Machine Learning Diffusion Monte Carlo Forces-Reference-Cited by-同舟云学术

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Machine Learning Diffusion Monte Carlo Forces

Published:2022-12-28 Issue:1 Volume:127 Page:339-355
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Huang Cancan¹^ORCID,Rubenstein Brenda M.¹^ORCID

Affiliation:

1. Department of Chemistry, Brown University, Providence, Rhode Island02912, United States

Funder

Basic Energy Sciences

Research Corporation for Science Advancement

Air Force Office of Scientific Research

Office of Integrative Activities

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.2c05904

Reference85 articles.

1. Density Functional Theory of Electronic Structure

2. An overview of coupled cluster theory and its applications in physics

3. Quantum Monte Carlo simulations of solids

4. ReaxFF Reactive Force Field for Molecular Dynamics Simulations of Hydrocarbon Oxidation

5. Finding the needle in the haystack: towards solving the protein-folding problem computationally

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1. Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories;Journal of Chemical Theory and Computation;2024-08-22

2. Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a Benchmark;Journal of Chemical Theory and Computation;2024-07-14

3. Efficient calculation of unbiased atomic forces in ab initio variational Monte Carlo;Physical Review B;2024-05-28

4. Regular and anomalous diffusion: I. Foundations;Journal of Physics A: Mathematical and Theoretical;2024-05-28

5. Quantum symmetrization transition in superconducting sulfur hydride from quantum Monte Carlo and path integral molecular dynamics;npj Computational Materials;2024-03-15

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