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Signal Processing Algorithm Description & Evaluation with - - PowerPoint PPT Presentation

Signal Processing Algorithm Description & Evaluation with Simulation Brooke Russell Yale University DUNE APA Consortium Meeting October 2 nd 2017 Outline Last meeting Hanyu summarized single phase LArTPC signal formation and a full


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SLIDE 1

Signal Processing

Algorithm Description & Evaluation with Simulation

Brooke Russell Yale University DUNE APA Consortium Meeting October 2nd 2017

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SLIDE 2

Outline

  • Last meeting
  • Hanyu summarized single phase LArTPC signal formation and a full TPC

simulation

  • Today I’ll describe
  • a technique to extract the ionization electron signal
  • a quantitative evaluation of this method using the simulation
  • limitations to this work and ongoing work to address these shortcomings

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SLIDE 3

Illustration of topology dependent signal & intra- and inter-wire dependence of field response

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Motivates 2D deconvolution with careful ROI selection

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SLIDE 4

1D Deconvolution

  • Deconvolution has been used

in ICARUS and ArgoNeuT

  • 𝑁 𝑢′ = ׬

−∞ ∞ 𝑆(𝑢, 𝑢′) ∙ 𝑇 𝑢 𝑒𝑢

  • Original signal 𝑇 𝑢
  • Measured signal 𝑁 𝑢′
  • Response function 𝑆(𝑢, 𝑢′)
  • 𝑇 𝜕 =

𝑁(𝜕) 𝑆(𝜕) ⟹ 𝑇 𝜕 = 𝑁 𝜕 𝑆 𝜕 ∙ 𝐺(𝜕)

  • Filter function 𝐺(𝜕) needed to suppress high

frequency noise

  • Deconvolve relative to the time dimension

(1D)

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SLIDE 5

1D Deconvolution Technique Tension with Signal Formation Picture

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  • Fie

ield ld response

  • Shockley-Ramo Theorem

𝑗 = −𝑟𝐹𝑥 ∙ Ԧ 𝑤𝑟 න 𝑗 𝑒𝑢 = 𝑟𝑛 ∙ (𝑊

𝑛 𝑓𝑜𝑒 − 𝑊 𝑛 𝑡𝑢𝑏𝑠𝑢)

  • Can infer:
  • Shape and normalization
  • Time duration of induced

current

  • Induction range

The weighting field extends beyond a single wire region

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SLIDE 6

2D Deconvolution

  • Deconvolve with respect to time and wire dimensions
  • 𝑁𝑗 𝑢′ = ׬

−∞ ∞ … + 𝑆1 𝑢0 − 𝑢 ∙ 𝑇𝑗−1 𝑢 + 𝑆0 𝑢0 − 𝑢 ∙ 𝑇𝑗 𝑢 + 𝑆1 𝑢0 − 𝑢 ∙ 𝑇𝑗+1 𝑢 + ⋯ 𝑒𝑢

  • 𝑁𝑗(𝑢′) - measured signal from wire i,
  • 𝑇𝑗(𝑢) - signal within the boundaries of wire i, where ± a half pitch defines the wire boundaries
  • 𝑆𝑜(𝑢0 − 𝑢) - average response of wire i, where 𝑜 =∥ 𝑗 ∥
  • Fourier transform in matrix notation,

𝑁1 𝜕 𝑁2 𝜕 ⋮ 𝑁𝑜−1 𝜕 𝑁𝑜 𝜕 = 𝑆0 𝜕 𝑆1 𝜕 ⋯ 𝑆𝑜−2 𝜕 𝑆𝑜−1 𝜕 𝑆1 𝜕 𝑆0 𝜕 ⋯ 𝑆𝑜−3 𝜕 𝑆𝑜−2 𝜕 ⋮ ⋮ ⋱ ⋮ ⋮ 𝑆𝑜−2 𝜕 𝑆𝑜−3 𝜕 ⋯ 𝑆0 𝜕 𝑆1 𝜕 𝑆𝑜−1 𝜕 𝑆𝑜−2 𝜕 ⋯ 𝑆1 𝜕 𝑆0 𝜕 ∙ 𝑇1 𝜕 𝑇2 𝜕 ⋮ 𝑇𝑜−1 𝜕 𝑇𝑜 𝜕

  • Now, by inverting 𝑆 and applying software filters for the wire and time dimensions, respectively, we’ve

taken into account the induction range inherent to LArTPCs to extract charge

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SLIDE 7

2D Deconvolution

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  • Deconvolution amplifies low-frequency noise

for induction wire planes 𝑇 𝜕 = 𝑁(𝜕) 𝑆(𝜕) ⋅ 𝐺(𝜕)

