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标题为英语Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

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 manual trial-and-error by…

arXiv — cs.AI作者: Armen Kasparian, Torri Jeske, Monibor Rahman, Chris Keith, James Maxwell, Thomas Britton, Malachi Schram, David Lawrence2026年10月5日 (10月5日)
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  • 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 manual trial-and-error by…
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Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

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