1. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(1) Front End Electronics for the NOvA Neutrino Detector John Oliver, Nathan Felt Harvard University Long baseline neutrino experiment Fermilab (Chicago) to northern Minnesota (~800 km) 20 - 25 kTon “Far” and smaller “Near” detectors

2. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(2) ~ 640,000 channels of liquid scintillator / wavelength shifting fiber cells Readout by 32 channel Avalanche Photo Diodes (10 pf per pixel ) Gain ~ 100 @ -15C MIP = ~ 25 photoelectrons @ far end of cell  2,500 e / minimum ionizing signal Neutrino interactions only in 10  s spill every ~ 2 sec Signal dominated by cosmic rays ~ 400 Hz/pixel NOvA Far Detector

3. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(3) Readout Electronics & Noise APD noise Minimum noise dominated by APD leakage of ~ 1 – 2 nA @ -15C Dual Correlated Sampling would yield current (parallel) noise of ~100 e rms @  T ~ 1  s Front end electronics & noise Integrate signals in ASIC preamplifier with low noise density of ~ 1 – 2 nV/rt(Hz) 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 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)

4. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(4) 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 run @ 16 MHz to sample each channel at 500 ns/sample ASIC’s four outputs are continuously digitized by quad ADC (AD41240 CERN/”ChipIdeas”) and sent to FPGA ~ 20,000 FEBs in NOvA Far Detector (~ 1 per ton of detector)

5. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(5) TfTf TrTr 8:1 Mux TfTf TrTr TfTf TrTr TfTf TrTr 8 8 8 8 32 ch ASIC (See talk by Tom Zimmerman) 16 MHz multiplexers 2 Msps per channel Adjustable risetime & falltime

6. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(6) DAQ Heirarchy – 64 FEBs to one “Data Concentrator Power Distribution Power Distribution Data Concentrator Data Concentrator FEBs Beam DAQ

7. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(7) DAQ Heirarchy – con’t 324 Data Concentrators 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) 90% - 95% of timestamps arrive within 1 sec. Efficiency is ~ 100% in < 10 sec. DCM DAQ & Timing

8. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(8) Signal Processing - Pulseheight 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)

9. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(9) Signal Processing – Pulseheight (con’t) In general  FIR filter with modest (2 – 8) number of coefficients Easily implemented in FPGA (multipliers, accumulators) Coefficients “learned” by DSO (Digital Oscilloscope) mode during calibration Take ~ 1 ms sample of baseline @ 500 ns / sample (2k points  4k bytes) Analysis of baseline noise yields  Equivalent APD leakage current  Compute enc vs  T using dual correlated sampling and fit to sqrt(  T)  Amplifier equivalent input noise density, e n  Compute enc vs risetime and fit to 1/sqrt(T R )  Optimal filter coefficients (from noise autocorrelation function)

10. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(10) Filter simulation & testing Synthesize signals and noise traces parameterized by  Equivalent APD leakage current, I L  Equivalent preamp input noise density e n  Pulseheight, risetime & falltime constants  Noise trace synthesis done by numerical integration (iterate finite diff eqn) Baseline noise and signals from prototype electronics ( Can’t “dial” noise components ) 100 us

11. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(11) Example : Quad sampling with 1 st pair  T = 1 us 2 nd pair  T = 3 us Variable weighting factor 0 <  < 1 Optimal point  ~ 0.4 Data taken from prototype electronics so can’t choose noise components Result is ~ 20% improvement over DCS with prototype electronics (not ASIC) In practice, 6 – 8 terms works well

12. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(12) Timing extraction 40 us Trailing edge contains as much timing information as the leading edge Timing extraction by “matched filtering” FIR filter performs correlation of “ideal” pulse shape with incoming pulse Filter output is ~ symmetrical signal whose peak is a measure of time of arrival Peak is found by “interpolation” filter (“upsampling”) 100 us

13. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(13) Interpolation (“upsampling”)

14. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(14) Timing resolution vs pulseheight (SNR) NOvA “Worst case” SNR NOvA “Typical” SNR Measurements made with test electronics Final results will depend on APD/ASIC noise spectrum

15. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(15) Triggering Triggering is done on output of pulseheight filter Pulse shape discrimination  “Signal don’t look like noise” Noise hits tend to stay over threshold for 1 clock duration only Triggering on signal over threshold for 2 clock cycles can reduce noise hit rate by 10 x

16. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(16) NOvA Near Detector Readout Near Detector is small version of Far Detector Location (End of NUMI beam line @ Fermilab) Shorter cells  higher photoelectron yield  much better SNR ( > 2x) Very low cosmic ray rates ( ~ 100 meters earth overburden) Very high rate of beam events in 10 us spill Initial simulations ~ 50 direct + 150 rock muon events per spill High probability of event overlaps in detector Requirements under study (simulations) but likely “several” microsecond 2-track separation Best case scenario  Maintain 500 ns sampling, filter modifications for good 2-track separation, take advantage of better SNR  Firmware modifications only Worst case scenario  Increase sampling to 250 ns or less.  ASIC mods  4:1 multiplexing  2 or more ADCs per board Other scenarios under study

17. 17 - 20 May, 2006FEE 2006 / Perugia, Italy(17) Conclusions Flexible architecture : Continuous digitization + DSP  2 MSPS DSO on every channel : Local analysis in FPGA  Algorithms optimized in-situ 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  1 FEB  ~ 100 Euro  1 ton of detector Un-advertised science bonus : If supernova occurs in our galaxy, NOvA will see it clearly : ~ 1,000s of neutrinos detected within 10 – 20 sec. with characteristic time structure. ( ~1% prob/yr )