sources of backgrounds all look well modelled, e.g. dirt, radiative delta decay, mis-ID pions and muons. Working on possible new sources of single gamma-rays. Currently analyzing neutrinos from NuMI source, horn-off, and anti-neutrino data sets.

5. 5 Examination of backgrounds reconstructed neutrino energy bin (MeV) 200-300 300-475 475-1250 total background  284±25 274±21 358±35  e intrinsic 26 67 229   induced 258 207 129 NC  0 115 76 62 NC  →N  20 51 20 Dirt 99 50 17 other 24 30 30 data 375±19 369±19 380±19 No significant excess at higher E, where  e bkgd dominant. Largest backgrounds at lower E are  -induced, in particular: NC  0 NC  → N  Dirt New 200-300 MeV bin Preliminary

6. 6 Checking Known e Backgrounds Measure  0 production rate as a function of  0 momentum and compare to MC prediction to calculate a correction factor. Correct NC   mis-ID rate using this measured correction factor –(Also can be used to correct the  N +  radiative background) Dirt background is due to interactions outside detector creating neutrals that enter tank –Measured in “dirt-enhanced” samples: Before box-opening meas/pred = 1.00±0.15 After box opening (bigger sample) meas/pred = 1.08  0.12 Backgrounds with a muon measured using events with cleanly time separated electron from muon decay –Includes any background from muon internal bremsstrahlung –Paper on this work: arXiv:0710.3897 [hep-ex] Submitted to PRD visible energy (GeV)dist to tank wall along track (cm)

7. 7 Possible Sources of Additional Single Gamma Backgrounds Processes that remove/absorb one of the gammas from a  -induced NC  0   –Photonuclear absorption was missing from our GEANT3 detector Monte Carlo But tends to give extra final state particles. Reduces size of excess Systematics being calculated No effect above 475 MeV processes that produce a final state single gamma –Example: “Anomaly mediated neutrino-photon interactions at finite baryon density.” Standard Model process  Under active investigation, prediction of ~140 (g  /10) 4 events, where g  is 10 to 30. Can use photon energy to check prediction. (Harvey, Hill, and Hill, arXiv:0708.1281[hep-ph]) Since MiniBooNE cannot tell an electron from a single gamma, any process that leads to a single gamma in the final state can be a background 200<En<300 Photonuc adds ~27% of excess 300<En<475 Photonuc adds ~13% of excess Stat error only Preliminary

8. 8 NuMI event composition:  : 81% e : 5%   : 13%  e : 1% Decay Pipe Beam Absorber The beam at MiniBooNE from NuMI is significantly enhanced in e from K decay because of the off-axis position. MINOS near NuMI Events in MiniBooNE MiniBooNE Work in collaboration with MINOS

9. 9 NuMI  and e Samples  Charged Current Quasi Elastic Sample e Charged Current Quasi Elastic Sample Results to be presented at an Upcoming Wine and Cheese seminar

10. 10 CC  + – 2 papers expected CC  0 – Reconstruction challenges overcome – 1 paper expected NC  0 – 1 paper about to be submitted to PRD – Coherent/resonant in nu and anti-nu modes – Flux averaged cross-section measurement – 2 further papers expected NC Elastic – About to graduate – Flux averaged cross-section measurement – 1 paper expected  -e Elastic – Nu mag. Mom – 1 paper expected. Oscillation – Refined Nue appearance – Nuebar appearance – Numu and numubar disappearance – 1 PRL, ~3 further papers expected Low Energy Excess – Big effort – 2+ papers expected Alternative Oscillations – Phenomenology – CP violation, Lorentz violation,... – 3+ papers expected NuMI Events – Large event rate from NuMI beam – Check on osc. and Low E – 1 paper being written CCQE – 1 paper submitted to PRL – 2 further papers expected Broad Range of Analyses Collaboration spent last 2 years sole focused on e appearance analysis Collaboration retasked over last 5 months to broad range of analyses No organizational separation between neutrino and anti-neutrino mode 15 PhD Students + 4 graduated = PhD Student (4 already graduated, not shown)

11. 11 Excellent description of  CCQE reaction has been obtained after adjustment of 2 Fermi-gas- model parameters: From Q 2 (4-mom. transfer) fits to  CCQE data: M A eff -- Effective axial mass  -- Pauli blocking param Paper on this work: arXiv:0706.0926 [hep-ex], submitted to PRL  CCQE Q 2 distribution  CCQE E distribution CCQE Events

12. 12 Wrong Sign Extraction Critical to extract neutrino flux in anti-neutrino mode from data and not rely entirely on MC Use angular distribution of muons from CCQE interaction All anti-nu analyses depend on this work Neutrino Mode MC Prediction: WS-QE:~2% RS-QE:~75% Non-QE:~23% Anti-Neutrino Mode MC Prediction: WS-QE:~20% RS-QE:~50% Non-QE:~30% Stat errors only

13. 13 NC  0 in Anti-Neutrino Mode Coherent contribution evident E  (1-COS   ) (MeV) M  (MeV) Statistical errors only No fit, just out-of-the-box Monte Carlo This is the worlds only anti-neutrino NC  0 sample below 2 GeV

