1. Measurement of the off-axis NuMI beam with MiniBooNE Zelimir Djurcic Columbia University Zelimir Djurcic Columbia University Outline of this Presentation 1.Off-axis Neutrino Beam 2.NuMI flux at MiniBooNE 3.MiniBooNE Detector and Reconstruction 4.CC  Sample 5.NC   Sample 6.CC e Sample Brookhaven National Lab Seminar, 1/17/08

2. Fermilab Neutrino Beams

3. LSND observed a (~3.8  ) excess of anti- e events in a pure  anti-  beam: 87.9 ± 22.4 ± 6.0 events  Models developed with 2 sterile ’s MiniBooNE Motivated the LSND Experiment Result In SM there are only 3 neutrinos

4. No Oscillation Signal Found! MiniBooNE Data Shows Low Energy Excess! reconstructed neutrino energy bin (MeV) 200-300 300-475 475-1250 data 375 369 380 total background  284 ± 25 274 ± 21 358 ± 35 Excess 91 ± 30 95 ± 27 22 ± 40 Result of the MiniBooNE Oscillation Search Result of the MiniBooNE Oscillation Search

5. 120 GeV protons ~ 3xE13/pulse. Primarily for the MINOS long baseline experiment. MINOS Experiment L~700 km E~2-5GeV However, the NuMI beam points in the direction of MiniBooNE as well. NuMI Beam NuMI Beam

6.  Target Horns Decay Pipe Detector First Proposed by BNL-E889 On-axis, neutrino energy more tightly related to hadron energy. Off-axis, neutrino spectrum is narrow-band and ‘softened’. Easier to estimate flux correctly: all mesons decay to same energy. Off-axis Beam

7. NOvA: –NuMI off-axis beam –810km baseline –14.5mrad; E ~2GeV T2K: –J-PARC 50GeV proton beam –Use SK as Far detector 295km away –35 mrad; E ~0.6GeV Use off-axis trick for optimized  -> e search. On-axis beam Off-axis beam Future off-axis Neutrino Experiments

8. NuMI events (for MINOS) detected in MiniBooNE detector! MiniBooNE detector is 745 meters downstream of NuMI target. MiniBooNE detector is 110 mrad off-axis from the target along NuMI decay pipe. p beam , K  NuMI beam and MiniBooNE detector

9. Analysis Motivation Observation and analysis of an off-axis beam. Measurement of  /K components of the NuMI beam. The NuMI beam provides MiniBooNE with an independent set of neutrino interactions. Enables a comparison of the Booster Neutrino Beam (BNB) with the NuMI neutrino beam (off axis): -Similar energy spectrum. -Proton target is further away (~746 m vs. 550 m) -Very different background composition. -Rich in e flux → can study e reactions in greater detail.

10. Beam Information and Neutrino Fluxes at MiniBooNE are provided by the MINOS collaboration (BNL, U Texas). Analysis of MiniBooNE data performed by the MiniBooNE collaboration. Joint collaboration between MiniBooNE and NuMI

11. KK  stopped K  stopped   Opportunity to demonstrate off- axis technique. Known spectral features from , K decays. Expected energy spectra is within MiniBooNE energy acceptance. NuMI off-axis beam at MiniBooNE detector

12. NuMI off-axis beam produces strong fluxes in both µ and e flavors. The e ’s are helpful to study the MiniBooNE detector. Provide a new setting for oscillation studies. Rates: NuMI off-axis(at MB) e ~6% NuMI on-axis e ~1% BNB on-axis e ~0.5% NuMI as a “ e Source” KK  stopped K 

13. Extensive experience with MINOS data. MINOS acquired data sets in variety of NuMI configurations. Tuned kaon and pion production (x F,p T ) to MINOS data. MINOS  Same parent hadrons produce neutrinos seen by MiniBooNE Flux at MiniBooNE should be well- described by NuMI beam MC? D.G. Michael et al, Phys. Rev. Lett. 97:191801 (2006) D.G. Michael et al, arXiv:0708.1495 (2007) NuMI Neutrino Spectrum is “Calibrated”

