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13 Readout Electronics A First Look 28-Jan-2004
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January 28, 2004J. Pilcher2 Requirements Digitize charge seen by each PMT Energy reconstruction Provide timing of signal for each PMT Position reconstruction Provide trigger for DAQ Physics triggers Neutrinos (prompt EM energy, delayed neutron energy) Backgrounds (to study and subtract) Muons Electronic calibration triggers (test pulses) Source/laser/LED calibration triggers Random triggers
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January 28, 2004J. Pilcher3 Comparisons KamLAND is important reference point Same reaction channel Scintillator-based detector Recent design But much larger target volume ~20 times larger KamLAND resolutions Energy 7.5% / Sqrt[E(MeV)] 2% 5.7% at 2 MeV Position 25cm 5 cm –timing resolution 2.0 ns RMS after charge correction
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January 28, 2004J. Pilcher4 KamLAND Electronics Berkeley Analog Waveform Transient Digitizer (AWTD) For 1325 PMTs (32% coverage) Sample every 1.5ns For signals above 1/3 pe 3 gain ranges (0.5, 4, 20) Store analog samples in switched capacitor arrays until trigger 128 samples deep (200 ns) 10-bit ADC ~15 bit dynamic range Converts 128 samples in 25 s.
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January 28, 2004J. Pilcher5 Channel Response Characteristics
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January 28, 2004J. Pilcher6 KamLAND Signals 128 samples of 1.5ns 3 gain scales (most events just use 20X scale) Gain 1/2 Gain 4X Gain 20X
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January 28, 2004J. Pilcher7 KamLAND Vertex Reconstruction Calibrate timing of individual PMT channels with variable laser pulses at center of detector Time offsets T vs Q Measure performance for physics with sources along z- axis
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January 28, 2004J. Pilcher8 KamLAND Vertex Reconstruction Mean reconstructed position depends on photon energy Apply energy dependent correction
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January 28, 2004J. Pilcher9 KamLAND Energy Reconstruction Set gains of PMTs using LEDs Equalize 1 pe peaks to 184 counts Must correct for variations in storage capacitors All signals converted to equivalent photoelectrons Convert to energy using calibration sources
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January 28, 2004J. Pilcher10 KamLAND Energy Reconstruction
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January 28, 2004J. Pilcher11 Fresh look at Readout Electronics Avoid ASICs if possible (local bias) Long development time Not cost effective in small volume Do not profit from evolution of chips in the commercial sector Main advantage size and possibly performance and functionality Continued performance growth in commercial ADCs and FPGAs (PLD) Popular building blocks for many applications
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January 28, 2004J. Pilcher12 Fresh look at Readout Electronics Does one need detailed pulse shape for E and t? Pulse shape discrimination can resolve photons from neutrons Depends on scintillator Some exhibit this property and some do not May depend on light collection from target –Reflections could obscure the effect Much simpler if one can do shaping of input signal Output amplitude proportional to input charge Can be done with passive elements (no noise added)
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January 28, 2004J. Pilcher13 ATLAS TileCal Approach For ATLAS TileCal 20 ns PMT signals converted into 50-ns-wide standard shape Amplitude proportional to input charge Slower signal can be handled by commercial ADCs (+40 megasamples per second) Analysis process fits shape to extract amplitude and time
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January 28, 2004J. Pilcher14 Performance of TileCal System Time reconstruction is excellent amplitude independent
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January 28, 2004J. Pilcher15 Alternatives Use LBNL AWTD Likely if they join the collaboration Possibly an updated version Build a system based on a flash ADC Eg. Maxim MAX1151 8 bit flash 750 MHz (sample every 1.3 ns) Power 5.5W each Need 3 per PMT for dynamic range Use 40 MHz “system” clock à la LHC Easy to distribute on optical fiber if LHC hardware used Generate local vernier clock synced to system clock Tale 16 samples for every 25 ns period of system
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January 28, 2004J. Pilcher16 Alternatives Build integrating system as in TileCal The next steps Test LHC system reading out scintillator test cell Look at pulse shape discrimination with test cell Continue to think about electronics Trigger –Can it be derived from digital data, thereby avoiding a second signal branch Consult with Harold
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