 13 Readout Electronics

13 Readout Electronics A First Look 28-Jan-2004

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 J. Pilcher

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 J. Pilcher

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. J. Pilcher

Channel Response Characteristics J. Pilcher

KamLAND Signals 128 samples of 1.5ns 3 gain scales (most events just use 20X scale) Gain 1/2 Gain 4X Gain 20X J. Pilcher

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 J. Pilcher

KamLAND Vertex Reconstruction • Mean reconstructed position depends on photon energy • Apply energy dependent correction J. Pilcher

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 J. Pilcher

KamLAND Energy Reconstruction J. Pilcher

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 J. Pilcher

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) J. Pilcher

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 J. Pilcher

Performance of TileCal System Time reconstruction is excellent amplitude independent J. Pilcher

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 J. Pilcher

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 J. Pilcher

 13 Readout Electronics