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We have reformulated the quantum Monte Carlo (QMC) technique so that a large part of the calculation scales linearly with the number of atoms. The reformulation is related to a recent alternative proposal for achieving linear-scaling QMC,…

Other Condensed Matter · Physics 2016-08-31 D. Alfe` , M. J. Gillan

In low-temperature high-density plasmas quantum effects of the electrons are becoming increasingly important. This requires the development of new theoretical and computational tools. Quantum Monte Carlo methods are among the most…

Statistical Mechanics · Physics 2014-08-12 T. Schoof , S. Groth , M. Bonitz

Quantum Monte Carlo is an efficient technique for finding the ground-state energy and related properties of small molecules. A major challenge remains in accurate determination of a molecule's geometry, i.e. the optimal location of its…

Computational Physics · Physics 2017-04-12 Jan Vrbik

A Monte Carlo method is presented to evaluate quantum states with many particles moving in the continuum. The scattering state is generated at each time by a Monte Carlo random sampling algorithm. The same calculation are repeated until the…

Nuclear Theory · Physics 2013-06-06 Zhen-Xiang Xu , Chong Qi

Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and…

Materials Science · Physics 2025-01-08 Alfonso Annarelli , Dario Alfè , Andrea Zen

Quantum Monte Carlo methods are accurate and promising many body techniques for electronic structure calculations which, in the last years, are encountering a growing interest thanks to their favorable scaling with the system size and their…

Chemical Physics · Physics 2014-02-17 Andrea Zen , Ye Luo , Sandro Sorella , Leonardo Guidoni

A paramount goal in the field of nuclear physics is to unify ab-initio treatments of bound and unbound states. The position-space quantum Monte Carlo (QMC) methods have a long history of successful bound state calculations in light systems…

Nuclear Theory · Physics 2023-08-29 Abraham R. Flores , Kenneth M. Nollett

Quantum Monte Carlo (QMC) methods are one of the most important tools for studying interacting quantum many-body systems. The vast majority of QMC calculations in interacting fermion systems require a constraint to control the sign problem.…

Strongly Correlated Electrons · Physics 2016-12-08 Mingpu Qin , Hao Shi , Shiwei Zhang

Monte Carlo simulations are widely employed to measure the physical properties of glass-forming liquids in thermal equilibrium. Combined with local Monte Carlo moves, the Metropolis algorithm can also be used to simulate the relaxation…

Statistical Mechanics · Physics 2024-09-23 Ludovic Berthier , Federico Ghimenti Frédéric van Wijland

A new Quantum Monte-Carlo (QMC) approach is proposed to investigate low-lying states of nuclei within the shell model. The formalism relies on a variational symmetry-restored wave-function to guide the underlying Brownian motion. Sign/phase…

Nuclear Theory · Physics 2015-10-20 Jérémy Bonnard , Olivier Juillet

Ab initio quantum Monte Carlo (QMC) is a state-of-the-art numerical approach for evaluating accurate expectation values of many-body wavefunctions. However, one of the major drawbacks that still hinders widespread QMC applications is the…

Materials Science · Physics 2024-07-17 Kousuke Nakano , Michele Casula , Giacomo Tenti

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

We propose a new quantum Monte Carlo algorithm to compute fermion ground-state properties. The ground state is projected from an initial wavefunction by a branching random walk in an over-complete basis space of Slater determinants. By…

Condensed Matter · Physics 2016-08-31 Shiwei Zhang , J. Carlson , J. E. Gubernatis

The projective quantum Monte Carlo (PQMC) algorithms are among the most powerful computational techniques to simulate the ground state properties of quantum many-body systems. However, they are efficient only if a sufficiently accurate…

Computational Physics · Physics 2019-10-04 S. Pilati , E. M. Inack , P. Pieri

Many-electron problems pose some of the greatest challenges in computational science, with important applications across many fields of modern science. Fermionic quantum Monte Carlo (QMC) methods are among the most powerful approaches to…

A path integral Monte Carlo method based on the worm algorithm has been developed to compute the chemical potential of interacting bosonic quantum fluids. By applying it to finite-sized systems of helium-4 atoms, we have confirmed that the…

Statistical Mechanics · Physics 2014-06-24 C. M. Herdman , A. Rommal , A. Del Maestro

We present a new quantum Monte Carlo algorithm suitable for generically complex problems, such as systems coupled to external magnetic fields or anyons in two spatial dimensions. We find that the choice of gauge plays a nontrivial role, and…

Condensed Matter · Physics 2009-10-22 Lizeng Zhang , Geoff Canright , Ted Barnes

We present a framework of an auxiliary field quantum Monte Carlo (QMC) method for multi-orbital Hubbard models. Our formulation can be applied to a Hamiltonian which includes terms for on-site Coulomb interaction for both intra- and…

Strongly Correlated Electrons · Physics 2009-10-30 Yukitoshi Motome , Masatoshi Imada

Quantum Monte Carlo (QMC) techniques are used to calculate the one-body density matrix and excitation energies for the valence electrons of bulk silicon. The one-body density matrix and energies are obtained from a Slater-Jastrow wave…

Condensed Matter · Physics 2009-10-31 P. R. C. Kent , Randolph Q. Hood , M. D. Towler , R. J. Needs , G. Rajagopal

We describe and analyze some Monte Carlo methods for manifolds in Euclidean space defined by equality and inequality constraints. First, we give an MCMC sampler for probability distributions defined by un-normalized densities on such…

Numerical Analysis · Mathematics 2017-09-21 Emilio Zappa , Miranda Holmes-Cerfon , Jonathan Goodman