Spectroscopic techniques can probe molecular systems non-invasively and investigate their
structure, properties and dynamics in different environments and physico-chemical …

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 following sections are included: Random Numbers and Statistical Analysis Probability
density and distribution functions Characterization of probability density functions Functions …

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

Abstract Quantum Monte Carlo methods represent a powerful and broadly applicable
computational tool for finding very accurate solutions of the stationary Schrödinger equation …

By means of a quadratic diffusion Monte Carlo method we have performed a comparative
analysis between the Aziz potential and a revised version of it. The results demonstrate that …

Ground state expectation values are obtained by using a path integral ground state Monte
Carlo method. The method allows calculations of ground state expectation values without …

A Monte Carlo algorithm for computing quantum-mechanical expectation values of
coordinate operators in many-body problems is presented. The algorithm, which relies on …

Properties that are necessarily formulated within pure (symmetric) expectation values are
difficult to calculate for projector quantum Monte Carlo approaches, but are critical in order to …

The multiconfiguration time-dependent Hartree (MCTDH) method and its multilayer
extension (ML-MCTDH) are powerful algorithms for the efficient computation of nuclear …