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Zelimir Djurcic Columbia University

Measurement of the off-axis NuMI beam with MiniBooNE. Zelimir Djurcic Columbia University. Outline of this Presentation Off-axis Neutrino Beam NuMI flux at MiniBooNE MiniBooNE Detector and Reconstruction CC n m Sample NC p 0 Sample CC n e Sample.

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Zelimir Djurcic Columbia University

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  1. Measurement of the off-axis NuMI beam with MiniBooNE Zelimir Djurcic Columbia University • Outline of this Presentation • Off-axis Neutrino Beam • NuMI flux at MiniBooNE • MiniBooNE Detector and Reconstruction • CC nm Sample • NC p0 Sample • CC ne Sample Brookhaven National Lab Seminar, 1/17/08

  2. Fermilab Neutrino Beams

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

  4. Result of the MiniBooNE Oscillation Search 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 No Oscillation Signal Found! MiniBooNE Data Shows Low Energy Excess!

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

  6. Off-axis Beam 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 .  Detector First Proposed by BNL-E889 Target Decay Pipe  Horns

  7. Future off-axis Neutrino Experiments On-axis beam Off-axis beam Use off-axis trick for optimized ->e search. 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

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

  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. Joint collaboration between MiniBooNE and NuMI 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.

  11. 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 stoppedp+ stopped K+ p+ K+

  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” stopped K+ m+ K+

  13. Extensive experience with MINOS data. MINOS acquired data sets in variety of NuMI configurations. Tuned kaon and pion production (xF,pT) to MINOS data. NuMI Neutrino Spectrum is “Calibrated” MINOS nm MINOS nm • 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)

  14. Decays of hadrons produce neutrinos that strike both MINOS and MiniBooNE. Parent hadrons ‘sculpted’ by the two detectors’ acceptances. Plotted are pT and p|| of hadrons which contribute neutrinos to MINOS (contours) or MiniBooNE (color scale). Two Views of the Hadron Decays MiniBooNE MiniBooNE MINOS MINOS

  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. Neutrino Origin Along NuMI Beam Line ne nm MiniBooNE diagram not to scale!

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

  17. Are the neutrinos coming from the target?

  18. Flux Uncertainties 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). MINOS Tuning stopped mesons excluded in this plot

  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 q p, K p beam Decay Pipe MiniBooNE Detector: 12m diameter sphere 950000 liters of oil(CH2) 1280 inner PMTs 240 veto PMTs 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 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. Backgrounds: cosmic muons and decay electrons ->Simple cuts reduce non-beam backgrounds to ~10-5

  22. Detector Operation and Event reconstruction The rate of neutrino candidates was constant: 0.51 x 10-15 /P.O.T. Neutrino candidates counted with:PMT veto hits < 6 and PMT tank hits > 200 The data set analyzed here: 1.42 x 1020 P.O.T. We have a factor two more data to analyze!

  23. Particle Identification Čerenkovrings provide primary means of identifying products of  interactions in the detector m candidate nmn m- p electroncandidate nen  e-p p0 candidate nmp nm pp0 n n p0→ gg

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

  25. Analysis Algorithm

  26. Event Reconstruction The tools used in the analysis here are developed and verified in MiniBooNE oscillation analysis of events from Booster beam. Details: Phys. Rev. Lett. 98, 231801 (2007), arXiv:0704.1500 [hep-ex] arXiv:0706.0926 [hep-ex] Accepted for publ. by Phys.Rev.Lett. and Event selection very similar to what was used in MiniBooNE analyses. 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.

  27. Analysis Method Uses detailed, direct reconstruction of particle tracks, and ratio of fit likelihoods to identify particles. 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? Form likelihood differences using minimized –logL quantities: log(Le/L) and log(Le/L) log(Le/L)<0-like events log(Le/L) log(Le/L)>0e-like events Example from MiniBooNE Oscillation Analysis. e 

  28.  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  ee) Tank Hits Cerenkov 1 e  12C nm Cerenkov 2 n Scintillation p Event Selection: Subevent 1: Thits>200, Vhits<6 R<500 cm Le/L < 0.02 Subevent 2: Thits<200, Veto<6

  30. Visible E of : final state interactions in  CCQE sample Log(Le/L)< 0.02 Total MC nNnXp0 Beam ne nmp m-D nmn m-p nmn m-np+ Other nm Events Events Events Data CCQE Monte Carlo “other” CC+ CCQE CC+ PRELIMINARY Visible energy in tank [GeV] Data (stat errors only) compared to MC prediction for visible energy in the tank. This sample contains 18000 events of which 70% are CCQE’s.

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

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

  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 Model Cross-section Visible energy [GeV] Visible energy [GeV] Total PRELIMINARY Beam PRELIMINARY Visible energy [GeV] Visible energy [GeV]

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

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

  36. Conclusion from  CCQE analysis section 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. 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

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

  39. Among the e-like mis-ids, 0 decays which are boosted, producing 1 weak ring and 1 strong ring is largest source. Analysis of 0 events from NuMI beam   g + p p p g p0 g  g  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 g + 0 p p  decays to a single photon: with 0.56% probability: What is applied to select 0s Event pre-selection: 1 subevent Thits>200, Vhits<600 R<500 cm log(Le/L)>0.05(e-like) log(Le/L)<0(0-like)

  40. Analysis of 0 events from NuMI beam: 0 mass The peak is 135 MeV/c2 Data Monte Carlo 0 e  e appear to be well modelled. This sample contains 4900 events of which 81% are 0 events: world second largest 0 sample!

  41. Analysis of 0 events from NuMI beam: 0 mass The peak is 135 MeV/c2 Data Monte Carlo 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 Data Monte Carlo  0 e PRELIMINARY We declare good MC/Data agreement for 0 sample going down to low mass region where ecandidates are showing up! Further Cross Check!

  43. Analysis of dirt events from NuMI beam dirt shower - “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.

  44. Selecting the dirt events log(Le/L)>0.05(e-like) Ee <550 MeV Distance-to-wall<250 cm m<70 MeV/c2(not 0-like) Event pre-selection: 1 subevent Thits>200, Vhits<600 R<500 cm Fits to dirt enhanced sample: Uncertainty in the dirt rate is less than 20%. Dirt sample • interactions in the tank Events/bin Events/bin PRELIMINARY We declare good MC/Data agreement for the dirtsample. Dist-to-wall of tank along track [m] Visible energy [GeV]

  45. Analysis of the e CCQE events from NuMI beam e CCQE (+n e+p) 1 Subevent Thits>200, Vhits<6 R<500 cm, Ee>200MeV Likelihood cuts as the as shown below + Ee>200MeV cut is appropriate to remove e contribution from the dump that is hard to model. Mass(0) cut Likelihood e/ cut Likelihood e/ cut Signal region Signal region Cut region Cut region MC example plots here come from Booster beam MC Cut region Signal region Visible energy [MeV] Visible energy [MeV] Visible energy [MeV] Analysis of e events: do we see data/MC agreement?

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

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

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

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

  50. Summary of estimated backgrounds vs data e CCQE sample Looking quantitative into low energy and high energy region: 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  At this point systematic errors are large: we cannot saymuch 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.

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