AIOP Jun. 24, 2024

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The current weekly meeting time is every other Monday at 13:00 US/Eastern

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Meeting URL: https://jlab-org.zoomgov.com/j/1605159491?pwd=ZnB0Vkp0SCtYZmRPWG1hRGVnQVprUT09&from=addon
Meeting ID: 160 515 9491
Passcode: 680042

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Meeting ID: 160 515 9491
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Meeting ID: 160 515 9491
Passcode: 680042

SIP: 1605159491@sip.zoomgov.com
Passcode: 680042

One tap mobile: US: +16692545252,,1601987443# or +16468287666,,1601987443#

Meeting URL: https://jlab-org.zoomgov.com/j/1605159491?pwd=ZnB0Vkp0SCtYZmRPWG1hRGVnQVprUT09&from=addon
Meeting ID: 160 515 9491
Passcode: 680042

AIOP - Polarized Target

Agenda:

  1. Previous Meeting
  2. Announcements
  3. Conferences/Workshops
  4. Project Progress
  5. PIER Activities
    • Middle School Data Science Hackathon Workshop
    • HUGS mini-Workshop - COMPLETED!
  6. AOT



Minutes

  • Prior Announcements
    • Patrick will write an abstract and send around for Polarization workshop
    • Torri will present 50% AIEC/AIOP in Texas
  • Project Progress
    • Data mining
      • Torri
        • Showed a notebook with distributions of fit params and inputs.
        • Starting to see some correlations in some subsets
          • Looking at Fridge_F (flow) and fit params
          • Move x–> (x-x0)
        • Looked at other variables
          • Chris gave explanation for some groupings seen in the data
      • Armen
        • Proton data fits without CC
          • Does slightly better (?)
            • Same data
          • Speculate that it may be collapsing to the average of a value that doesn’t change much.
          • Discussed approaches with/without cc
        • Trying to train with both positive and negative values doesn’t work
          • Split data pos: 22k neg: 13k
            • Some confusion on counts post split
            • Thomas noticed the split meant 0s end up in both
            • Torri/Chris discussed the kinds of data and what restrictions they have (defined to be positive)
          • Can train well if pos and neg are trained apart. Not together
          • Discussion of better engineered features than mean, stdev
            • Use area?
  • Todo
    • Armen to use area (which he already has) to retrain pos/neg data

Action Items