Noncovalent interactions by quantum Monte Carlo
Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-
body problems such as the stationary Schrödinger equation. The review introduces basic …
body problems such as the stationary Schrödinger equation. The review introduces basic …
[PDF][PDF] Docking and ligand binding affinity: uses and pitfalls
MJR Yunta - Am. J. Model. Optim, 2016 - researchgate.net
In this review article, we will explore the foundations of different classes of docking and
scoring functions, their possible limitations, and their suitable application domains. We also …
scoring functions, their possible limitations, and their suitable application domains. We also …
Benchmarks and reliable DFT results for spin gaps of small ligand Fe (II) complexes
All-electron fixed-node diffusion Monte Carlo provides benchmark spin gaps for four Fe (II)
octahedral complexes. Standard quantum chemical methods (semilocal DFT and CCSD (T)) …
octahedral complexes. Standard quantum chemical methods (semilocal DFT and CCSD (T)) …
Multideterminant wave functions in quantum Monte Carlo
Quantum Monte Carlo (QMC) methods have received considerable attention over past
decades due to their great promise for providing a direct solution to the many-body …
decades due to their great promise for providing a direct solution to the many-body …
[HTML][HTML] Almost exact energies for the Gaussian-2 set with the semistochastic heat-bath configuration interaction method
The recently developed semistochastic heat-bath configuration interaction (SHCI) method is
a systematically improvable selected configuration interaction plus perturbation theory …
a systematically improvable selected configuration interaction plus perturbation theory …
TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods
ABSTRACT TURBOGENIUS is an open-source Python package designed to fully control ab
initio quantum Monte Carlo (QMC) jobs using a Python script, which allows one to perform …
initio quantum Monte Carlo (QMC) jobs using a Python script, which allows one to perform …
Benchmark phaseless auxiliary-field quantum Monte Carlo method for small molecules
We report a scalable Fortran implementation of the phaseless auxiliary-field quantum Monte
Carlo (ph-AFQMC) and demonstrate its excellent performance and beneficial scaling with …
Carlo (ph-AFQMC) and demonstrate its excellent performance and beneficial scaling with …
A mountaineering strategy to excited states: Highly accurate energies and benchmarks for bicyclic systems
Pursuing our efforts to define highly accurate estimates of the relative energies of excited
states in organic molecules, we investigate, with coupled-cluster methods including iterative …
states in organic molecules, we investigate, with coupled-cluster methods including iterative …
Phase stability of TiO2 polymorphs from diffusion Quantum Monte Carlo
Titanium dioxide, TiO 2, has multiple applications in catalysis, energy conversion and
memristive devices because of its electronic structure. Most of these applications utilize the …
memristive devices because of its electronic structure. Most of these applications utilize the …
Introduction to the variational and diffusion Monte Carlo methods
We provide a pedagogical introduction to the two main variants of real-space quantum
Monte Carlo methods for electronic structure calculations: variational Monte Carlo (VMC) …
Monte Carlo methods for electronic structure calculations: variational Monte Carlo (VMC) …