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The basic idea of fast Monte Carlo (MC) simulations is to perform particle-based MC simulations with the excluded-volume interactions modeled by "soft" repulsive potentials that allow particle overlapping. This gives much faster system…

Soft Condensed Matter · Physics 2012-01-24 Qiang Wang

Monodisperse ensembles of particles that have cluster crystalline phases at low temperatures can model a number of physical systems, such as vortices in type-1.5 superconductors, colloidal suspensions and cold atoms. In this work we study a…

Soft Condensed Matter · Physics 2019-04-29 Wenlong Wang , Rogelio Díaz-Méndez , Mats Wallin , Jack Lidmar , Egor Babaev

Monte Carlo algorithms are frequently used in atomistic simulations, including for computation of magnetic parameter temperature dependences in multiscale simulations. Even though parallelization strategies for Monte Carlo simulations of…

Mesoscale and Nanoscale Physics · Physics 2021-09-15 Serban Lepadatu , George McKenzie , Tim Mercer , Callum Robert MacKinnon , Philip Raymond Bissell

We demonstrate a scaling method for non-Markovian Monte Carlo wave-function simulations used to study open quantum systems weakly coupled to their environments. We derive a scaling equation, from which the result for the expectation values…

Quantum Physics · Physics 2009-11-10 J. Piilo , S. Maniscalco , A. Messina , F. Petruccione

We perform path integral Monte Carlo simulations to study the imaginary time dynamics of metastable supercooled superfluid states and nearly superglassy states of a one component fluid of spinless bosons square wells. Our study shows that…

Statistical Mechanics · Physics 2016-02-10 Riccardo Fantoni

To estimate the smoothing distribution in a nonlinear state space model, we apply the conditional particle filter with ancestor sampling. This gives an iterative algorithm in a Markov chain Monte Carlo fashion, with asymptotic convergence…

Computation · Statistics 2015-09-17 Andreas Svensson , Thomas B. Schön , Manon Kok

We present a quantum Monte Carlo method capable of sampling the full density matrix of a many-particle system at finite temperature. This allows arbitrary reduced density matrix elements and expectation values of complicated non-local…

Computational Physics · Physics 2015-06-15 N. S. Blunt , T. W. Rogers , J. S. Spencer , W. M. C. Foulkes

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…

Statistical Mechanics · Physics 2014-05-27 Jerome P. Nilmeier , Gavin E. Crooks , David D. L. Minh , John D. Chodera

We present molecular dynamics (MD) simulations results for dense fluids of ultrasoft, fully-penetrable particles. These are a binary mixture and a polydisperse system of particles interacting via the generalized exponential model, which is…

Soft Condensed Matter · Physics 2012-12-24 Daniele Coslovich , Marco Bernabei , Angel J. Moreno

We present an algorithm for Monte Carlo simulations of a nearest-neighbor spin ice model based on its cluster representation. To assess its performance, we estimate a relaxation time, and find that, in contrast to the Metropolis algorithm,…

Statistical Mechanics · Physics 2015-06-23 Hiromi Otsuka

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like…

Statistical Mechanics · Physics 2013-05-20 Karsten Schwarz , Heiko Rieger

We have used the Monte Carlo (MC) simulation method with Metropolis algorithm to study the finite temperature phase transition properties of a binary alloy spherical nanoparticle with radius $r$ of the type $A_{p}B_{1-p}$. The system…

Statistical Mechanics · Physics 2017-03-08 Z. D. Vatansever , E. Vatansever

We use an auxiliary-field Monte Carlo (AFMC) method to calculate thermodynamic properties (spin susceptibility and heat capacity) of ultra-small metallic grains in the presence of pairing correlations. This method allows us to study the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Y. Alhassid , L. Fang , S. Schmidt

Computer simulations are used to study a three-dimensional polydisperse model glassformer in a replica-coupling setup where an attractive field $\propto - \varepsilon Q$ of strength $\varepsilon$ can adjust the similarity of the system to a…

Soft Condensed Matter · Physics 2024-02-07 Niklas Küchler , Jürgen Horbach

In this paper, we present a very fast Monte Carlo scheme for additive processes: the computational time is of the same order of magnitude of standard algorithms for Brownian motions. We analyze in detail numerical error sources and propose…

Computational Finance · Quantitative Finance 2023-07-17 Michele Azzone , Roberto Baviera

I describe the classic circle-packing problem on a sphere, and the analytic and numerical approaches that have been used to study it. I then present a very simple Markov-chain Monte Carlo algorithm, which succeeds in finding the best…

Disordered Systems and Neural Networks · Physics 2007-05-23 Werner Krauth

Muon ionization cooling involves passing particles through solid or liquid absorbers. Careful simulations are required to design muon cooling channels. New features have been developed for inclusion in the transfer map code COSY Infinity to…

Accelerator Physics · Physics 2018-08-15 Josiah Kunz , Pavel Snopok , Martin Berz , Kyoko Makino

A kinetic Monte Carlo (KMC) method is used to study the structural properties and dynamics of a supercooled binary Lennard-Jones liquid around the glass transition temperature. This technique permits us to explore the potential energy…

Soft Condensed Matter · Physics 2015-06-24 Javier Hernandez-Rojas , David J. Wales

We combine Creutz energy conservation with Kawasaki spin exchange to simulate the microcanonical dynamics of a system of interacting particles. Relaxation occurs via Glauber spin-flip activation using a self-consistent temperature.…

Disordered Systems and Neural Networks · Physics 2007-05-23 Ralph V. Chamberlin , Kurt J. Stangel

A major challenge in simulating glassy systems is the ability to generate configurations that may be found in equilibrium at sufficiently low temperatures, in order to probe static and dynamic behaviour close to the glass transition. A…

Soft Condensed Matter · Physics 2024-06-19 Pallabi Das , Anshul D. S. Parmar , Srikanth Sastry