17 citations · 33 across the 3 of their papers we have counts for
5 papers
Self-learning hybrid Monte Carlo method for isothermal-isobaric ensemble: Application to liquid silica
Keita Kobayashi, Yuki Nagai, Mitsuhiro Itakura +1
Self-learning hybrid Monte Carlo (SLHMC) is a first-principles simulation that allows for exact ensemble generation on potential energy surfaces based on density functional theory.…
Mean Force Based Temperature Accelerated Sliced Sampling: Efficient Reconstruction of High Dimensional Free Energy Landscapes
Asit Pal, Subhendu Pal, Shivani Verma +2
Temperature Accelerated Sliced Sampling (TASS) is an efficient method to compute high dimensional free energy landscapes. The original TASS method employs the Weighted Histogram An…
Nuclear Quantum Effects on Autoionization of Water Isotopologues Studied by Ab Initio Path Integral Molecular Dynamics
Bo Thomsen, Motoyuki Shiga
In this study we investigate the nuclear quantum effects (NQEs) on the acidity constant (pKA) of liquid water isotopologues at the ambient condition by path integral molecular dyna…
Self-learning Hybrid Monte Carlo: A First-principles Approach
Yuki Nagai, Masahiro Okumura, Keita Kobayashi +1
We propose a novel approach called Self-Learning Hybrid Monte Carlo (SLHMC) which is a general method to make use of machine learning potentials to accelerate the statistical sampl…
A screened automated structural search with semiempirical methods
Yukihiro Ota, Sergi Ruiz-Barragan, Masahiko Machida +1
We developed an interface program between a program suite for an automated search of chemical reaction pathways, GRRM, and a program package of semiempirical methods, MOPAC. A two-…