21-Aug-06DoE Site Review / Harvard(1) Front End Electronics for the NOvA Neutrino Detector John Oliver Long baseline neutrino experiment Fermilab (Chicago) to northern Minnesota (~800 km) ~20-25 kTon “Far” and smaller “Near” detectors (Number given for 20 kTon in this document)

21-Aug-06DoE Site Review / Harvard(2) Electronics & DAQ Organization L2 Manager – L. Mualem / U. Minn Electronic Project Engineer – J. Oliver / Harvard Front End Boards (FEBs)  L3 Manager – J.Oliver  Elect Eng – N. Felt  Technician / designer – S. Harder  Test software – J. Boehm DAQ – FNAL Power Distribution & Slow Controls – U. Va

21-Aug-06DoE Site Review / Harvard(3) ~ 500,000 channels of liquid scintillator / wavelength shifting fiber cells Readout by 32 channel Avalanche Photo Diodes (10 pf per pixel ) Gain ~ -15C MIP = ~ 25 far end of cell  2,500 e / minimum ionizing signal Neutrino interactions in 10  s spill every ~ 2 sec Signal dominated by cosmic rays ~ 400 Hz/pixel NOvA Far Detector

21-Aug-06DoE Site Review / Harvard(4) DAQ Heirarchy – 64 FEBs to one “Data Concentrator Power Distribution Power Distribution Data Concentrator Data Concentrator FEBs Beam DAQ

21-Aug-06DoE Site Review / Harvard(5) DAQ Hierarchy 250 Data Concentrator Modules connected to CPU Farm via ethernet switches & timing cables. All pixel hit data sent through Concentrators to CPU farm – Timing signal take reverse path Each “hit”  32 bit timestamp (62.5 ns / bin, synched to Global timing system) + pulseheight Global timing system with GPS receiver to correlate timing with NUMI beam spills All data are buffered for ~ 10 seconds NUMI beamline spill is GPS timestamped & transmitted to Far Detector via internet (as is now done in MINOS) In 10 sec buffer period, internet efficiency of spill signal is ~ 100% DCM DAQ & Timing FEB GPS Receiver

21-Aug-06DoE Site Review / Harvard(6) Front End Board (FEB) Architecture APD Module TE Cooler Control ADC FPGA DAQ ASIC Thermoelectric cooler maintains – 15C at APD ASIC integrates & shapes 32 signal channels from APD Selectable risetime & falltime constants ASIC’s 8:1 Multiplexers 16 MHz to sample each channel at 500 ns/sample ASIC’s four outputs are continuously digitized by quad 16 Msps and sent to FPGA ~ 16,000 FEBs in NOvA Far Detector

21-Aug-06DoE Site Review / Harvard(7) Readout Electronics & Noise APD noise Minimum noise dominated by APD leakage of ~ 1 – 2 -15C Dual Correlated Sampling would yield current (parallel) noise of ~100 e  T ~ 1  s  Keep APDs cold! Front end electronics & noise Integrate signals in ASIC preamplifier with low noise Dual Correlated Sampling with controlled risetime constant of a few hundred ns would yield ~ 150 e rms  Readout objective is to minimize both noise components Readout strategy Sample & digitize each APD integrated signal continuously every 500 ns Digitize all samples off-chip (low cost external ADCs) & send to FPGA Perform multiple correlated sampling filters in local FPGA Extract pulseheight & timestamp locally for each hit Find “in spill” hits by timestamp in DAQ system (no trigger or spill signals on Front End Board)

21-Aug-06DoE Site Review / Harvard(8) TfTf TrTr 8:1 Mux TfTf TrTr TfTf TrTr TfTf TrTr ch ASIC (T. Zimmerman / FNAL) 16 MHz multiplexers 2 Msps per channel Adjustable risetime & falltime Status  Prototypes fabricated on TSMC 0.25u CMOS  Tested & work as per simulations

21-Aug-06DoE Site Review / Harvard(9) Signal Processing – Pulseheight & Timing Use multiple correlated pairs of samples centered on leading edge Weight the pairs by optimal coefficients Optimal coefficients depend on noise spectrum  Parallel noise favors inner pair (small sampling time, small no of samples)  Series noise favors multiples pairs (long risetime constant, large number of samples) Calibration  “Learn” noise spectrum by sampling baseline (~ Msps)  Compute optimal digital filter parameters offline  Download parameters back to FEBs

21-Aug-06DoE Site Review / Harvard(10) Filter simulation & testing DSP filter tests  Measurements from prototype electronics  Simulated noise pulses Advantage  Can easily vary noise sources (leakage current, thermal noise) 100 us

21-Aug-06DoE Site Review / Harvard(11) DSP example – Timing extraction (N. Felt) Matched filter  Convolute signal with stored “ideal” pulse shape Convolution yields sharply peaked function of time Apply interpolation filter  ~ 60ns timing resolution with ~ 500ns sampled signal (test data)

21-Aug-06DoE Site Review / Harvard(12) Summary Flexible architecture : Continuous digitization + DSP  2 MSPS DSO on every channel : Local analysis in FPGA  Algorithms optimized off-line for pulseheight & timing  In-situ diagnostics: Opens, shorts, APD high voltage, etc NUMI beam spill signal not required “in-time” at FEBs  Spill signal sent to Far Detector via internet after spill  All in-spill data sorted for time-stamp and saved to disc Low cost Front End Electronics Recent production electronics experience at Harvard  ATLAS MDT Front End Electronics  75k chips produced & tested  16k Mezzanine cards produced *, tested, and delivered to ATLAS * We gratefully acknowledge Weizmann Institute for Mezz Card production in Israel