[8p-N106-1~11] 3.4 Laser system and materials

3:15 PM - 3:30 PM JST(6:15 AM - 6:30 AM UTC)Presentation by Applicant for JSAP Young Scientists Presentation Award

[8p-N106-7] Implementing Deep Reinforcement Learning for autonomous laser cavity optimization

〇Yuki Ikeya^1,2, Takashi Sekine¹, Endo Tsubasa², Toshio Otsu², Takaaki Morita¹, Yoshinori Tamaoki¹, Yoshinori Kato¹, Toshiyuki Kawashima¹, Yohei Kobayashi¹ (1.Hamamatsu Photonics K.K., 2.ISSP, Univ.Tokyo.)

Keywords:

spatial light modulator,machine learning,laser cavity

In order to obtain ideal oscillation characteristics in the development of a laser resonator, a huge amount of parameter search and control technology is required. The introduction of reinforcement learning is considered to be an effective means of solving the problem, but it is unknown whether it can be applied to a real laser system. We have made it possible to dynamically and quickly control the angle and curvature of the mirror with high degrees of freedom by using a spatial light modulator (LCOS-SLM) instead of the resonator mirror. In this presentation, we will report on a control method using DQN, which is one of the deep reinforcement learning methods.