单步相位识别和相位锁定用于使用深度学习的连贯光束组合
Yunhui Xie1, Fedor Chernikov2, Ben Mills2
1Optoelectronics Research Centre, University of Southampton, Southampton, UK. yunhui.xie@soton.ac.uk.
Scientific reports
|March 30, 2024
概括
本研究展示了实时连贯光束组合使用深度学习来控制光纤激光器相位偏移. 这种方法可以精确控制高功率激光系统和先进的光束成型.
科学领域:
- 光学和光子学 在光学和光子学.
- 激光物理 激光物理
- 人工智能的人工智能
背景情况:
- 对于高功率光纤激光器来说,一致的光束组合至关重要,但由于无法获得相位信息和系统噪声,精确的相位控制具有挑战性.
- 单个光纤功率限制需要组合多个光束,需要精确的相位对齐以获得最佳的强度配置.
- 现有的方法在纤维激光系统中不断变化的相位噪声的实时校正方面存在困难.
研究的目的:
- 开发一种实时方法,用于精确的相位控制在多束连贯光纤激光组合.
- 利用深度学习直接从组合强度模式中识别和纠正相位偏移.
- 为了证明同时的光束组合和光束塑造能力.
主要方法:
- 实施七束光纤激光系统,使用空间光调制器进行相位控制.
- 应用深度学习代理来分析组合强度配置文件并确定相对相位偏移.
- 基于深度学习输出的阶段校正实时反循环.
主要成果:
- 在使用深度学习用于相位偏移识别的七束系统中成功展示了连贯的组合.
- 实现了相位噪声的实时校正,实现了稳定和最佳的光束组合.
- 深度学习代理成功计算了用户指定的目标强度配置文件的相位校正,实现了光束成型.
结论:
- 深度学习提供了一种有效的解决方案,用于实时阶段控制,在光纤激光器的连贯束组合中.
- 开发的方法克服了相位信息获取和动态相位噪声的挑战.
- 这种方法可以实现先进的功能,如同步光束组合和精确的光束成型,用于高功率激光应用.
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