  • Low frequency software filters are used to

find induction plane signals in the deconvolved waveform

  • Tight low-frequency filter for short

signals

  • Loose low-frequency-filter for

prolonged signals

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SLIDE 8

ROI Refinement

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SLIDE 9

Algorithm Description

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Qualitative Performance

  • 1D deconvolution
  • Signal smearing
  • Less efficiency for reconstructing

charge for tracks at large angle with respect to wire plane

  • 2D
  • Better recovers the true signal
  • More efficient recovery of charge

for difficult topologies

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SLIDE 11

Performance

Point Charge

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Deconvolution results of a point charge of 10k electrons simulated 1m from wires planes

  • Time smearing: about 2.7 ticks and 2.3 ticks for induction and collection planes, respectively
  • Wire smearing: due to long range of induction, more pronounced on U plane
  • Charge bias: mismatch in field response (in signal formation and deconvolution) is mitigated by diffusion

Percentage of total charge recovered (+ charge, - charge) Relative positive charge in percentage per wire

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SLIDE 12

Noise Induced Charge Resolution

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Bin-to-bin correlations on induction planes Noise-like on collection plane

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Noise Induced Charge Resolution

Total l Charge Resolution Wit ithin in th the Enti tire ROI Win indow Center Bin in Char arge Resolu lution Cor

  • rrespondin

ing to

  • Di

Different ROI win indows

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Line Charge Bias, Resolution & Inefficiency

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Cha Charge Bi Bias Significant in induction planes at large 𝜄𝑦𝑨, a ramification of bipolar cancelation Cha Charge Res esolu lutio ion Dominated by noise induced charge fluctuation, especially problematic from noise in induction plane magnified by bipolar response in deconvolution Ine Ineffic iciency Ratio of reconstructed charge to true charge

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SLIDE 15

Signal Processing Results on Data

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Point Sources Line Source

Fairly good charge matching across all three wire planes

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Signal Processing Results on Data

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  • Average waveform from tracks
  • f restricted angular range
  • Inter-plane charge matching
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SLIDE 17

Limitations

ROI Finding

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  • Failure to find ROI for large 𝜄𝑦𝑨 tracks is a common source of

inefficiency in current signal processing

  • Improving this is a current area of investigation
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SLIDE 18

Limitations 2D Field Resposes

  • We presently use Garfield to calculate

2D Field responses

  • Have residual limitations for modeling a

3D effect

  • Computing limitations make a direct 3D

calculation difficult; this is an area of active development

  • Data-MC response comparison

indicates there is room for further improvement

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2D Garfield simulation scheme illustration

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SLIDE 19

Summary

  • Presented a method for ionization electron charge extraction in single

phase LArTPCs

  • Evaluated the signal processing technique with a new full TPC

simulation

  • Provided explanation of current technique limitations and areas of

future development

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Backup Slides

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TPC Simulation

𝑋𝑏𝑤𝑓𝑔𝑝𝑠𝑛 = 𝐸𝑓𝑞𝑝𝑡𝑗𝑢𝑗𝑝𝑜 ⊗ 𝐸𝑠𝑗𝑔𝑢𝑗𝑜𝑕 ⊗ 𝐸𝑣𝑑𝑢𝑗𝑜𝑕 + 𝑂𝑝𝑗𝑡𝑓 ⨀𝐸𝑗𝑕𝑗𝑢𝑗𝑨𝑏𝑢𝑗𝑝𝑜

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Charge deposition input: Geant4 or WCT tool or manual

  • Ionization
  • Recombination
  • Electron attachment
  • Diffusion
  • Statistical fluctuation
  • Field response
  • Electronics response

Inherent electronics noise model

  • 2 MHz sampling
  • 2V max
  • 12 bit ADC
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SLIDE 22

Signal Formation

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  • Field response
  • Electronics response
  • Event topolo

logy

True charge in one wire region Reconstructed charge (using average response) in one wire region Reconstructed charge from center and neighboring wire regions Intra-wire field response dependence Inter-wire field response dependence

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SLIDE 23

Signal Formation

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  • Field response
  • Electronics response
  • Event topolo

logy

  • Results in topology-

dependent signals

𝜄𝑧 = 90° with 𝜄𝑦𝑨 varying 𝜄𝑦𝑨 = 0° with 𝜄𝑧 varying