18-22 October 2021
Matsue, Shimane Prefecture, Japan
Asia/Tokyo timezone

Machine Learning Online Monitoring for the SpinQuest experiment at Fermilab

22 Oct 2021, 07:50
25m
Room 303-304 (Kunibiki Messe)

Room 303-304

Kunibiki Messe

Parallel Session Presentation Future facilities and experiments Future facilities and experiments

Speaker

Arthur Conover (University of Virginia)

Description

The SpinQuest experiment (E1039) is a transversely polarized fixed target experiment at Fermi National Accelerator Laboratory designed to measure the sea-quark Sivers functions via the Drell-Yan process. An unpolarized beam of 120-GeV protons will interact with a transversely polarized proton or deuteron target which will produce Drell-Yan dimuon events. Those muons will be detected in the spectrometer which allows for the extraction of the single-spin transverse asymmetry. Fast online monitoring is necessary to scan the quality of the incoming data and the general health of the experiment. Machine learning techniques can be used to speed the reconstruction of dimuon events and monitor any false asymmetry measured in each spill. Additionally, slow controls information can be integrated, allowing for automation of diagnostics and quality checks during the experiment, potentially reducing the overall systematic error of the experiment.

Primary author

Arthur Conover (University of Virginia)

Presentation Materials

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