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Logistic information

Meeting room at JLab: CC F226

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Analyzer code updates

  1. General discussion
  2. Pull requests
    • #239---Feature-Aggregator Add Regressed
      • Needs some "general cleanup" before merging
    • #247---Feature alarm updates
      • Merged
  3. New feature plans
    • Continuing development of minirun functionality
    • Data-handlers which can process results from other data-handlers
      • I've made some progress, and expect to be committing it this week
      • How do we want to check for residual correlation after correction? Done within a second pass in JAPAN, or as a post-processing script?
    • BMW first pass extractor
      • Cameron has been in contact with Wouter to get started, will follow up this week

Prompt analysis toolchain

  1. Status on the farm
    • The analysis is basically ready, but we need to set up directories
    • Also need to set up a procedure to stage outputs to tape. Cameron has checked the volatile location: 1TB reserved, 3TB available. We should ask for an increase
  2. Path to migration to japan
    • Needs: Correlation/correction done on mini-run basis, BMW extractor
    • Do we want to do all of the prompt plots again? Certainly for CREX; let's think about it for PREX
      • If we redo them for PREX, we probably should make a new set of directories. Do we have enough space in the web directories?
    • Aggregation
  3. Dithering analysis status & updates?
    • Cameron has done some cleanup of the dithering analysis scripts, and it could be added as a postprocessing step
    • We still would need to decide which supercycles to use to calculate the slopes for a particular run-range
  4. Lagrange analysis
    • Tao thinks this probably should be merged with the dithering processing step
    • It calculates sensitivities from dithering data, just as the dithering analysis does. Perhaps have one tool to get all the sensitivities, and then use them in different ways?
      • Wouter makes the comments: Someone should think hard about the assumptions behind this Lagrange multiplier method: 1) assumes an identical Gaussian probability model for both dithering and natural beam motion data, 2) is sensitive to outliers, 3) assumes that all uncertainty is in the dependent variables (think: fits y values against x axis, ignoring uncertainty in all x points)
        [See] https://arxiv.org/pdf/1008.4686.pdf for a fun read

Other issues

    • Let's aim at getting everything ready for a respin by October 23.
    • Cameron has skimmed through the dataset. Including the AT and SAMs in the regression, and thus cutting events when those channels have an issue is generally a small loss in events (~1e-4 lost event fraction). Maybe do three sets of regression: main detectors only, with ATs, and with ATs and SAMs.


Tao, Weibin

Phone: Paul K., Cameron, Devi, Robert R., Sakib, Devaki, Wouter