Application of Bayesian optimization for experimental conditions of film deposition

Abstract

Bayesian optimization, which is a machine learning method for sequential optimization, is widely applied as an optimization method that balances exploration and exploitation. In this paper, we first explain the outline of Bayesian optimization, and then introduce its application to the optimization of deposition conditions of epitaxial Si film growth. This paper focus on utilizing the expertise and experience of engineers.