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We derive an efficient method for the insertion of structured particles in grand canonical Monte Carlo simulations of adsorption in very confining geometries. We extend this method to path integral simulations and use it to calculate the…

Statistical Mechanics · Physics 2008-04-09 G. Garberoglio

We present a massively parallel quantum Monte Carlo based implementation of real-space dynamical mean-field theory for general inhomogeneous correlated fermionic lattice systems. As a first application, we study magnetic order in a binary…

Quantum Gases · Physics 2010-12-16 N. Blümer , E. V. Gorelik

We present a method which extends Monte Carlo studies to situations that require a large dynamic range in particle number. The underlying idea is that, in order to calculate the collisional evolution of a system, some particle interactions…

Astrophysics · Physics 2009-11-13 C. W. Ormel , M. Spaans

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

Various kinetic Monte Carlo algorithms become inefficient when some of the population sizes in a system are large, which gives rise to a large number of reaction events per unit time. Here, we present a new acceleration algorithm based on…

Quantitative Methods · Quantitative Biology 2019-07-24 Yen Ting Lin , Song Feng , William S. Hlavacek

The investigation of the nonequilibrium quantum dynamics of bosonic many-body systems is very challenging due to the excessively growing Hilbert space and poses a major problem for their theoretical description and simulation. We present a…

Quantum Gases · Physics 2019-08-07 F. Köhler , K. Keiler , S. I. Mistakidis , H. -D. Meyer , P. Schmelcher

Quantum nanosystems involve the coupled dynamics of fermions or bosons across multiple scales in space and time. Examples include quantum dots, superconducting or magnetic nanoparticles, molecular wires, and graphene nanoribbons. The number…

Mesoscale and Nanoscale Physics · Physics 2011-11-01 D. Balamurugan , Peter. J. Ortoleva

Correlated fermions are of high interest in condensed matter (Fermi liquids, Wigner molecules), cold atomic gases and dense plasmas. Here we propose a novel approach to path integral Monte Carlo (PIMC) simulations of strongly degenerate…

Quantum Gases · Physics 2016-01-15 Tobias Dornheim , Simon Groth , Alexey Filinov , Michael Bonitz

We study a soliton in an optical lattice holding bosonic atoms quantum mechanically using both an exact numerical solution and quantum Monte Carlo simulations. The computation of the state is combined with an explicit account of the…

Quantum Physics · Physics 2009-11-13 Juha Javanainen , Uttam Shrestha

A new Markov Chain Monte Carlo method for simulating the dynamics of molecular systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is…

Computational Physics · Physics 2017-02-07 Liborio I. Costa

An accurate and consistent theory of phonons in metals requires that all long-range Coulomb interactions between charged particles (electrons and ions) be treated on equal footing. So far, all attempts to deal with this non-perturbative…

Strongly Correlated Electrons · Physics 2016-11-02 Igor S. Tupitsyn , Andrey S. Mishchenko , Naoto Nagaosa , Nikolay Prokof'ev

We develop an all-electron path integral Monte Carlo (PIMC) method with free-particle nodes for warm dense matter and apply it to water and carbon plasmas. We thereby extend PIMC studies beyond hydrogen and helium to elements with core…

Materials Science · Physics 2012-03-22 Kevin Driver , Burkhard Militzer

Path-Integral-Monte-Carlo simulation has been used to calculate the properties of a two-dimensional (2D) interacting Bose system. The bosons interact with hard-core potentials and are confined to a harmonic trap. Results for the density…

Statistical Mechanics · Physics 2007-05-23 Stefan Heinrichs , William J. Mullin

The direct simulation Monte Carlo (DSMC) method is a widely used stochastic particle approach to solving the Boltzmann equation. However, its computational cost remains a major drawback, which can be attributed to statistical errors when…

Fluid Dynamics · Physics 2024-07-12 Takehiro Shiraishi , Ikuya Kinefuchi

Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Hamiltonian system. However, HMC is sensitive to large time…

Machine Learning · Statistics 2016-09-15 Xiaoyu Lu , Valerio Perrone , Leonard Hasenclever , Yee Whye Teh , Sebastian J. Vollmer

The probability of accepting a candidate move in the hybrid Monte Carlo algorithm can be increased by considering a transition to be between windows of several states at the beginning and end of the trajectory, with a state within the…

High Energy Physics - Lattice · Physics 2008-02-03 R. M. Neal

A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are…

Biomolecules · Quantitative Biology 2017-07-13 Akira R. Kinjo

We propose a local, O(N) molecular dynamics algorithm for the simulation of charged systems. The long ranged Coulomb potential is generated by a propagating electric field that obeys modified Maxwell equations. On coupling the…

Soft Condensed Matter · Physics 2009-11-10 Jörg Rottler , A. C. Maggs

This review gives an overview on the research of algorithms for dynamical fermions used in large scale lattice QCD simulations. First a short overview on the state-of-the-art of ensemble generation at the physical point is given. Followed…

High Energy Physics - Lattice · Physics 2024-02-20 Jacob Finkenrath

Accurately and efficiently estimating system performance under uncertainty is paramount in power system planning and operation. Monte Carlo simulation is often used for this purpose, but convergence may be slow, especially when detailed…

Computation · Statistics 2020-10-23 Simon Tindemans , Goran Strbac