Analysis of  and e events from NuMI beamline at MiniBooNE Zelimir Djurcic (a) and Zarko Pavlovic (b) Columbia University (b) University of Texas Austin 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

Analysis Motivation Joint collaboration between MiniBooNE and NuMI. Observation and analysis of an off-axis beam. Measurement of /K components of the NuMI beam. Check of nm CCQE and ne CCQE interactions independent from Booster beam neutrinos. ne-rich sample to study MiniBooNE reconstruction and particle identification algorithms. Performing physics analysis complementary to MinibooNE analyses.

NuMI Beam and MiniBooNE Detector NuMI events (for MINOS) detected in MiniBooNE detector! MiniBooNE q p beam p, K 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.

The Woes of Knowing the n flux For wide-band(*) neutrino beams, Use MC simulation Particle production Focusing Measure in the detector Use some process with known cross section History has several examples of substantial corrections to these estimates ANL 12’ B.C. in ZGS horn beam FNAL 15’ B.C., 400GeV horn beam BNL E734, AGS horn beam Gargamelle, CERN PS beam Borodovsky et al., Phys. Rev. Lett. 68, 274 (1992) (BNL E776 ) got flux correct, right ‘out of the box’ (*) Narrow-band beams can more readily measure fluxes directly

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 n. n Detector First Proposed by BNL-E889 Decay Pipe q Target Horns

Future off axis experiments On-axis beam Off-axis beam Use off-axis trick for optimized nmne search NOvA NuMI off-axis beam 810km baseline 14.5mrad; Enu~2GeV T2K J-PARC 50GeV proton beam Use SK as Far detector 295km away 35 mrad; Enu~0.6GeV

NuMI Off-axis Beam at MiniBooNE K+ p+ stopped K+ stopped p+ Opportunity to demonstrate off-axis technique Known spectral features from p, K decays Expected energy spectra softened to within MiniBooNE acceptance

NuMI as a “ne Source” NuMI off-axis beam produces strong flux in both nm and ne flavors. The ne’s are helpful to study the MiniBooNE detector. Hopefully one can do some physics with a ‘enhanced’ ne beam NuMI on-axis ne ~1% NuMI off-axis ne ~6% BNB on-axis ne ~0.5% stopped K+ m+ K+

NuMI Spectrum is “Calibrated” Extensive experience with MINOS data MINOS acquired datasets in variety of NuMI configurations Tuned kaon and pion production (xF,pT) to MINOS data 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)

Two views of the same decays 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) MiniBooNE MiniBooNE MINOS MINOS

Neutrino Sources along NuMI beam Higher energy neutrinos mostly from particles created in target Interactions in shielding and beam absorber contributes in lowest energy bins Colors indicate the origin of  parents nm MiniBooNE diagram not to scale!

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

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

NuMI Beam and MiniBooNE Detector NuMI events (for MINOS) detected in MiniBooNE detector! MiniBooNE q p beam p, K 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.

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

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!

Particle Identification Čerenkov rings provide primary means of identifying products of  interactions in the detector m candidate nm n  m- p electron candidate ne n  e- p p0 candidate nm p  nm p p0 n n p0 → gg

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%

Analysis Algorithm

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.

Analysis Method log(Le/L) 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)>0 e-like events Example from MiniBooNE Oscillation Analysis.  e

 CCQE Analysis

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

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 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.

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!

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

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]

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 

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

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.

e CCQE Analysis

Backgrounds to e CCQE sample e CCQE (+n  e+p) 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. Therefore, before analyzing e CCQE we constrain the backgrounds by measurement in our own data.

Analysis of 0 events from NuMI beam Among the e-like mis-ids, 0 decays which are boosted, producing 1 weak ring and 1 strong ring is largest source. g g p0  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 p + g   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)

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!

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!

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 e candidates are showing up! Further Cross Check!

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

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 dirt sample. Dist-to-wall of tank along track [m] Visible energy [GeV]

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. Likelihood e/ cut Likelihood e/ cut Mass(0) cut Signal region Signal region Cut region MC example plots here come from Booster beam MC Cut region Cut region Signal region Visible energy [MeV] Visible energy [MeV] Visible energy [MeV] Analysis of e events: do we see data/MC agreement?

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.

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

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

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

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 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.

Summary and Future Steps

We performed analyses of neutrinos from NuMI beam observed with MiniBooNE detector. The sample analyzed here corresponds to 1.42x 1020 protons on NuMI target. We observed good description of the data by Monte Carlo 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

We are currently reprocessing and collecting more data In the future we will reduce e CCQE sample systematics constraining it with our large statistics  CCQE sample. 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 1020 P.O.T. collected by now.) These errors will be reduced PRELIMINARY

Backups

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

NuMI Off-axis Beam at MiniBooNE 1st opportunity to demonstrate off-axis technique Known spectral features from p, K decays Expected energy spectra softened to within MiniBooNE acceptance stopped p+ stopped K+ stopped K-

NuMI as a “ne Source” NuMI off-axis beam produces strong flux in both nm and ne flavors. The ne’s are helpful to study the MiniBooNE detector. Hopefully one can do some physics with a ‘pure’ ne beam (only a few past proposals on how to build such a beam).

