The 80th JSAP Autumn Meeting 2019

Presentation information

Oral presentation

3 Optics and Photonics » 3.7 Laser processing

[18a-N304-1~8] 3.7 Laser processing

Wed. Sep 18, 2019 9:30 AM - 11:45 AM N304 (N304)

Daisuke Nakamura(Kyushu Univ.), Takashi Nakajima(Kyoto Univ.)

9:30 AM - 9:45 AM

[18a-N304-1] A Deep Learning Approach for Predicting Laser-induced Plasma Characteristics in Glass

〇(M2)Kohei Shimahara1, Shuntaro Tani1, Yohei Kobayashi1 (1.ISSP, Univ. Tokyo)

Keywords:glass, deep learning, plasma

Deep learning is a tool that enables one to approximate functions that A) are highly non-linear, and B) have multi-dimensional inputs such as morphological data frequently acquired in laser processing research; therefore, it has great potential in dealing with complex systems such as laser-matter interaction. Our goal is to predict the time evolution of laser-induced destruction in glass using this technology. In this presentation, I will report our work on designing and training a neural network that can predict the characteristics of laser-induced plasma in glass under a given condition(crater shape and laser power).