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A Monte Carlo method is given to compute the binding affinity of a ligand to a protein. The method involves extending configuration space by a discrete variable indicating whether the ligand is bound to the protein and a special Monte Carlo…

Statistical Mechanics · Physics 2007-05-23 Charles F. F. Karney , Jason E. Ferrara , Stephan Brunner

We calculate the efficiency of a rejection-free dynamic Monte Carlo method for $d$-dimensional off-lattice homogeneous particles interacting through a repulsive power-law potential $r^{-p}$. Theoretically we find the algorithmic efficiency…

Statistical Mechanics · Physics 2009-11-13 Marta L. Guerra , M. A. Novotny , Hiroshi Watanabe , Nobuyasu Ito

We show how to generalize the Lattice Switch Monte Carlo method to calculate the phase diagram of a binary system. A global coordinate transformation is combined with a modification of particle diameters, enabling the multi-component system…

Statistical Mechanics · Physics 2009-11-13 A. N. Jackson , G. J. Ackland

Real-space quantum Monte Carlo is used to calculate the total atomization energy of benzene. In contrast to orbital-space methods common in quantum chemistry, real-space methods allow results at near the complete-basis-set limit to be…

Strongly Correlated Electrons · Physics 2021-07-21 Iliya Sabzevari , Sandeep Sharma

An efficient method for computing thermodynamic equilibrium states at the micromagnetic length scale is introduced, using the Markov chain Monte Carlo method. Trial moves include not only rotations of vectors, but also a change in their…

Mesoscale and Nanoscale Physics · Physics 2021-11-10 Serban Lepadatu

In this text, we implement a monte carlo algorithm to study thermodynamic properties of ice. Our program, written in Python, is open-sourced and available at https://github.com/AKnightWing/ColdAsIce. We develop a novel scheme to compute the…

Statistical Mechanics · Physics 2020-10-13 Tanmay Bhore , Siddharth Chaini , Siddharth Bachoti , Vipin Khade , Vinay Patil

We present a new Monte Carlo scheme for the efficient simulation of multi-polymer systems. The method permits chains to be inserted into the system using a biased growth technique. The growth proceeds via the use of a retractable feeler,…

Statistical Mechanics · Physics 2009-10-31 S. Consta , N. B. Wilding , D. Frenkel , Z. Alexandrowicz

A Monte-Carlo approach to proton stopping in warm dense matter is implemented into an existing particle-in-cell code. The model is based on multiple binary-collisions among electron-electron, electron-ion and ion-ion, taking into account…

Plasma Physics · Physics 2017-02-22 D. Wu , X. T. He , W. Yu , S. Fritzsche

We propose a new Monte Carlo method for efficiently sampling trajectories with fixed initial and final conditions in a system with discrete degrees of freedom. The method can be applied to any stochastic process with local interactions,…

Statistical Mechanics · Physics 2012-03-30 Thierry Mora , Aleksandra M. Walczak , Francesco Zamponi

We provide a complete thermodynamic solution of a 1D hopping model in the presence of a random potential by obtaining the density of states. Since the partition function is related to the density of states by a Laplace transform, the…

Quantitative Methods · Quantitative Biology 2009-11-13 Gelio Alves , Yi-Kuo Yu

It is a long-standing challenge to accurately and efficiently compute thermodynamic quantities of many-body systems at thermal equilibrium. The conventional methods, e.g., Markov chain Monte Carlo, require many steps to equilibrate. The…

Statistical Mechanics · Physics 2025-12-10 Shuo-Hui Li , Yao-Wen Zhang , Ding Pan

We combine the principle of gauge invariance with extrinsic string geometry to develop a lattice model that can be employed to theoretically describe properties of chiral, unbranched homopolymers. We find that in its low temperature phase…

Statistical Mechanics · Physics 2014-11-18 Ulf H. Danielsson , Martin Lundgren , Antti J. Niemi

We perform simulations for long hard-sphere polymer chains using a recently developed binary-tree based Monte Carlo method. Systems in two to five dimensions with free and periodic boundary conditions and up to $10^7$ repeat units are…

Soft Condensed Matter · Physics 2023-12-01 Stefan Schnabel , Wolfhard Janke

We present a novel implementation of the parallel tempering Monte Carlo method in a multicanonical ensemble. Multicanonical weights are derived by a self-consistent iterative process using a Boltzmann inversion of global energy histograms.…

Soft Condensed Matter · Physics 2009-11-07 Roland Faller , Qiliang Yan , Juan J. de Pablo

Starting from a master equation in a quantum Hamilton form we study analytically a nonequilibrium system which is coupled locally to two heat bathes at different temperatures. Based on a lattice gas description an evolution equation for the…

Statistical Mechanics · Physics 2007-05-23 Steffen Trimper , Simone Artz

We develop the hybrid Monte Carlo method for simulations of single off-lattice polymer chains. We discuss implementation and choice of simulation parameters in some detail. The performance of the algorithm is tested on models for…

High Energy Physics - Lattice · Physics 2009-10-22 A. Irbäck

We determined scaling laws for the numerical effort to find the optimal configurations of a simple model potential energy surface (PES) with a perfect funnel structure that reflects key characteristics of the protein interactions.…

Biological Physics · Physics 2009-10-31 K. Hamacher , W. Wenzel

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

Restricted path integral Monte Carlo simulations are used to calculate the equilibrium properties of hydrogen in the density and temperature range of $9.83 \times 10^{-4}\rm \leq \rho \leq 0.153 \rm gcm^{-3}$ and $5000 \leq T \leq 250 000…

Plasma Physics · Physics 2009-11-07 B. Militzer , D. M. Ceperley

We translate the problem of calculating the entropy of a set of binary configurations/signals into a sequence of supervised classification tasks. Subsequently, one can use virtually any machine learning classification algorithm for…

Statistical Mechanics · Physics 2019-10-25 Romuald A. Janik