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Monte Carlo (MC) simulations of lattice models are a widely used way to compute thermodynamic properties of substitutional alloys. A limitation to their more widespread use is the difficulty of driving a MC simulation in order to obtain the…

统计力学 · 物理学 2009-11-07 A. van de Walle , M. Asta

We present computer simulations of a dynamic Monte Carlo algorithm for polymer chains on the FCC lattice which takes explicitly into account the possibility to overcome topological constraints by controlling the rate at which nearby polymer…

软凝聚态物质 · 物理学 2021-12-01 Mattia Alberto Ubertini , Angelo Rosa

We present a lattice Monte Carlo algorithm based on the one originally proposed by Maggs and Rossetto for simulating electrostatic interactions in inhomogeneous dielectric media. The original algorithm is known to produce attractive…

软凝聚态物质 · 物理学 2017-05-12 Xiaozheng Duan , Issei Nakamura , Zhen-Gang Wang

Monte Carlo (MC) simulations are essential computational approaches with widespread use throughout all areas of science. We present a method for accelerating lattice MC simulations using fully connected and convolutional artificial neural…

强关联电子 · 物理学 2019-07-31 Shaozhi Li , Philip M. Dee , Ehsan Khatami , Steven Johnston

Monte Carlo simulations of quantum field theories on a lattice become increasingly expensive as the continuum limit is approached since the cost per independent sample grows with a high power of the inverse lattice spacing. Simulations on…

高能物理 - 格点 · 物理学 2021-01-04 Karl Jansen , Eike Hermann Müller , Robert Scheichl

Quantitative theory of interbilayer interactions is essential to interpret x-ray scattering data and to elucidate these interactions for biologically relevant systems. For this purpose Monte Carlo simulations have been performed to obtain…

生物物理 · 物理学 2009-10-31 Nikolai Gouliaev , John F. Nagle

In order to solve quantum field theory in a non-perturbative way, Lagrangian lattice simulations have been very successful. Here we discuss a recently proposed alternative Hamiltonian lattice formulation - the Monte Carlo Hamiltonian. In…

高能物理 - 格点 · 物理学 2007-05-23 H. Kröger , X. Q. Luo , K. J. M. Moriarty

This review article is intended as a practical guide for newcomers to the field of kinetic Monte Carlo (KMC) simulations, and specifically to lattice KMC simulations as prevalently used for surface and interface applications. We will…

计算物理 · 物理学 2019-04-05 Mie Andersen , Chiara Panosetti , Karsten Reuter

Soft particles at fluid interfaces play an important role in many aspects of our daily life, such as the food industry, paints and coatings, and medical applications. Analytical methods are not capable of describing the emergent effects of…

计算物理 · 物理学 2019-09-25 Maarten Wouters , Othmane Aouane , Timm Krueger , Jens Harting

Monte Carlo simulations are a powerful tool to investigate the thermodynamic properties of atomic systems. In practice however, sampling of the complete configuration space is often hindered by high energy barriers between different regions…

统计力学 · 物理学 2020-05-04 Jonas A. Finkler , Stefan Goedecker

We review the application of lattice QCD techniques, most notably the Hybrid Monte-Carlo (HMC) simulations, to first-principle study of tight-binding models of crystalline solids with strong inter-electron interactions. After providing a…

高能物理 - 格点 · 物理学 2016-08-23 P. V. Buividovich , M. V. Ulybyshev

We use Monte Carlo simulations to study polymer melts consisting of fully flexible and moderately stiff chains in the bond fluctuation model at a volume fraction $0.5$. In order to reduce the local density fluctuations, we test a…

软凝聚态物质 · 物理学 2015-06-24 Hsiao-Ping Hsu

We describe an MCMC method for sampling distributions with soft constraints, which are constraints that are almost but not exactly satisfied. We sample a total distribution that is a convex combination of the target soft distribution with…

统计计算 · 统计学 2022-10-24 Ildebrando Magnani

We introduce a Markov Chain Monte Carlo (MCMC) algorithm that dramatically accelerates the simulation of quantum many-body systems, a grand challenge in computational science. State-of-the-art methods for these problems are severely limited…

强关联电子 · 物理学 2025-10-17 Deqian Kong , Shi Feng , Jianwen Xie , Ying Nian Wu

We study some aspects of a Monte Carlo method invented by Maggs and Rossetto for simulating systems of charged particles. It has the feature that the discretized electric field is updated locally when charges move. Results of simulations of…

统计力学 · 物理学 2007-06-27 P. A. McClarty

We demonstrate the use of a new algorithm called the Flat Histogram sampling algorithm for the simulation of lattice polymer systems. Thermodynamics properties, such as average energy or entropy and other physical quantities such as…

统计力学 · 物理学 2009-11-07 Lik Wee Lee , Jian-Sheng Wang

Lattice Monte Carlo (MC) simulations and the functional Renormalization Group (RG) are powerful approaches that allow for quantitative studies of non-perturbative phenomena such as bound-state formation, spontaneous symmetry breaking and…

高能物理 - 格点 · 物理学 2025-03-19 Niklas Zorbach , Jan Philipp Klinger , Owe Philipsen , Jens Braun

A GPU-accelerated version of the lattice Boltzmann method for efficient simulation of soft materials is introduced. Unlike standard approaches, this method reconstructs the distribution functions from available hydrodynamic variables…

We summarize a series of numerical experiments of collisional dynamics in dense stellar systems such as globular clusters (GCs) and in weakly collisional plasmas using a novel simulation technique, the so-called Multi-particle collision…

We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

统计力学 · 物理学 2012-04-16 Stephen Whitelam
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