AI辅助实验控制与校准
AI Assisted Experiment Control and Calibration
AI总结：
本文报告了将AI/ML集成到GlueX谱仪探测器控制与校准中的项目，通过环境信息预测中央漂移室校准常数并自动调整设备控制，提高了校准稳定性和效率，同时兼顾设备安全与数据质量。
摘要：
本文为AI辅助实验控制与校准项目的最终报告。该项目将AI/ML集成到GlueX谱仪中一个生产探测器系统的控制与校准中，GlueX谱仪是杰斐逊实验室实验大厅D中的大型核物理探测器。AI/ML模型利用数据采集前可获得的环境信息预测中央漂移室的校准常数，然后自动调整设备控制，使数据后处理所需的校准值更加稳定且能更快确定。集成到生产系统中需要设置防护措施和策略选择，以确保设备安全和数据质量。该项目还尝试将类似技术应用于其他探测器，本文也对这些工作进行了描述，并记录了项目的许多细节。
英文摘要：
Final report for the AI Assisted Experiment Control and Calibration project. This project integrated AI/ML into the controls and calibration of a production detector system in the GlueX spectrometer, a large scale Nuclear Physics detector in experimental Hall-D at Jefferson Lab. The AI/ML model predicted calibration constants for a Central Drift Chamber using environmental information available prior to taking the data. The device controls were then automatically adjusted so that the calibration values needed for post-processing of the data were much more stable and quicker to determine. Integration into a production system required guardrails and policy choices to ensure safety of the equipment and the data quality. The project sought to apply similar technology to other detectors. Those efforts are also described here. This documents many of the details of the project.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
