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We present a study of the parallel tempering (replica exchange) Monte Carlo method, with special focus on the feedback-optimized parallel tempering algorithm, used for generating an optimal set of simulation temperatures. This method is…

Statistical Mechanics · Physics 2014-10-15 Krzysztof Lewandowski , Piotr Knychala , Michal Banaszak

We propose a Multi-Cell Monte Carlo algorithm, or (MC)^2, for predicting stable phases in chemically complex crystalline systems. Free atomic transfer among cells is achieved via the application of the lever rule, where an assigned molar…

Materials Science · Physics 2018-11-13 Changning Niu , You Rao , Wolfgang Windl , Maryam Ghazisaeidi

In this work, we consider the problem of estimating summary statistics to characterise biochemical reaction networks of interest. Such networks are often described using the framework of the Chemical Master Equation (CME). For…

Quantitative Methods · Quantitative Biology 2018-11-27 Christopher Lester , Christian A. Yates , Ruth E. Baker

We have developed a technique to accelerate the acquisition of effectively uncorrelated configurations for off-lattice models of dense polymer melts which makes use of both parallel tempering and large scale Monte Carlo moves. The method is…

Soft Condensed Matter · Physics 2009-10-31 Alex Bunker , Burkhard Duenweg

An off-lattice Monte Carlo algorithm for solutions of equilibrium polymers (EP) is proposed. At low and moderate densities this is shown to reproduce faithfully the (static) properties found recently for flexible linear EP using a lattice…

Statistical Mechanics · Physics 2009-10-31 A. Milchev , J. P. Wittmer , D. P. Landau

A general synthetic iterative scheme is proposed to solve the Enskog equation within a Monte Carlo framework. The method demonstrates rapid convergence by reducing intermediate Monte Carlo evolution and preserves the asymptotic-preserving…

Fluid Dynamics · Physics 2025-09-26 Bin Hu , Liyan Luo , Lei Wu

Reinforcement learning constantly deals with hard integrals, for example when computing expectations in policy evaluation and policy iteration. These integrals are rarely analytically solvable and typically estimated with the Monte Carlo…

Machine Learning · Computer Science 2022-02-23 Sebastien M. R. Arnold , Pierre L'Ecuyer , Liyu Chen , Yi-fan Chen , Fei Sha

We present a new, biased Monte Carlo scheme for simulating complex, cyclic peptides. Backbone atoms are equilibrated with a biased rebridging scheme, and side-chain atoms are equilibrated with a look-ahead configurational bias Monte Carlo.…

Biological Physics · Physics 2009-10-31 Minghong G. Wu , Michael W. Deem

We consider a theoretical model for a binary mixture of colloidal particles and spherical emulsion droplets. The hard sphere colloids interact via additional short-ranged attraction and long-ranged repulsion. The droplet-colloid interaction…

Soft Condensed Matter · Physics 2012-01-11 Ingmar Schwarz , Andrea Fortini , Claudia Simone Wagner , Alexander Wittemann , Matthias Schmidt

We present a novel approach that allows to calculate the dielectric response of periodic systems in the quantum Monte Carlo formalism. We employ a many-body generalization for the electric enthalpy functional, where the coupling with the…

Other Condensed Matter · Physics 2009-11-11 P. Umari , A. J. Williamson , Giulia Galli , Nicola Marzari

In complex systems with many degrees of freedom such as spin glass and biomolecular systems, conventional simulations in canonical ensemble suffer from the quasi-ergodicity problem. A simulation in generalized ensemble performs a random…

Statistical Mechanics · Physics 2008-06-24 Y. Okamoto

Reaction networks in the bulk and on surfaces are widespread in physical, chemical and biological systems. In macroscopic systems, which include large populations of reactive species, stochastic fluctuations are negligible and the reaction…

Statistical Mechanics · Physics 2007-10-12 Baruch Barzel , Ofer Biham , Raz Kupferman

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in…

Strongly Correlated Electrons · Physics 2016-06-10 Kensaku Takai , Kota Ido , Takahiro Misawa , Youhei Yamaji , Masatoshi Imada

With the path integral approach, the thermal average in a multi-electronic-state quantum systems can be approximated by the ring polymer representation on an extended configuration space, where the additional degrees of freedom are…

Numerical Analysis · Mathematics 2020-11-24 Xiaoyu Lei , Zhennan Zhou

On the base of the diffusion Monte-Carlo method we develop the method allowing to simulate the quantum systems with complex wave function. The method is exact and there are no approximations on the simulations of the module and the phase of…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

A Monte Carlo method to sample the classical configurational canonical ensemble is introduced. In contrast to the Metropolis algorithm, where trial moves can be rejected, in this approach collisions take place. The implementation is…

Statistical Mechanics · Physics 2015-03-19 E. A. J. F. Peters , G. de With

Particle methods based on evolving the spatial derivatives of the solution were originally introduced to simulate reaction-diffusion processes, inspired by vortex methods for the Navier--Stokes equations. Such methods, referred to as…

Numerical Analysis · Mathematics 2025-01-24 Giulia Bertaglia , Lorenzo Pareschi , Russel E. Caflisch

We present a new and general Monte Carlo iteration method for generalized ensembles. It consists of two elements: (1) a simple algorithm to distinguish between distributions arising from respectively equilibrium- and non-equilibrium…

Condensed Matter · Physics 2007-05-23 J. Borg

A simple Monte Carlo (MC) algorithm for the simulation of the passage of low-energy gamma rays and electrons through any material medium is presented. The algorithm includes several approximations that accelerate the simulation while…

Accelerator Physics · Physics 2023-10-25 Víctor Moya , Jaime Rosado , Fernando Arqueros

The electrostatic potential in the neighborhood of a biomolecule can be computed thanks to the non-linear divergence-form elliptic Poisson-Boltzmann PDE. Dedicated Monte-Carlo methods have been developed to solve its linearized version (see…

Numerical Analysis · Mathematics 2016-11-15 Mireille Bossy , Nicolas Champagnat , Helene Leman , Sylvain Maire , Laurent Violeau , Mariette Yvinec