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Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

This story is from 2026-10-06. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2610.02452v1 Announce Type: new Abstract: The operation of dynamically polarized targets in nuclear physics experiments relies on continuous tuning of the microwave frequency to compensate for radiation damage and evolving material properties, a task that is traditionally performed through ma…

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  1. 2026-10-06 04:00 · arXiv cs.AI
    Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

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