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Zelimir Djurcic Physics Department Columbia University

Backgrounds in neutrino appearance signal at MiniBooNE. Zelimir Djurcic Physics Department Columbia University. Before the MiniBooNE: The LSND Experiment. LSND took data from 1993-98 - 49,000 Coulombs of protons - L = 30m and 20 < E n < 53 MeV .

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Zelimir Djurcic Physics Department Columbia University

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  1. Backgrounds in neutrino appearance signal at MiniBooNE Zelimir Djurcic Physics Department Columbia University Zelimir Djurcic-PANIC05-Santa Fe

  2. Before the MiniBooNE: The LSND Experiment LSND took data from 1993-98 - 49,000 Coulombs of protons - L = 30m and 20 < En< 53 MeV Saw an excess ofe:87.9 ± 22.4 ± 6.0 events. With an oscillation probability of (0.264 ± 0.067 ± 0.045)%. 3.8 s significance for excess. Oscillations? Signal: p e+ n n p  d (2.2MeV) Need definitive study of e at high m2 … MiniBooNE

  3. Search for e appearance in  beam Use protons from the 8 GeV booster Neutrino Beam <E>~ 1 GeV FNAL 8 GeV Beamline 50 m decay pipe 12m sphere filled withmineral oil and 1520 PMTslocated 500m from source decay region:   ,  K   “little muon counters:” measure K flux in-situ magnetic horn: meson focusing MiniBooNE detector  →e? movable absorber: stops muons, undecayed mesons magnetic focusing horn Zelimir Djurcic-PANIC05-Santa Fe e ???

  4. Neutrino Interactions in the Detector We are looking for e : nen  e-p Janet Conrad’s talk Current Collected data: 685k neutrino candidates (before analysis cuts) for 6.5 x 1020 protons on target (p.o.t.) • 48% QE • 31% CC +/- • 1% NC elastic • 8% NC 0 • 5% CC 0 • 4% NC +/- • 4% multi- If LSND is correct, we expect several hundred e (after analysis cuts) from for e oscillations. Zelimir Djurcic-PANIC05-Santa Fe

  5. Energy Calibration  e We have calibration sources spanning wide range of energies and all event types ! Michel electrons prod 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 provides  tracks of known length → E

  6. Particle Identification Čerenkovrings provide primary means of identifying products of  interactions in the detector beam m candidate nmn m- p Michel e- candidate nen  e-p beam p0 candidate nmp nm pp0 n n p0→ gg ring profile → can distinguish particles which shower from those which don’t

  7. Background to e appearance signal Comes from: -Misidentification of ’s in charged current  events as electrons. -Intrinsic e’s in beam. -Misidentification of 0’s in neutral current  events as electrons. -Radiative decays of . • Separation of  from e events • Exiting  events fire the veto • Stopping  events have a Michel electron after a few sec • Also, scintillation light with longer time constant  enhanced for pions and protons (high dE/dx) • Čerenkov rings from outgoing particles • Shows up as a ring of hits in the phototubes mounted inside the MiniBooNE sphere • Pattern of phototube hits tells the particle type Zelimir Djurcic-PANIC05-Santa Fe

  8. Intrinsic e in the beam p+ m+ nm e+ nenm K+p0 e+ne KLp-e+ne Monte Carlo Small intrinsicne rate  Event Ratione/nm=6x10-3 • nefromm-decay • Directly tied to the observednminteractions • Kaon rates measured in low energy proton production experiments • HARP experiment (CERN) • E910 (Brookhaven) • MiniBooNE Data • “Little Muon Counter” measures • rate of kaons in-situ See Robert Nelson’s talk for details !

  9. Production of the 0 ’s e appearance: 0 production important because background to →e if ’s highly asymmetric in energy or small opening angle (overlapping rings) can appear much like primary electron emerging from a e QE interaction! signal 0 background Resonant 0 production  N  N=(p,n) 0 N’ Coherent 0 production  A  A 0 p0→g g In addition to its primary decay N, the  resonance has a branching fraction of 0.56% to N final state. Zelimir Djurcic-PANIC05-Santa Fe

  10. Reconstruction and PID Various algorithms (MLL, ANN, BDT) used to optimize PID, to achieve good: • Robustness • Efficiency of PID separation Boosted decision trees: • Go through all PID variables and find best • variable and value to split events. • For each of the two subsets repeat the process • Proceeding in this way a tree is built. • Ending nodes are called leaves. • After the tree is built, additional trees are • built with the leaves re-weighted. • The process is repeated until best S/B • separation is achieved. Reference NIM A 543 (2005) 577. Zelimir Djurcic-PANIC05-Santa Fe

  11. Boosting PID Algorithm Neural Network Efficiency of PID separation example: muon / electron identification, measured with cosmic ray muons and associated decay electrons, for two PID algorithms under study PRELIMINARY Boosting Decision Tree PRELIMINARY Muons Electrons Zelimir Djurcic-PANIC05-Santa Fe

  12. Important Cross-check… … comes from NuMI events detected in MiniBooNE detector! Remember that MiniBooNE conducts a blind data analysis! We do not look in MiniBooNE data region where the osc. e are expected… We get e,  , 0 , +/- , ,etc. events from NuMI inMiniBooNE detector, all mixed together Use them to check our e reconstruction and PID separation! MiniBooNE NuMI events serve as gold mine to verify our analysis! Decay Pipe Beam Absorber See Alexis Aguilar-Arevalo’s talk for details !

  13. Look for appearance of e events above background expectation Use data measurements both internal and external to constrain background rates Appearance Signal SignalMis IDIntrinsic e • Fit to E distribution used to separate background from signal. Event Class Cross-check K+ HARP,LMC,External Data K0 E910,MiniBooNE Data External Data  MiniBooNE Data 0 NuMI,MiniBooNE Data Other(,etc) NuMI,MiniBooNE Data Zelimir Djurcic-PANIC05-Santa Fe

  14. Dm2 = 1 eV2 Dm2 = 0.4 eV2 MiniBooNE Oscillation Sensitivity • Oscillation sensitivity and measurement capability • Data sample corresponding to 1x1021 pot • Systematic errors on the backgrounds average ~5% Zelimir Djurcic-PANIC05-Santa Fe

  15. Conclusion and Prospects Background to e oscillation signal is well understood. Most backgrounds can be constrained with MiniBooNE data.  Background will be constrained to allow the signal to be extracted, if present. • At the current time have collected 6.5x1020 p.o.t. • Plan is to “open the box” when analysis is ready  Current estimate is not before end of 2005 • This leads to the question of the next step • If MiniBooNE sees no indications of oscillations withnm  Need to run withnm since LSND signal wasnmne • If MiniBooNE sees an oscillation signal  Then …………(stay tuned).

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