NMR with Machine Learning

27 Sept 2022, 10:00
25m
HIM

HIM

Helmholtz Institute Mainz Staudingerweg 18 55128 Mainz

Speaker

Devin Seay (University of Virginia)

Description

Constant current continuous wave Nuclear Magnetic Resonance (NMR) has
been an essential tool for polarized target experiments in Nuclear and
High-energy physics. Q-meter based phase-sensitive detection can provide
accurate monitoring of the polarization over the course of a scattering
experiment with limitations due to some operational parameters. In this talk,
we present recent studies of improved signal to noise in NMR-based Spin-1
polarization measurements as well as reliable measurements outside of the
designated range of the Q-meter’s operational parameters with the use of
machine learning (ML). This approach will allow for real time online
polarization monitoring and offline polarization data analysis for improved
overall figure of merit for experiments using solid state polarized targets.

Category Polarized Targets

Primary author

Devin Seay (University of Virginia)

Co-authors

Dr Dustin Keller (University of Virginia) Dr Ishara Fernando (University of Virginia)

Presentation materials