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Sep 24 – 29, 2023
US/Eastern timezone

Utilizing Machine Learning Pattern Recognition for Online Monitoring and Visualization in SpinQuest Experiment

Sep 26, 2023, 2:30 PM
25m
Junior Ballroom C (Durham Convention Center)

Junior Ballroom C

Durham Convention Center

Speaker

Jordan Roberts (University of Virginia)

Description

SpinQuest will measure the sea quarks Sivers Asymmetry, a left-right

asymmetry, with a target transversely polarized with respect to the in-
coming 120 GeV proton beam. An online monitoring system has been

developed to scan the polarized target system and polarization data while
integrating information from detectors and event reconstruction for near
continuous quality checking of the incoming data. Online monitoring of
the target system and detector package will play a vital role in ensuring
optimal performance of the target while achieving the highest figure of

merit possible given the experimental circumstances. This novel moni-
toring system enhances the debugging process during commissioning and

data acquisition through the use of machine learning pattern recognition
techniques and anomaly detection. The scheme outlined promises to aid
target operators and shift takers during the two year long production runs
to begin in Fall of 2023 at Fermilab.

Primary author

Jordan Roberts (University of Virginia)

Presentation materials