Machine Learning Extraction of Tensor Polarization in Spin-1 Observables

ORAL

Abstract

Tensor polarization enhancement using radio frequency manipulation of the

spin-1 line shape can improve the figure of merit of specialized tensor polariza-

tion observables in scattering experiments, improving the overall figure of merit.

This improvement is optimized only if careful manipulation and measurement

are synchronized to near-real time so that the RF manipulation can be applied

after each NMR sweep. This presentation discusses the measurement scheme

designed to reduce uncertainties in the tensor polarization while maximizing the

enhancement as well as a novel machine learning approach designed to improve

inference speed, accuracy, and precision.

*This work was supported by DOE contract DE-FG02-96ER40950.

Presenters

  • Devin Allen Seay

    • University of Virginia

Authors

  • Devin Allen Seay

    • University of Virginia
  • Dustin Keller

    • University of Virginia