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Performance of a Magnetised Scintillating Detector for a Neutrino Factory. Scoping Study Meeting Rutherford Appleton Lab Tuesday 25 th April 2006 M. Ellis & A. Bross. Outline. Detector description Simulation Digitisation Data set Example events Reconstruction Performance:
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Performance of a Magnetised Scintillating Detector for a Neutrino Factory Scoping Study Meeting Rutherford Appleton Lab Tuesday 25th April 2006 M. Ellis & A. Bross
Outline • Detector description • Simulation • Digitisation • Data set • Example events • Reconstruction • Performance: • Points per track • Track Length • Position Resolution • Reconstruction efficiency • Charge mis-ID rate • Momentum resolution • P from track length • Electron identification • Electron reconstruction • Next steps
Detector Description • All scintillator box (15m x 15m x 100m) sitting inside a magnetic field (e.g. ATLAS style air toroid). • Basic unit is a triangular pyramid: • base 3 cm • height 1.5 cm • length 15 m • Uniform magnetic fields simulated: • 0.15 T • 0.30 T • 0.45 T • Digitisation takes into account dE/dx in scintillator slab and reasonable light yield, but does not take into account propagation effects (small effect).
Full Detector Total mass: 22.5 kT 100 m 15 m 15 m
Simulation • GEANT4 (6.2.p02) simulation • Each slab is modeled in the G4 description (parameterised solids to build an “X” and “Y” plane. Many modules containing one of each are placed down the z axis). • All relevant physics processes are switched on. • Magnetic field is simulated as a uniform field. • Primary particles are generated as either positrons or positive muons. • Three momentum ranges studied: • “Low”: 100 MeV/c – 500 MeV/c initial momentum • “Medium”: 500 MeV/c – 2.5 GeV/c initial momentum • “High”: 2.5 GeV/c – 12.5 GeV/c initial momentum • Momentum distribution is flat in all three cases • Initial position just inside the “entrance” to the detector (i.e. upstream if there were a neutrino beam). • Flat initial position between +10 and -10 cm in X and Y • Initial direction gaussian with a width of 100 mrad in X’ and Y’
Digitisation • Detector is broken up into: • 3333 Modules (X and Y plane) • Each plane contains 1000 slabs • Total: 6.7M channels (single-ended readout) • All hits on the same slab are collected into a single Digit. • dE/dx in scintillator is scaled to be equivalent to 20 Photo Electrons for a muon passing through the full height of the pyramid (i.e. 1.5 cm). • Energy resolution of the readout electronics is simulated to be 2.0 Photo Electrons • 0.5 Photo Electron cut is applied after merging hits into a single digit. • No timing information is simulated • potential improvement for future runs • may well be useful for pattern recognition! • requires more serious thought about plausible front end electronics choices
Data Set • Muons: • Approximately equal statistics for the three magnetic fields: • Low momentum: 100k events each • Medium momentum: 45k events each • High momentum: 10k events each • Positrons: • Only simulated in a 0.3T field: • Low momentum: 100k events • Medium momentum: 49k events • High momentum: 14k events • Total 635k events took approximately 3 CPU-days and occupies 8 GB (zipped). • Potential for higher statistics studies without too much difficulty. • Main limitation is file size of output file.
Reconstruction • Pattern recognition cheats using Monte Carlo information: • Muons – select hits from primary muon (discard delta rays). No attempt is made to find kink from delta production. • Positrons – select all hits in the event (i.e. complete shower). • Real pattern recognition will need to be written to study neutrino events (primary lepton vs hadronic jet, etc). • Space points reconstructed using “ADC” information (no timing is digitised) • Tracks are built from all space points under two hypotheses: • positive charge • negative charge • Momentum resolution, efficiency, etc are determined from the fit to a positive charge. • Charge mis-identification rate is found by counting the number of tracks for which the 2 of the fit as a negative particle is better than that for a positive particle.
Reconstructed High P Muon 10 GeV/c Muon Blue points: Hits from the primary muon Black points: All other hits
Reconstructed High P Positron 10 GeV/c Positron Blue points: Hits from the primary positron Black points: All other hits
Performance Red: 0.15 T Magnetic Field Green: 0.30 T Magnetic Field Blue: 0.45 T Magnetic Field
Position Resolution Position resolution ~ 4.5 mm
Reconstruction Efficiency Red: 0.15 T Magnetic Field Green: 0.30 T Magnetic Field Blue: 0.45 T Magnetic Field
Charge mis-Identification Red: 0.15 T Magnetic Field Green: 0.30 T Magnetic Field Blue: 0.45 T Magnetic Field
Momentum Resolution Red: 0.15 T Magnetic Field Green: 0.30 T Magnetic Field Blue: 0.45 T Magnetic Field
Momentum from Track Length 12% Resolution Red: 0.15 T Magnetic Field * Track fit ° Track length Green: 0.30 T Magnetic Field * Track fit ° Track length Blue: 0.45 T Magnetic Field * Track fit ° Track length
Electron Identification Red: Positrons (0.3T) Blue: Muons (0.3T)
Electron Reconstruction Red: 0.30 T e+ Full Track Blue: 0.30 T e+ Short Track Green: 0.30 T m+ Full Track
Summary • Muons are reconstructed with a high efficiency (i.e. if Pattern Recognition succeeds, the track fit is good) above about 200 MeV/c • A combination of momentum determination by track fit at low momentum and track length at high momentum gives an overall resolution that is reasonably flat at about 12%. • Positrons are reconstructed with a resolution which is slightly worse than that for muons, however this has not been optimised. • Charge mis-identification rate is of order 10% at very low and very high momentum and drops to as little as 0.1% at 500 MeV/c. • Electron and Muon identification through the measurement of dE/dx in the scintillator appears possible above about 700 MeV/c. • More work required in several areas: • Muon track fit can be improved at medium-high momentum, should improve momentum resolution • Track fit (dE/dx model, MCS, etc) has not been optimised for electrons • Realistic pattern recognition needs to be implemented (especially for positrons, fit the clear track before it showers).
Next Steps • Tune muon reconstruction to get better fit quality across full momentum range. • Study Detector optimisations: • Air gap between modules (i.e. same mass, greater length). • Double ended readout? • TDC as well as ADC information (very useful for PR and Reconstruction) • Implement real pattern recognition to identify tracks: • Search for multiple muon-like tracks in an event • Search for showers and jets • Implement calorimetry in reconstruction • Repeat study with single tracks • Simulate neutrino interactions • Study detector performance after reconstructing nm and ne events.