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CRT Detector Simulation Andrew Olivier 7/25/2018 1 CRT Simulation - PowerPoint PPT Presentation

CRT Detector Simulation Andrew Olivier 7/25/2018 1 CRT Simulation Plan artDAQ Particle Generator Detector Simulation Geometry Timing CRT Decoder MCTruth Energy Deposit Particle Transport CRT detected in largeant Trigger


  1. CRT Detector Simulation Andrew Olivier 7/25/2018 1

  2. CRT Simulation Plan artDAQ Particle Generator Detector Simulation Geometry ● Timing CRT Decoder MCTruth ● Energy Deposit Particle Transport ● CRT detected in largeant Trigger ↔ ● Channel mapping AuxDetSimChannel CRT::Trigger Assns MCParticle AuxDetSimChannel Trigger ↔ Track Assns Validation 2

  3. CRT in largeant  Started handful of 2GeV muons at -5000mm in z  Correct channel mapping → CRT channels line up with MCParticles  ProtoDUNE geometry sorts by y, then z, then x  Recommend encode detector channel in name X Y Strip Width Distance [mm] 3

  4. System to Simulate Discriminator: FPGA: PMT Anodes, 80 ns OR Fast Shaper PhotoCathode PreAmp Readout Slow Shaper Logic: 32 us  The CRT Self-Triggers  Reads out ALL channels when one triggers  Read out ADCs and one timestamp per trigger 4

  5. Detector Simulation Components  Timing  Energy → ADC  Readout all  Scintillator channels? efficiency  Data-taking window  Photocathode  Dead time  Amplification  “Traffic Jam”?  Shapers? 5

  6. Timing Simulation  Group hits into 62.5 MHz clock ticks  Search windows for hits above threshold  Readout if one channel above threshold  Keep accepting hits for readout window  Write data products  CRT::Trigger represents one readout  Assns with AuxDetSimChannel for backtracking  Skip forward by discriminator dead time 6

  7. Energy Simulation Strategies  Birks’ Law in AuxDets?  Noticed G4EmSaturation in optical model  Prefer to correct as close to Geant as possible  Parameterized  Detailed  Scintillator efficiency: Gaussian  Energy → PE from  Photocathode: Poisson calibration  Amplification: Simulate each  PE → ADC from anode? calibration  Shapers: TODO 7

  8. Framework Data Format  CRT::Trigger  CRT::Hit ↔ Trigger Associations  Get all information at  Don’t have to access once Hits  Have to associate Track  Can create CRT::Hit ↔ with entire readout recob::Track Assns  Fully encapsulates one  Have to access Assns → module readout → adds complexity simpler raw::ExternalTrigger CRT::Trigger A Assns A s s s s n n s CRT::Hit CRT::Hit CRT::Hit s CRT::Hit CRT::Hit CRT::Hit 8

  9. Output: What to Expect  CRT::Trigger  Module number = AuxDet ID  Timestamp  CRT::Hit  Channel number = AuxDetSensitive ID  ADC value  Assns CRT::Trigger ↔ AuxDetSimChannel  Backtracking handle if we need it 9

  10. Future Plans  Energy simulation  Only use ADC for muon selection?  Parameterized for now  Quantitative reason for complex model?  “Traffic jam” simulation?  Understand timing better  Cable lengths  Read out “empty” Triggers when ADC busy?  How often are tokens sent out? 10

  11. Backup: Minimize Framework Coupling  Motivation  Start testing software during commissioning  Later: gallery-powered monitoring?  Implementation  Data product in separate repository  Algorithms in separate repository  Coupled to data product  Some geometry queries outside of framework? 11

  12. Overview of CRT Hardware From Ed Blucher’s Collaboration Meeting slides  Left: 2 layers of 32 channels that are offset by ~25mm  Right: 4 frames with 4 modules each on front and back of cryostat 12

  13. CRT in the GDML File  dunetpc v06_76_00  Single frame on front and back of cryostat → Need 4  Modules’ dimensions look correct 13

  14. Backup: Visualization of CRT  Short red strips are my interpretation of CRT simulation channels  Want to map channel to position and look energy and timing 14

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