Advancements in Signal Processing for ProtoDUNE Experiment
The team, including Xin Qian, Chao Zhang, and Brett Viren from BNL, leverages past experience in MicroBooNE to outline a comprehensive work plan for signal processing in ProtoDUNE. Their focus includes managing excess noise, addressing non-functional channels, and evolving signal processing techniques to improve data analysis efficiency. The new signal processing procedure emphasizes long-range signal realization and topology-dependent waveform observations, enhancing the overall data processing for ProtoDUNE.
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Signal Processing Work for ProtoDUNE Xin Qian, Chao Zhang, and Brett Viren BNL 1
Outline Past experience of the team in MicroBooNE Thoughts on protoDUNE signal processing Work plan on protoDUNE 2
Past experience of the Wire-Cell team in MicroBooNE Excess noise identification and filtering in MicroBooNE https://arxiv.org/abs/1705.07341 Describing the new TPC signal processing algorithm: 2D deconvolution + ROI https://arxiv.org/abs/1802.08709 Data/MC comparison and proper dealing with various detailed signal processing issues observed in MicroBooNE TPC: demonstration of thorough understanding of the MicroBooNE TPC https://arxiv.org/abs/1804.02583 3
Excess Noise Filtering (1705.07341) Three major excess noise sources: ASIC low-voltage regulator (low frequency coherent noise) Cathode high voltage power supply (36, 108 kHz) Excess noise from PMT or other system (~900 kHz) 4
Excess Noise Filtering In general, dealing with one particular excess of noise is straight forward. The challenges show up when there are multiple sources of excess of noise Expect protoDUNE s excess of noise is much better than MicroBooNE (lessons learned from previous experiments) 5
Non-functional Channels Other major issues that encountered in MicroBooNE are Saturation of ASICs due to movement of wires Misconfigured channels (4.7 mV/fC + 1.0 us instead of 14 mV/fC + 2.0 us) Sleeping ASICs (due to start-up problem) All these should be much better in protoDUNE, as MicroBooNE s experience provides feedback to improved preamp ASIC design 6
Evolution of Signal Processing in MicroBooNE ~ 2 years of effort Drift time Wire number Two signal processing papers (~100 pages) to be submitted 7 Field response is based on 2D Garfield calculation, see Chao s talk on LArFCS
New Signal Processing Procedure (1802.08709) The key in developing the new signal processing algorithm is realizing the induced signal is long-range Leading to topology-dependent observed waveform 2D deconvolution taking into account both wire and time dimensions Additional ROI algorithm + software filter to reduce impact of intrinsic noise 8
Significant Improvements in Signal and Noise Simulation In order to quantitatively evaluate the new signal processing chain, significant improvements in signal and noise simulation is needed: New TPC signal simulation includes Long-range of induced current beyond the closest wire (+-10 wires in MicroBooNE) Position-dependent induced current within a wire pitch (1/10 of the wire pitch) New noise simulation utilizes Rayleigh distribution of the noise magnitude in the frequency domain Data-driven noise spectrum 10
Part II of Signal Processing Paper (1804.02583) Focus on the data/MC comparison in MicroBooNE Solutions to a few special signal processing issues encountered in MicroBooNE Pole-zero cancellation issue in preamp ASIC (much improved in protoDUNE) Signal processing in the shorted wire region (L1SP, do not expect such behavior in protoDUNE) ADC bit shift (happened in the data packing stage in MicroBooNE after warm ADC) Demonstration of the charge matching among three wire planes Foundation of the Wire-Cell reconstruction paradigm (https://arxiv.org/abs/1803.04850) 11
Imperfect Electronics Response Depending on the channels, the electronics response may contain long tails Calibrated by the pulser data and corrected in the signal processing 12
Data/MC Comparison Parallel track Large angle track 13
Signal Processing in the shorted wire region (L1 SP) In the shorted-Y region, a collection type signal (unipolar) can show up in the induction wires (expecting a bipolar response) The nominal signal processing would fail in this case leading to distorted deconvoluted signal A special signal processing based on the compressed sensing technique is developed to deal with this case 14
Demonstration of Charge Matching Since the same amount of ionization electrons are measured by each of the wire plane, the same should be reconstructed by different wire planes Line source Point source Foundation of the Wire-Cell reconstruction paradigm is demonstrated! 16
Thoughts on protoDUNE signal processing protoDUNE and MicroBooNE share many common hardware elements Most of them are improved based on lessons learned in MicroBooNE Expectations include: Much more uniform electronics response function Less non-functional preamp ASICs due to start-up problem Less misconfigured preamp ASICs No shorted wires Demonstration of <1% non-functional channels No saturations of preamp ASICs No excess noise due to cathode high voltage and low-voltage regulator 18
Thoughts on protoDUNE signal processing There are also new hardware elements in protoDUNE compared to MicroBooNE The cold ADC chip is not performing as desired Stuck codes in ADC (some data is lost) Need to deal with before the signal processing Non-linearity in conversion between ADC and voltage Need to be calibrated (bench data vs. in-situ calibration) As always, if there is one problem, it is relatively straight forward to deal with. If there are more, it is much harder to deal with Best scenario: no shorted wires, no excess of noise, preamp ASICs are all properly configured only need to deal with the cold ADC problem (can design a in-situ calibration plan on this, next page) Worst scenario: shorted wires + lots of excess noise + cold ADC problem may take many months of time to deal with 19
Thoughts of ADC Non-linearity Calibration ADC nonlinearity is essentially a nonlinear conversion between voltage and the ADC value In principle, the calibration is straight forward, if we know the input voltage, and measure the corresponding ADC values, we can build up this non-linearity curve The challenges of calibration is coming from the fact that we do not have a simple known input voltage in-situ Instead, we have the calibration pulser data, which go through the shaping of cold electronics, we have a (reasonably well-known) curve instead of known voltage Tunable knobs include (gain and shaping time of cold preamp chip, calibration pulse height, starting time of the calibration pulse) The last is important, as the digitization is performed at 2 MHz 20
Thoughts of ADC Non-linearity Calibration Take data at different calibration pulse gains and different starting time (assuming fixed gain and shaping time for the cold preamp) Pick up the data at the same ADC codes (same ADC nonlinearity) Correct gain for the data in order to map out the electronics response function Combine data at different ADC codes to be more efficient Use the calibrated electronics response function to calibrate the ADC nonlinearity (different ADC codes) Use the nonlinearity curve in the signal processing 21
Work plan for protoDUNE (I) Signal processing code (deconvolution + ROI) is available in larsoft Need to be properly configured for protoDUNE usage Integration of full TPC signal and noise simulation is almost ready Need to be configured for protoDUNE to test the signal processing code in simulation Need a new module prepared for excess noise filtering and ADC-related correction 22
Work Plan for ProtoDUNE (II) Connect the signal processing code with existing simulation Figure out some basic parameters , channel mapping, multiple APAs, time length and other inputs Replace the existing simulation with improved TPC signal/noise simulation Allows for quantitative checks on the signal processing Prepare the new module for ADC mitigation and excess noise filtering Auxiliary tools: event displays for experts, channel mapping Prepare for the worst, and hope for the best 23