14. Decays of hadrons produce neutrinos that strike both MINOS and MiniBooNE. Parent hadrons ‘sculpted’ by the two detectors’ acceptances. Plotted are p T and p || of hadrons which contribute neutrinos to MINOS (contours) or MiniBooNE (color scale). MINOS MiniBooNE MINOS MiniBooNE Two Views of the Hadron Decays

15. Higher energy neutrinos mostly from particles created in target. Interactions in shielding and beam absorber contributes in lowest energy bins. Plots show where the parent was created. e  MiniBooNE diagram not to scale! Neutrino Origin Along NuMI Beam Line

16. Higher energy neutrinos mostly from particles created in target. Interactions in shielding and beam absorber contributes in lowest energy bins. Neutrino sources along NuMI beamline

17. Are the neutrinos coming from the target?

18. Focusing uncertainties are negligible. Uncertainty is dominated by production of hadrons. –off the target (estimated from MINOS tuning). –in the shielding (estimated in gfluka/gcalor). –in beam absorber (estimated in gfluka, 50% error assigned). stopped mesons excluded in this plot MINOS Tuning Flux Uncertainties

19. MiniBooNE (Booster Neutrino Experiment) becomes An off axis neutrino experiment using Main Injector

20. NuMI Beam and MiniBooNE Detector NuMI events (for MINOS) detected in MiniBooNE detector! MiniBooNE Detector: 12m diameter sphere 950000 liters of oil 950000 liters of oil(CH 2 ) 1280 inner PMTs 240 veto PMTs p beam , K  Main trigger is an accelerator signal indicating a beam spill. Information is read out in 19.2  s interval covering arrival of beam.

21. Detector Operation and Event reconstruction No high level analysis needed to see neutrino events Backgrounds: cosmic muons and decay electrons ->Simple cuts reduce non-beam backgrounds to ~10 -5 Events in DAQ window:no cuts Removed cosmic ray muons: PMT veto hits < 6 Removed cosmic ray muons and  -decay electrons: PMT veto hits < 6 and PMT tank hits > 200 6-batch structure of MI about 10  s duration reproduced.

22. Detector Operation and Event reconstruction The data set analyzed here: 1.42 x 10 20 P.O.T. We have a factor two more data to analyze! The rate of neutrino candidates was constant: 0.51 x 10 -15 /P.O.T. Neutrino candidates counted with: PMT veto hits 200

23.  0 →  electron candidate  candidate  0 candidate Č erenkov rings provide primary means of identifying products of interactions in the detector  n   - p e n  e - p  p   p  0 n Particle Identification

24. Events from NuMI detected at MiniBooNE CCQE 39%  + CC  + 26%  0 NC  0 9% Neutrino interactions at carbon simulated by NUANCE event generator: neutrino flux converted into event rates. Event rates Event rates Flux NuMI event composition at MB  -81%, e -5%,   -13%,  e -1%

25. Analysis Algorithm

26. To reconstruct an event: -Separate hits in beam window by time into sub-events of related hits. -Reconstruction package maximizes likelihood of observed charge and time distribution of PMT hits to find track position, direction and energy (from the charge in the cone) for each sub-event. Event Reconstruction The tools used in the analysis here are developed and verified in MiniBooNE oscillation analysis of events from Booster beam. Phys. Rev. Lett. 98, 231801 (2007), arXiv:0704.1500 [hep-ex] Details: and arXiv:0706.0926 [hep-ex] Accepted for publ. by Phys.Rev.Lett. Event selection very similar to what was used in MiniBooNE analyses.

