量研学術機関リポジトリ「QST-Repository」は、国立研究開発法人 量子科学技術研究開発機構に所属する職員等が生み出した学術成果（学会誌発表論文、学会発表、研究開発報告書、特許等）を集積しインターネット上で広く公開するサービスです。 Welcome to QST-Repository where we accumulates and discloses the academic research results(Journal Publications, Conference presentation, Research and Development Report, Patent, etc.) of the members of National Institutes for Quantum Science and Technology.
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Angle-resolved photoemission spectroscopy (ARPES) is a powerful experimental technique in modern materials science because it can directly probe electronic states, which are directly related to the physical properties of materials. Among the advanced ARPES techniques, spatially-resolved ARPES has recently attracted growing interest because of its capability to obtain local electronic information at the micro- or nano-metric length scales by utilizing a well-focused light source [1]. On the other hand, it is not trivial to analyze and understand the spatial variation of electronic states against massive datasets, typically in 4-dimensional space (energy, momentum, and two spatial axes). In this work, we present unsupervised clustering analyses based on K-means and Fuzzy-c-means methods on spatially-resolved micro-ARPES data from Y-based high-Tc cuprate superconductor YBa2Cu3O7-δ, which shows spatial inhomogeneity due to multiple surface terminations due to BaO or CuO layers on a cleavage (001) plane [2]. The performance of the clustering analyses will be demonstrated with the comparison of the conventional analysis method.
[1] Hideaki Iwasawa, Electronic Structure 2, 043001 (2020).
[2] H. Iwasawa et al., Phys. Rev. B 98, 081112(R) (2018).
会議概要（会議名, 開催地, 会期, 主催者等）
The 11th New Generation in Strongly Correlated Electron Systems
Unsupervised Clustering of Spatially-resolved ARPES Data
