Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session B58: DFT and Beyond II
11:15 AM–1:39 PM,
Monday, March 2, 2020
Room: Mile High Ballroom 3B
Sponsoring
Units:
DCP DCOMP DPOLY DCMP
Chair: Adam Wasserman, Purdue Univ
Abstract: B58.00002 : Essential difference between the machine learning and artificial Kohn-Sham potentials
Presenter:
Ryo Nagai
(Department of Physics, The University of Tokyo)
Authors:
Ryo Nagai
(Department of Physics, The University of Tokyo)
Kieron Burke
(Departments of Physics and Astronomy and of Chemistry, University of California, Irvine)
Ryosuke Akashi
(Department of Physics, The University of Tokyo)
Osamu Sugino
(Department of Physics, The University of Tokyo)
Here, we analyze the properties of the machine-learning density functionals. We investigate essential differences between the machine-learned functionals and artificial functionals by comparing their performance using accurate densities and ones from artificial functionals as the training data.
[1] R. Nagai, R. Akashi, and O. Sugino, arXiv:1903.00238 (2019).
[2] R. Nagai, K. Burke, R. Akashi, and O. Sugino, in preparation.
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