[21p-E201-1~8] 17.3 Layered materials

△ [21p-E201-3] Machine learning analysis of opto-valley physics in atomically-thin semiconductors

〇Kenya Tanaka¹, Kengo Hachiya¹, Wenjin Zhang¹, Kazunari Matsuda¹, Yuhei Miyauchi¹ (1.IAE, Kyoto Univ.)

Keywords:valleytronics, transition metal dichalcogenides, Machine Leaning

In monolayer transition metal dichalcogenides, polarization information of light can be transformed to valley information of excitons, and vice versa. These materials have attracted much attention because of their applicability to opto-valleytronics using the excitonic valley degrees of freedom. We will demonstrate machine-learning analysis and prediction of spatial heterogeneity of exciton valley polarization in a monolayer WSe₂ sample.