Papers › Aligning an optical interferometer with beam divergence control and continuous action space
Aligning an optical interferometer with beam divergence control and continuous action space
Stepan Makarenko, Dmitry Sorokin, Alexander Ulanov, A. I. Lvovsky
Reinforcement learning is finding its way to real-world problem application, transferring from simulated environments to physical setups. In this work, we implement vision-based alignment of an optical Mach-Zehnder interferometer with a confocal telescope in one arm, which controls the diameter and divergence of the corresponding beam. We use a continuous action space; exponential scaling enables us to handle actions within a range of over two orders of magnitude. Our agent trains only in a simulated environment with domain randomizations. In an experimental evaluation, the agent significantly outperforms an existing solution and a human expert.
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