Aug 22, 2019 Calorimeter

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Meeting Time: 11:00 a.m.

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Participant Direct Lines

  • JLab Phone in CC L207 is 757-269-7084 (usual room)
  • JLab Phone: in CC F326 is 757-269-6460
  • Phone in the Regina Video-conference Suite is 306-585-4204
  • Athens Phone: in Christina's office is 011-30-210-727-6947


  1. FCAL HDFCAL log book
  2. BCAL HDBCAL log book

Goals for Calorimetry Group

  1. Determine preliminary photon reconstruction efficiencies as a function of E, phi and theta in data and simulation with a point-to-point precision of at least 5%.
  2. Measure systematics of pi0/eta mass calibration as a function of detector position to a precision of at east 5 MeV.
  3. Demonstrate agreement of photon reconstruction efficiency and resolution between data and simulation as a function of E, phi and theta to within 5%.

Action Items

Short term items:

  1. Investigate uniqueness tracking for efficiency calculations in calorimeters (Jon)
  2. Complete Calorimeter work packages

Long term items:

  1. From Mike's work: -cos(phi) type dependence in the data and a phi dependence at the downstream end of the bcal. See Sep 21, 2017 Calorimeter Meeting.
  2. FCAL: It has been noticed that the pi0 mass shifts when the LED pulser runs at high rate. This is still not understood. See Log Entry 3595928 and references. Several runs have been taken in raw mode. These runs exhibit the shift in pi0 mass with LED running at 1 kHz. There is a need to analyze these to try to determine the cause:
    1. 50634 - FCAL Green LED: 1kHz, 29 V, Livetime is 9%, 1.7 M events
    2. 50635 - FCAL Violet LED: 1kHz, 22 V, Livetime is 9%, 1.4 M events
    3. 50636 - FCAL Blue LED: 1kHz, 15 V, Livetime is 9%, 1.5 M events

Tentative Agenda

  1. Announcements
  2. Action Items
  3. Run Updates
    1. FCAL
    2. BCAL
  4. Calibrations
  5. Monitoring
  6. Efficiencies
  7. Simulations
  8. BCAL Deep Learning
  9. NIM articles
  10. Any other business


Attending: Elton, Mark, Jon (JLab); Karthik, Dhillon, Varun, Ahmed (Regina); Tolga (FIU)

  1. Announcements
  2. Action Items
  3. We touched on the Calorimetry Work package. See below under simulations for updates from Karthik
  4. Run Updates
    1. FCAL
    2. BCAL
  5. Calibrations
  6. Monitoring
  7. Efficiencies
  8. Simulations
    1. BCAL efficiencies from particle gun (Karhik)
      • Starting to reproduce studies with the BCAL that Jon had completed for the FCAL. The first was to study the efficiency with a particle gun.
      • Events were generated over the range of 10-120 deg and from 0 - 6 GeV.
      • Distributions of measured energy were obtained. They look Gaussian with little background. The data (for a 0.5 bin in energy) were fit to a Gaussian and a pol2 background.
      • The efficiency was computed as the integral under the Gaussian within +/-3sigma divided by the number of thrown events in that interval. Efficiencies obtained are ~90-97%.
      • Mark: Suggests to ignore the background term and compute the efficiency taking the events within +/-3 sigma from the covariance matrix (instead of Gaussian fit) divided by the number of thrown events.
      • Elton: Check that this new method is consistent with the previous.
      • Jon: Use the MC to determine where photons are lost. Conversions in the material upstream of the BCAL? Material in the CDC/FDC? Loss of events in the reconstruction? Information to determine sources needs to be requested via a custom file. Karthik can get details from Jon.
    2. Generate BGGEN events in an attempt to generate inclusive pi0 data with distributions similar to calibration data. (Karthik)
      • Finding many more events at low energy than seen in the data.
      • Mark: Differences may be caused by selection cuts in the reconstruction. Karthik will contact Shaun with a list of his cuts to see if additional selections are used in the skimming process.
    3. Questions about reconstruction (Tolga)
      • Has found that 1 GeV generated photons, observed on the event display, do not show up on the monitoring histograms. Elton: Should have a private plugin that dumps out hits in the BCAL, this may be used to find where in the analysis process showers (or hits) are getting lost.
  9. BCAL Deep Learning
  10. NIM articles
    • Elton is starting an outline for a GlueX detector paper for NIM. We will need to decide how to include the relevant information from the FCAL into this overall paper.
  11. Any other business