Zobrazeno 1 - 4
of 4
pro vyhledávání: '"R A Vargas-Hernández"'
Publikováno v:
New Journal of Physics, Vol 21, Iss 2, p 022001 (2019)
We propose a machine-learning approach based on Bayesian optimization to build global potential energy surfaces (PES) for reactive molecular systems using feedback from quantum scattering calculations. The method is designed to correct for the uncert
Externí odkaz:
https://doaj.org/article/3ea95eb2dcf14c4aa53b2c4e4fdaf3d6
Autor:
R. A. Vargas−Hernández
Publikováno v:
The journal of physical chemistry. A. 124(20)
The accuracy of some density functional (DF) models widely used in material science depends on empirical or free parameters that are commonly tuned using reference physical properties. Grid-search methods are the standard numerical approximations use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::061ba378783da0a8a2c1fa4995462839
https://pubmed.ncbi.nlm.nih.gov/32338905
https://pubmed.ncbi.nlm.nih.gov/32338905
Autor:
R A Vargas-Hernández, R V Krems
Publikováno v:
Journal of Physics B: Atomic, Molecular & Optical Physics; 12/14/2016, Vol. 49 Issue 23, p1-1, 1p
Autor:
A. Jasinski, J. Montaner, R. C. Forrey, B. H. Yang, P. C. Stancil, N. Balakrishnan, J. Dai, R. A. Vargas-Hernández, R. V. Krems
Publikováno v:
Physical Review Research, Vol 2, Iss 3, p 032051 (2020)
Quantum scattering calculations for all but low-dimensional systems at low energies must rely on approximations. All approximations introduce errors. The impact of these errors is often difficult to assess because they depend on the Hamiltonian param
Externí odkaz:
https://doaj.org/article/75d939b1289b4801b810ec23e8785ed4