Detector Modeling Detector (optical) model defines how light of generated event is propagated and detected in MiniBooNE detector Sources of light: Cerenkov (prompt, directional cone),and scintillation+fluorescence of oil (delayed, isotropic) Propagation of light: absorption, scattering (Rayleigh and Raman) and reflection at walls, PMT faces, etc. We have developed 39-parameter “Optical Model”. Strategy to verify model: External Measurements: emission, absorption of oil, PMT properties. Calibration samples: Laser flasks, Michel electrons, NC elastic events. Validation samples: Cosmic muons (tracker and cubes).

Low energy  cross sections Predictions from NUANCE - MC which MiniBooNE uses - open source code - supported & maintained by D. Casper (UC Irvine) - standard inputs - Smith-Moniz Fermi Gas - Rein-Sehgal 1 - Bodek-Yang DIS Imperative is to precisely predict signal & bkgd rates for future oscillation experiments We need data on nuclear targets! (most past data on H2, D2) MINOS, NuMI K2K, NOvA MiniBooNE, T2K Super-K atmospheric 

Cross-section uncertainties in the analysis MAQE, elosf 6%, 2% (stat + bkg only) QE  norm 10% QE  shape function of E e/ QE  function of E coh/res ratio NC 0 norm 25%   Nrate 7% BF EB, pF 9 MeV, 30 MeV s 10% MA1 25% MAN 40% DIS  25% Determined from MiniBooNE  QE data MiniBooNE data Other Experiments Determined from other experiments

Energy Calibration Michel electrons from  decay: We have calibration sources spanning wide range of energies and all event types ! Michel electrons from  decay: provide E calibration at low energy (52.8 MeV), good monitor of light transmission, electron PID 12% E res at 52.8 MeV 0 mass peak: energy scale & resolution at medium energy (135 MeV), reconstruction cosmic ray  + tracker + cubes: energy scale & resolution at high energy (100-800 MeV), cross-checks track reconstruction  e provides  tracks of known length → E

Are the neutrinos coming from the target? Geological Survey: Y=24.80,XZ=87.50.

Are the neutrinos coming from the target?

Are the neutrinos coming from the target? Measurement of exiting muons from neutrino interaction: Y=24.40, XZ=87.250.

 CCQE events: Q2 distribution

PID cuts efficiency for e CCQE events “Precuts” + Log(Le/L) + Log(Le/L) + invariant mass cut to rject low energy events near wall is: .not.(R>426 cm .and. Evisible<280)

Rejecting “-like” events log(Le/L)>0 favors electron-like hypothesis e CCQE  CCQE MC Separation is clean at high energies where muon-like events are long. This does not separate e/0 as photon conversions are electron-like.

Rejecting “0-like” events MC 0 mass cut log(Le/L) cut  NC 0 e CCQE

0 mass in 0 momentum bins 0 momentum bins are: 0<P <0.2, 0.2<P <0.3, 0.3<P <0.4, 0.4<P <0.5, 0.5<P <0.6, 0.6<P <0.8, 0.8<P <1.0, 1.0<P <1.2, 1.2<P <1.6,and P >1.6GeV/c2

0 momentum In an analysis of neutral 0 sample from Booster beam we used this distribution to tune MC to data: no need to do it here.

Selecting the dirt events Event pre-selection: 1 subevent Thits>200, Vhits<600 R<500 cm log(Le/L)>0.05 (e-like) Ee <550 MeV Distance-to-wall <250 cm m<70 MeV/c2 (not 0-like) True  energy:

Does the dirt sample constrain events in e CCQE sample? Lets use e CCQE cuts + “dirt” cuts: this is the overlap: cos e

Visible energy of e CCQE events: systematic uncertainty Visible energy in tank [GeV] Visible energy in tank [GeV]

Visible energy of e CCQE events with dirt cuts Visible energy in tank [GeV] Visible energy in tank [GeV]

cose and Ee of e CCQE events with dirt cuts

We have an indication of data over MC excess below 0. 9 GeV with 1 We have an indication of data over MC excess below 0.9 GeV with 1.4 significance: could it be due to a signal? Anomaly Mediated Neutrino-Photon Interactions at Finite Baryon Density (arXiv:0708.1281: Jeffrey A. Harvey, Christopher T. Hill, Richard J. Hill) CP-Violation 3+2 Model: Maltoni & Schwetz, arXiv:0705.0107 Extra Dimensions 3+1 Model: Pas, Pakvasa, & Weiler, Phys. Rev. D72 (2005) 095017 Lorentz Violation: Katori, Kostelecky, & Tayloe, Phys. Rev. D74 (2006) 105009 CPT Violation 3+1 Model: Barger, Marfatia, & Whisnant, Phys. Lett. B576 (2003) 303 New Light Gauge Boson: Nelson & Walsh, arXiv:0711.1363