[24p-E203-1~16] 23.1 Joint Session N "Informatics"

△ [24p-E203-10] Bayesian Estimation for Multi-element XPS Spectrum Analysis using SESSA as a Generative Model

〇Atsushi Machida¹, Kenji Nagata², Ryo Murakami³, Hiroshi Shinotsuka², Hayaru Shouno³, Hideki Yoshikawa², Masato Okada^1,2 (1.Univ. of Tokyo, 2.NIMS, 3.UEC)

Keywords:data-driven science, Bayesian statistics

XPS is a widely used measurement technique for surface material analysis, but often requires analysis based on the analyst's experience. From previous study, Bayesian estimation method for XPS analysis was proposed as a method to solve this problem. In this study, we replace the generative model in the previous study with the simulator SESSA, which allows us to set the layer structure of the sample and to estimate parameters such as its thickness.