14. 14 MiniBooNE Present and Future Taken 5.58 x 10 20 POT in neutrino mode –Making suite of cross-section measurements –Also searching for neutrino disappearance –Publications already coming out –No need to request more neutrino mode running Taken 2.33 x 10 20 POT in anti-neutrino mode –Making suite of cross-section measurements –Searching for anti-neutrino disappearance PAC request for extra running for an anti-nue appearance search –LSND result was an indication of anti-nue appearance –CP violating models (e.g. “3+N”) predict no MB signal in neutrino mode, but LSND style signal in anti-neutrino mode –Extra 3 x 10 20 POT (making grand total of ~5 x 10 20 POT) –Should take FY2008 and FY2009 running

15. 15 Calculating anti- e Appearance Sensitivity Two key features of neutrino mode oscillation result: –Backgrounds measured or constrained by MiniBooNE data –Systematics estimated by assessing uncertainty in all relevant low level quantities (e.g. pion production, detector optical model, etc) and propagating these to an error matrix on the final histogram. This approach carries over directly to an anti- e measurement –i.e. the vast majority of the work has already been done Just need to turn the crank on the anti-neutrino MC and propagate error matrices to produce complete anti- e sensitivity –Full set of low level systematics has already been assessed The major differences from neutrino mode analysis are handled automatically –For example: larger wrong sign background in e and  samples

16. 16 Anti-nue Appearance Sensitivity Region allowed at 90% C.L. by joint analysis of LSND and KARMEN Only anti-neutrinos allowed to oscillate

17. 17 Conclusion and Request MiniBooNE is bringing out a wide range of important results in neutrino and anti-neutrino oscillation and cross-section physics. “MiniBooNE requests an additional 3.0 x 10 20 POT in anti-neutrino mode to give the experiment a total of ~5.0 x 10 20 POT in this configuration and enable a powerful check of the LSND result in anti-neutrinos. The experiment further requests that these POT be delivered in FY2008 and FY2009.”

18. 18 BackUp Slides

19. 19 Anti-Neutrino Low Energy Excess Scenarios Predictions for the excess of nue(bar) candidate events in anti-neutrino mode under 3 scenarios:- 1.The excess is due to nue CC interactions 2.The excess is due to a mis-estimation of the numu NC D rate 3.The excess is due to some other NC process whose cross-section is the same for neutrinos and anti-neutrinos With 5.0 x 10 20 POT in anti-neutrino mode the excesses in these scenarios are not significantly different from each other Alternatively if one naively scales the neutrino mode excess down by the ratio of anti-neutrino mode to neutrino mode backgrounds then one predicts an excess of 67±16.7(sys)±16.4(stat) for 5.0 x 10 20 POT.

20. 20 CP Violating Models Adding two (or more) sterile neutrinos brings a CP violating phase (  45 ) into the mixing matrix Fits of such models to world data allow the possibility for MiniBooNE to see no signal in neutrino mode, but a visible signal in anti-neutrino mode

21. 21 Particle Identification No major discrepancy in Particle Identification

22. 22 NC  0 and Radiative  N  Backgrounds are Constrained by Identified NC  0 Events Using PID variables isolate a very pure sample  0 events from   N    N +  0 (mainly from  N +  0 ) Purity ~90% or greater Measure  0 production rate as a function of  0 momentum and compare to MC prediction to calculate a correction factor. Correct NC   mis-ID rate using this measured correction factor (Also can be used to correct the  N +  radiative background) M  Mass Distribution for Various p  0 Momentum Bins

23. 23 “Dirt” background - Dirt background is due to interactions outside detector creating neutrals that enter tank - Measured in “dirt-enhanced” samples: - before box-opening, fit predicted: 1.00±0.15 - in different (open) sample, a fit says that meas/pred is 1.08  0.12. - Shape of visible E and distance-to-wall distributions are well-described by MC shower dirt results from dirt-enhanced fits visible energy (GeV) dist to tank wall along track (cm) 76%  0  

24. 24 Muon Misidentification (including muon internal bremsstrahlung) Data-MC excess, but note the scale! Apply reconstruction and particle identification to clean sample muon CCQE events (muon decay visible). Then scale normalization to account for how often the second subevent is missing What results is a direct measurement and MC prediction for almost all the rate at which events with a final state muon enter the e background -Misidentified Muons not a problem. Paper on this work: arXiv:0710.3897 [hep-ex] Submitted to PRD

25. 25 example signal-candidate event display Detector Anomalies or Reconstruction Problems event/POT vs day, 300<Enu<475 MeV No Detector anomalies found - Example: rate of electron candidate events is constant (within errors) over course of run No Reconstruction problems found - All low-E electron candidate events have been examined via event displays, consistent with 1-ring events Signal candidate events are consistent with single-ring neutrino interactions  But could be either electrons or photons

26. 26 energy/angle distributions in E bins 200< E <300 MeV 300 <E <475 MeV 475 <E <3000 MeV cos  200< E <300 MeV 300< E <475 MeV 475< E <3000 MeV At higher energy, data are well-described by predicted background Excess distributed among visible E, cos  bins visible energy distributions: cos  distributions:

27. 27 Other Distributions UZ, Radius, RtoWall, etc. => Events distributed throughout tank, no indication of edge effects.

28. 28 Logistics Survey of collaborating institutions on ability to staff shifts in new two years –Recent past: 54 FTE –FY2008: 44 FTE –FY2009: 37 FTE FY2008 shared with SciBooNE so filling shifts should not be an issue FY2009 will need to increase people’s shift quota and perhaps take measures like pager shifts for overnight

29. 29 Sensitivity Over LSND Only Regions Regions allowed at 90% C.L. And 95% C.L. by LSND alone

30. 30 Effect of Statistics and Systematics Regions allowed at 90% C.L. And 95% C.L. by LSND alone