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17 - 20 May, 2006 17 - 20 May, 2006 FEE 2006 / Perugia, Italy FEE 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

17 - 20 May, 2006FEE 2006 / Perugia, Italy(1) Front End Electronics for the NOvA Neutrino Detector John Oliver, Nathan Felt Harvard University Long baseline

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Page 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

17 - 20 May, 200617 - 20 May, 2006 FEE 2006 / Perugia, ItalyFEE 2006 / Perugia, Italy ((11))

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

Page 2: 17 - 20 May, 2006FEE 2006 / Perugia, Italy(1) Front End Electronics for the NOvA Neutrino Detector John Oliver, Nathan Felt Harvard University Long baseline

17 - 20 May, 200617 - 20 May, 2006 FEE 2006 / Perugia, ItalyFEE 2006 / Perugia, Italy ((22))

• ~ 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

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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)

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Front End Board (FEB) Architecture

APDModule

TE CoolerControl

ADC FPGADAQ

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)

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Tf

Tr 8:

1 M

ux8:

1 M

ux

Tf

Tr 8:

1 M

ux8:

1 M

uxTf

Tr 8:

1 M

ux8:

1 M

ux

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Tr 8:

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32 ch ASIC (See talk by Tom Zimmerman)

• 16 MHz multiplexers• 2 Msps per channel• Adjustable risetime & falltime

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DAQ Heirarchy – 64 FEBs to one “Data Concentrator

PowerDistribution

PowerDistribution

DataConcentrator

DataConcentrator

FEBs

Beam

Beam

Beam

DAQ

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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

DCM

DCM

DAQ&

Timing

Page 8: 17 - 20 May, 2006FEE 2006 / Perugia, Italy(1) Front End Electronics for the NOvA Neutrino Detector John Oliver, Nathan Felt Harvard University Long baseline

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Signal Processing - Pulseheight

6 5 4 3 2 1 0 1 2 3 4 5 6

Sampled waveform

g x( )

g n( )

• 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)

Page 9: 17 - 20 May, 2006FEE 2006 / Perugia, Italy(1) Front End Electronics for the NOvA Neutrino Detector John Oliver, Nathan Felt Harvard University Long baseline

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Signal Processing – Pulseheight (con’t)

• In general FIR filter with modest (2 – 8) number of coefficients

k

knin

knout VV

• 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, en

Compute enc vs risetime and fit to 1/sqrt(TR) Optimal filter coefficients (from noise autocorrelation function)

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Filter simulation & testing

• Synthesize signals and noise traces parameterized by Equivalent APD leakage current, IL

Equivalent preamp input noise density en

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

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Example : Quad sampling with • 1st pair T = 1 us• 2nd 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

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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

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Interpolation (“upsampling”)

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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

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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

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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

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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 )