Deep learning methods outperform human capabilities in pattern recognition and data
processing problems and now have an increasingly important role in scientific discovery. A …

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic
structure calculations. It supports calculations of metallic and insulating solids, molecules …

We review recent advances in the capabilities of the open source ab initio Quantum Monte
Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency …

We present a general approach to converge excited state solutions to any quantum
chemistry orbital optimization process, without the risk of variational collapse. The resulting …

We extend our recently developed heat-bath configuration interaction (HCI) algorithm, and
our semistochastic algorithm for performing multireference perturbation theory, to calculate …

Density functional theory (DFT) based modeling of electronic excited states is of importance
for investigation of the photophysical/photochemical properties and spectroscopic …

Orbital optimization is crucial when using a non-Aufbau Slater determinant that involves
promotion of an electron from a (nominally) occupied molecular orbital to an unoccupied …

We present a discussion of recent progress in excited‐state‐specific quantum chemistry and
quantum Monte Carlo alongside a demonstration of how a combination of methods from …

We present how to compute vibrational eigenstates with tree tensor network states (TTNSs),
the underlying ansatz behind the multilayer multiconfiguration time-dependent Hartree (ML …

In single-reference coupled-cluster (CC) methods, one has to solve a set of non-linear
polynomial equations in order to determine the so-called amplitudes that are then used to …