27. Uses detailed, direct reconstruction of particle tracks, and ratio of fit likelihoods to identify particles. Analysis Method Apply likelihood fits to three hypotheses: -single electron track -single muon track -two electron-like rings (  0 event hypothesis ) Compare observed light distribution to fit prediction: Does the track actually look like an electron? log(L e /L  )<0  -like events log(L e /L  )>0 e-like events Example from MiniBooNE Oscillation Analysis. log(L e /L  ) Form likelihood differences using minimized –logL quantities: log(L e /L  ) and log(L e /L  )  e

28.  CCQE Analysis  CCQE Analysis

29. Analysis of the  CCQE events from NuMI beam  e  CCQE ( +n   +p) has a two “subevent” structure (with the second subevent from stopped   e e) Event Selection: Subevent 1: Thits>200, Vhits<6 R<500 cm L e /L  < 0.02 Subevent 2: Thits<200, Veto<6 p  n Scintillation Cerenkov 1 12 C Cerenkov 2 e  Tank Hits

30. This sample contains 18000 events of which 70% are CCQE’s. Log(L e /L  )< 0.02 Visible E of  : final state interactions in  CCQE sample Data (stat errors only) compared to MC prediction for visible energy in the tank. Visible energy in tank [GeV] CCQE  + CC  + Monte Carlo Data PRELIMINARY CCQE  + CC  + “other” Total MC N  X  0 Beam e  p      n    p  n    n  + Other  Events Events

31.  K Compare  CCQE MC to Data:Parent Components MC is normalized to data POT number with no further corrections! Visible energy in tank [GeV] Beam MC tuned with MINOS near detector data. Cross-section Monte Carlo tuned with MB measurement of CCQE pars M A and . PRELIMINARY arXiv:0706.0926 [hep-ex]

32.  K Compare  CCQE MC to Data:Parent Components Predicted Kaons are matching the data out of box! Visible energy in tank [GeV] PRELIMINARY

33. Systematic Uncertainties in  CCQE analysis To evaluate Monte Carlo agreement with the data need estimate of systematics from three sources: -Beam modeling: flux uncertainties. -Cross-section model: neutrino cross-section uncertainties. -Detector Model:describes how the light emits, propagates, and absorbs in the detector (how detected particle looks like?). Detector ModelCross-section Beam Total Visible energy [GeV] PRELIMINARY PRELIMINARY

34. Add Systematic uncertainty to  CCQE Monte Carlo  visible energy distribution Visible energy in tank [GeV] Outgoing  angular distribution cos   Information about incoming :wrt NuMI target direction.  K  K Predicted Pions are matching the data within systematics! PRELIMINARY PRELIMINARY

35. Understanding of the beam demonstrated: MC is normalized to data POT number ! Reconstructed E QE :from E lepton (“visible energy”) and lepton angle wrt neutrino direction  CCQE sample: Reconstructed energy E of incoming  CCQE sample: Reconstructed energy E of incoming  K PRELIMINARY

36. This is the first demonstration of the off- axis principle. There is very good agreement between data and Monte Carlo:the MC need not be tuned. Conclusion from  CCQE analysis section Because of the good data/MC agreement in  flux and because the  and e  share same parents the beam MC can now be used to predict: e rate, and mis-id backgrounds for a e analysis.

37. e CCQE Analysis e CCQE Analysis

38. e When we try to isolate a sample of e candidates we find background contribution to it: -  0 (  0  ) and radiative  (  N  ) events, and -”dirt” events. Backgrounds to e CCQE sample e CCQE ( +n  e+p) Therefore, before analyzing e CCQE we constrain the backgrounds by measurement in our own data.

39. Strategy:Don’t try to predict the  0 mis-id rate, measure it! Measured rates of reconstructed  0 … tie down the rate of mis-ids  decays to a single photon: with 0.56% probability: Analysis of  0 events from NuMI beam  0 What is applied to select  0 s Event pre-selection: 1 subevent Thits>200, Vhits<600 R<500 cm log(L e /L  )>0.05 (e-like) log(L e /L  )<0 (  0 -like)    Among the e-like mis-ids,  0 decays which are boosted, producing 1 weak ring and 1 strong ring is largest source. p ++ 00 p   pp ++  p

40. Analysis of  0 events from NuMI beam:  0 mass This sample contains 4900 events of which 81% are  0 events: world second largest  0 sample! The peak is 135 MeV/c 2 e appear to be well modelled. Monte Carlo Data 0000 e 

41. Analysis of  0 events from NuMI beam:  0 mass The peak is 135 MeV/c 2 Monte Carlo Data 0000 e  The  0 events are well modeled with no corrections to the Monte Carlo!

