Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388955%3A_____%2F20%3A00538076" target="_blank" >RIV/61388955:_____/20:00538076 - isvavai.cz</a>

Result on the web

<a href="http://hdl.handle.net/11104/0315897" target="_blank" >http://hdl.handle.net/11104/0315897</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1063/5.0015042" target="_blank" >10.1063/5.0015042</a>

Result language

angličtina

Original language name

Data-driven kinetic energy density fitting for orbital-free DFT: Linear vs Gaussian process regression

Original language description

We study the dependence of kinetic energy densities (KEDs) on density-dependent variables that have been suggested in previous works on kinetic energy functionals for orbital-free density functional theory. We focus on the role of data distribution and on data and regressor selection. We compare unweighted and weighted linear and Gaussian process regressions of KEDs for light metals and a semiconductor. We find that good quality linear regression resulting in good energy-volume dependence is possible over density-dependent variables suggested in previous literature studies. This is achieved with weighted fitting based on the KED histogram. With Gaussian process regressions, excellent KED fit quality well exceeding that of linear regressions is obtained as well as a good energy-volume dependence, which was somewhat better than that of best linear regressions. We find that while the use of the effective potential as a descriptor improves linear KED fitting, it does not improve the quality of the energy-volume dependence with linear regressions but substantially improves it with Gaussian process regression. Gaussian process regression is also able to perform well without data weighting.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10403 - Physical chemistry

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Chemical Physics

ISSN

0021-9606

e-ISSN

—

Volume of the periodical

153

Issue of the periodical within the volume

7

Country of publishing house

US - UNITED STATES

Number of pages

15

Pages from-to

074104

UT code for WoS article

000563905200002

EID of the result in the Scopus database

2-s2.0-85089794538