?13 Readout Electronics

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?13 Readout Electronics

• A First Look
• 28-Jan-2004

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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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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 / SqrtE(MeV) ? 2 ? 5.7 at 2 MeV
• Position
• 25cm ? 5 cm
• timing resolution 2.0 ns RMS after charge
  correction

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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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Channel Response Characteristics
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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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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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KamLAND Vertex Reconstruction

• Mean reconstructed position depends on photon
  energy
• Apply energy dependent correction

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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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KamLAND Energy Reconstruction
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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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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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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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Performance of TileCal System
Time reconstruction is excellent amplitude
independent
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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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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