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We develop a Monte Carlo wave function algorithm for the quantum linear Boltzmann equation, a Markovian master equation describing the quantum motion of a test particle interacting with the particles of an environmental background gas. The…

Quantum Physics · Physics 2010-09-28 Marc Busse , Piotr Pietrulewicz , Heinz-Peter Breuer , Klaus Hornberger

We present a multi-lattice kinetic Monte Carlo (kMC) approach that efficiently describes the atomistic dynamics of morphological transitions between commensurate structures at crystal surfaces. As an example we study the reduction of a…

Mesoscale and Nanoscale Physics · Physics 2015-01-09 Max J. Hoffmann , Matthias Scheffler , Karsten Reuter

We discuss a projector Monte Carlo method for quantum spin models formulated in the valence bond basis, using the S=1/2 Heisenberg antiferromagnet as an example. Its singlet ground state can be projected out of an arbitrary basis state as…

Strongly Correlated Electrons · Physics 2007-05-23 A. W. Sandvik , K. S. D. Beach

We show how accurate benchmark values of the surface formation energy of crystalline lithium hydride can be computed by the complementary techniques of quantum Monte Carlo (QMC) and wavefunction-based molecular quantum chemistry. To…

Materials Science · Physics 2010-11-10 S. J. Binnie , S. J. Nolan , N. D. Drummond , D. Alfè , N. L. Allan , F. R. Manby , M. J. Gillan

We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of self-bound quantum many-body systems in continuous Hilbert…

Nuclear Theory · Physics 2025-04-30 Elad Parnes , Nir Barnea , Giuseppe Carleo , Alessandro Lovato , Noemi Rocco , Xilin Zhang

We implement the phaseless auxiliary field quantum Monte Carlo method using the plane-wave based projector augmented wave method and explore the accuracy and the feasibility of applying our implementation to solids. We use a singular value…

An overview of recent work on Monte Carlo simulations of a granular binary mixture is presented. The results are obtained numerically solving the Enskog equation for inelastic hard-spheres by means of an extension of the well-known direct…

Fluid Dynamics · Physics 2007-05-23 J. M. Montanero

We present a recently developed projector quantum Monte Carlo method for calculations of electronic structure in systems with spin-orbit interactions. The method solves for many-body eigenstates in the presence of spin-orbit using the…

Chemical Physics · Physics 2017-08-09 Cody A. Melton , M. Chandler Bennett , Lubos Mitas

We extend the recently introduced phaseless auxiliary-field quantum Monte Carlo (QMC) approach to any single-particle basis, and apply it to molecular systems with Gaussian basis sets. QMC methods in general scale favorably with system…

Computational Physics · Physics 2007-05-23 W. A. Al-Saidi , Shiwei Zhang , Henry Krakauer

We present an \textit{ab initio} auxiliary field quantum Monte Carlo method for studying the electronic structure of molecules, solids, and model Hamiltonians at finite temperature. The algorithm marries the \textit{ab initio} phaseless…

Strongly Correlated Electrons · Physics 2018-11-13 Yuan Liu , Minsik Cho , Brenda Rubenstein

A statistical method is derived for the calculation of thermodynamic properties of many-body systems at low temperatures. This method is based on the self-healing diffusion Monte Carlo method for complex functions [F. A. Reboredo J. Chem.…

Other Condensed Matter · Physics 2014-03-05 Fernando A. Reboredo , Jeongnim Kim

Hamiltonian Monte Carlo (HMC) is an efficient Bayesian sampling method that can make distant proposals in the parameter space by simulating a Hamiltonian dynamical system. Despite its popularity in machine learning and data science, HMC is…

Machine Learning · Statistics 2020-09-02 Ziming Liu , Zheng Zhang

The combination of continuum Many-Body Quantum physics and Monte Carlo methods provide a powerful and well established approach to first principles calculations for large systems. Replacing the exact solution of the problem with a…

Computational Physics · Physics 2009-10-01 J. R. Trail

For a long time, people have been focusing on how to extract more information, such as off-diagonal observables, from the quantum Monte Carlo (QMC) simulation of the partition function, but there have been numerous difficulties, and many of…

Strongly Correlated Electrons · Physics 2026-03-13 Zhiyan Wang , Zhe Wang , Bin-Bin Mao , Zheng Yan

Treating the fermionic ground state problem as a constrained stochastic optimization problem, a formalism for fermionic quantum Monte Carlo is developed that makes no reference to a trial wavefunction. Exchange symmetry is enforced by…

Strongly Correlated Electrons · Physics 2020-10-14 Michael Hutcheon

We report variational and diffusion quantum Monte Carlo (VMC and DMC) studies of the binding curve of the ground-state chromium dimer. We employed various single determinant (SD) or multi-determinant (MD) wavefunctions multiplied by a…

Chemical Physics · Physics 2012-04-06 Kenta Hongo , Ryo Maezono

We demonstrate the simulation of a noncollinear molecule, e.g. H2O molecule using Variational Quantum Eigensolver (VQE) with high chemical accuracy. The 2D and 3D potential energy surface (PES) were reported. Taking advantage of the…

Quantum Physics · Physics 2021-09-02 Anh Pham , Daniel Beaulieu

Detailed numerical results obtained with state-of-the-art Quantum Monte Carlo (QMC) simulations are presented for the superfluid phase of $^4$He at saturated vapor pressure. The aim of this contribution is that of providing reliable,…

Statistical Mechanics · Physics 2026-05-04 Massimo Boninsegni

The quantum Monte Carlo methods represent a powerful and broadly applicable computational tool for finding very accurate solutions of the stationary Schroedinger equation for atoms, molecules, solids and a variety of model systems. The…

Computational Physics · Physics 2011-01-28 Jindrich Kolorenc , Lubos Mitas

Variational quantum algorithms are poised to have significant impact on high-dimensional optimization, with applications in classical combinatorics, quantum chemistry, and condensed matter. Nevertheless, the optimization landscape of these…

Quantum Physics · Physics 2022-02-02 Taylor L. Patti , Omar Shehab , Khadijeh Najafi , Susanne F. Yelin