9 citations · 35 across the 11 of their papers we have counts for
6 papers · 1 filter
jQMC: A JAX-based ab initio quantum Monte Carlo package designed for GPU-accelerated computing
Kousuke Nakano, Michele Casula
We present jQMC, a Python-based computational package for {\it ab initio} Quantum Monte Carlo (QMC) simulations, designed for modern GPU-accelerated computing environments. jQMC im…
The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project
Qiming Sun, Matthew R Hermes, Xiaojie Wu +100
Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum…
Assessing the impact of nodal surface optimization in fixed-node diffusion Monte Carlo on non-covalent interactions
Kousuke Nakano, Benjamin X. Shi, Dario Alfè +1
Diffusion quantum Monte Carlo (DMC) and coupled cluster theory [CCSD(T)] are widely-employed benchmark methods for noncovalent interactions (NCIs). However, recent studies have rep…
Fast Evaluation of Unbiased Atomic Forces in ab initio Variational Monte Carlo via the Lagrangian Technique
Kousuke Nakano, Stefano Battaglia, Jürg Hutter
Ab initio quantum Monte Carlo (QMC) methods are state-of-the-art electronic structure calculations based on highly parallelizable stochastic frameworks for accurate solutions of th…
Load-Balanced Diffusion Monte Carlo Method with Lattice Regularization
Kousuke Nakano, Sandro Sorella, Michele Casula
Ab initio quantum Monte Carlo (QMC) is a stochastic approach for solving the many-body Schrödinger equation without resorting to one-body approximations. QMC algorithms are readily…
Basis set incompleteness errors in fixed-node diffusion Monte Carlo calculations on non-covalent interactions
Kousuke Nakano, Benjamin X. Shi, Dario Alfè +1
Basis set incompleteness error (BSIE) is a common source of error in quantum chemistry (QC) calculations, but it has not been comprehensively studied in fixed-node Diffusion Monte…