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

**Published:** October 5, 2026
**Author:** Armen Kasparian, Torri Jeske, Monibor Rahman, Chris Keith, James Maxwell, Thomas Britton, Malachi Schram, David Lawrence
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/reinforcement-learning-techniques-for-the-optimization-of-target-polariz

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…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2610.02452)

**Tags:** #arXiv

---

*AI Qazaqstan — non-commercial informational portal about AI in Kazakhstan. Machine translations and summaries are AI-generated.*