This topical review describes the methodology of continuum variational and diffusion
quantum Monte Carlo calculations. These stochastic methods are based on many-body …

As the name implies, Monte Carlo (MC) methods employ random numbers to solve
problems. The range of problems that may be treated by MC is substantial; these include …

The electronic Schrödinger equation can only be solved analytically for the hydrogen atom,
and the numerically exact full configuration-interaction method is exponentially expensive in …

Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising
cutting-edge technique of ab initio quantum chemistry. However, the high computational cost …

We design a neural network Ansatz for variationally finding the ground-state wave function
of the homogeneous electron gas, a fundamental model in the physics of extended systems …

A large collaboration carefully benchmarks 20 first-principles many-body electronic structure
methods on a test set of seven transition metal atoms and their ions and monoxides. Good …

We pursue the development and application of the recently introduced linear optimization
method for determining the optimal linear and nonlinear parameters of Jastrow–Slater wave …

Since the early work of Hylleraas on the helium atom, 1 it has been common knowledge that,
to accurately account for the interaction between the electrons in an atom or a molecule …

Defining accurate and compact trial wavefunctions leading to small statistical and fixed-node
errors in quantum Monte Carlo (QMC) calculations is still a challenging problem. Here we …

The positron, as the antiparticle of the electron, can form metastable states with atoms and
molecules before its annihilation with an electron. Such metastable matter–positron …