42. Analysis of  0 events from NuMI beam:  0 momentum We declare good MC/Data agreement  0 for  0 sample going down to low mass e region where e candidates are showing up! Monte Carlo Data 0000 e  Further Cross Check! PRELIMINARY

43. Analysis of dirt events from NuMI beam - “Dirt” background is due to interactions outside detector. Final states (mostly neutral current interactions) enter the detector. - Measured in “dirt-enhanced” samples: - we tune MC to the data selecting a sample dominated by these events. -”Dirt” events coming from outside deposit only a fraction of original energy closer to the inner tank walls. - -Shape of visible energy and event vertex distance-to-wall distributions are well-described by MC: good quantities to measure this background - component. shower dirt

44. Selecting the dirt events Event pre-selection: 1 subevent Thits>200, Vhits<600 R<500 cm log(L e /L  )>0.05 (e-like) E e <550 MeV Distance-to-wall <250 cm m  <70 MeV/c 2 (not  0 -like) Dist-to-wall of tank along track [m]Visible energy [GeV] Events/bin Dirt sample interactions in the tank Uncertainty in the dirt rate is less than 20%. Fits to dirt enhanced sample: the dirt We declare good MC/Data agreement for the dirt sample. PRELIMINARY

45. Analysis of e events: do we see data/MC agreement? Analysis of the e CCQE events from NuMI beam e CCQE ( +n  e+p) 1 Subevent Thits>200, Vhits<6 E e R 200MeV Likelihood cuts as the as shown below + Likelihood e/  cutLikelihood e/  cut Mass(  0 ) cut Cut region Signal region Visible energy [MeV] MC example plots here come from Booster beam MC E e E e >200MeV cut is appropriate to remove e contribution from the dump that is hard to model.

46. Visible energy of e CCQE events Before we further characterize data/MC agreement we have to account for the systematic uncertainties. Data = 783 events. Monte Carlo prediction = 662 events. Visible energy in tank [GeV] Monte Carlo Data 0000 e Other  dirt  PRELIMINARY

47. Systematic Uncertainties in e CCQE analysis Detector ModelCross-section Beam Total Visible energy [GeV] PRELIMINARY PRELIMINARY “dirt” component of Xsec: 20% error;  0 component of Xsec: 25% error

48. e CCQE events: e visible energy and angular distribution e CCQE events: e visible energy and angular distribution e visible energy distribution Outgoing e angular distribution Visible energy in tank [GeV] cos  e All   K  KLKL PRELIMINARY PRELIMINARY

49. Outgoing electron angular distribution e CCQE sample:Reconstructed energy E of incoming e CCQE sample: Reconstructed energy E of incoming All  All e PRELIMINARY

50. E QE [MeV] 200-900 900-3000 total background 401±66 261±50 e intrinsic 311 231  induced 90 30 NC  0 30 25 NC  → N  14 1 Dirt 35 1 other 11 3 Data 498±22 285±17 Data-MC 97  70 24  53 Significance 1.40  0.45  Summary of estimated backgrounds vs data  e CCQE sample e  At this point systematic errors are large: we cannot say much about the difference between low and high-E regions. In the future we will reduce e CCQE sample systematics constraining it with our large statistics  CCQE sample. Looking quantitative into low energy and high energy region:

51. Summary and Future Steps

52. We performed analyses of neutrinos from NuMI beam observed with MiniBooNE detector. The sample analyzed here corresponds to 1.42x 10 20 protons on NuMI target. We observed good description of the data by Monte Carlo  e with both  CCQE and e CCQE sample: successful demonstration of an off-axis beam at 110 mrad.   CCQE sample demonstrated proper understanding of the Pion and Kaon contribution to neutrino beam. PRELIMINARY

53. e  In the future we will reduce e CCQE sample systematics constraining it with our large statistics  CCQE sample. e The e CCQE sample will be compared to what we observed with Booster beam. We are currently reprocessing and collecting more data (expect about 3 x 10 20 P.O.T. collected by now.) These errors will be reduced PRELIMINARY