Machine learning pattern recognition algorithm with applications to coherent laser combination
We analyze a new kind of machine learning algorithm designed to feedback stabilize
coherently combined lasers. This algorithm learns differential, rather than absolute, values of …
coherently combined lasers. This algorithm learns differential, rather than absolute, values of …
[PDF][PDF] 国家自然科学基金视角下我国激光科学技术发展的分析和展望
唐华， 沈咏， 龙丽媛 - Chinese Journal of Lasers, 2023 - researching.cn
摘要激光自发明以来经历了飞速的发展, 带动物理, 化学, 生物, 信息等众多相关领域取得了重大
突破, 在基础科学和应用技术研究中占据了至关重要的地位. 本文从国家自然科学基金的视角 …
突破, 在基础科学和应用技术研究中占据了至关重要的地位. 本文从国家自然科学基金的视角 …
Experimental beam combining stabilization using machine learning trained while phases drift
An 8-beam, diffractive coherent beam combiner is phase controlled by a learning algorithm
trained while optical phases drift, using a differential mapping technique. Combined output …
trained while optical phases drift, using a differential mapping technique. Combined output …
Feedback and control systems for future linear colliders: White Paper for Snowmass 2021 Topical Group AF07-RF
Particle accelerators for high energy physics will generate TeV-scale particle beams in
large, multi-Km size machines colliding high brightness beams at the interaction point [1-4] …
large, multi-Km size machines colliding high brightness beams at the interaction point [1-4] …
An Optical Controlling Environment and Reinforcement Learning Benchmarks
A Abuduweili, C Liu - arXiv preprint arXiv:2203.12114, 2022 - arxiv.org
Deep reinforcement learning has the potential to address various scientific problems. In this
paper, we implement an optics simulation environment for reinforcement learning based …
paper, we implement an optics simulation environment for reinforcement learning based …