Analysis of Kohn–Sham Eigenfunctions Using a Convolutional Neural Network in Simulations of the Metal–Insulator Transition in Doped Semiconductors-Reference-Cited by-同舟云学术

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Analysis of Kohn–Sham Eigenfunctions Using a Convolutional Neural Network in Simulations of the Metal–Insulator Transition in Doped Semiconductors

Published:2021-09-15 Issue:9 Volume:90 Page:094001
ISSN:0031-9015
Container-title:Journal of the Physical Society of Japan
language:en
Short-container-title:J. Phys. Soc. Jpn.

Author:

Harashima Yosuke¹²^ORCID,Mano Tomohiro³,Slevin Keith⁴^ORCID,Ohtsuki Tomi³^ORCID

Affiliation:

1. Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8601, Japan

2. Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan

3. Physics Division, Sophia University, Chiyoda, Tokyo 102-8554, Japan

4. Department of Physics, Osaka University, Toyonaka, Osaka 560-0043, Japan

Funder

Japan Society for the Promotion of Science

Publisher

Physical Society of Japan

Subject

General Physics and Astronomy

Link

https://journals.jps.jp/doi/pdf/10.7566/JPSJ.90.094001

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