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The advances in materials and biological sciences have necessitated the use of molecular simulations to study polymers. The Markov chain Monte Carlo simulations enable the sampling of relevant microstates of polymeric systems by traversing…

Soft Condensed Matter · Physics 2023-07-24 Monika Angwani , Tushar Mahendrakar , Kaustubh Rane

If a stochastic system during some periods of its evolution can be divided into non-interacting parts, the kinetics of each part can be simulated independently. We show that this can be used in the development of efficient Monte Carlo…

Materials Science · Physics 2009-11-13 V. I. Tokar , H. Dreyssé

Nuclear magnetic relaxation is widely used to probe protein dynamics. For decades, most analyses of relaxation in proteins have relied successfully on the model-free approach, forgoing mechanistic descriptions of motions. Model-free types…

The folding kinetics of three-dimensional lattice Go models with side chains is studied using two different Monte Carlo move sets. A flexible move set based on single, double and triple backbone moves is found to be far superior compared to…

Soft Condensed Matter · Physics 2009-11-07 Mai Suan Li , D. K. Klimov , D. Thirumalai

We propose an efficient Monte Carlo algorithm for the off-lattice simulation of dense hard sphere polymer melts using cluster moves, called event chains, which allow for a rejection-free treatment of the excluded volume. Event chains also…

Soft Condensed Matter · Physics 2015-09-24 Tobias Alexander Kampmann , Horst-Holger Boltz , Jan Kierfeld

A kinetic Monte Carlo approach is developed for studying growth and evaporation of nanoparticles on/off nanotubes. This study has been motivated by recent experimental advances in using nanoparticle evaporation (sublimation) off…

Mesoscale and Nanoscale Physics · Physics 2017-01-04 Vladimir Privman , Vyacheslav Gorshkov , Yuval E. Yaish

The protein folding problem is stated and a list of properties that do not depend upon specific molecules is compiled and analyzed. The relationship of this analysis to future simulations is emphasized. The choice of power and time as…

Biological Physics · Physics 2017-09-26 Walter A. Simmons

Unbiased stochastic sampling of the one- and two-body reduced density matrices is achieved in full configuration interaction quantum Monte Carlo with the introduction of a second, "replica" ensemble of walkers, whose population evolves in…

Computational Physics · Physics 2015-09-02 Robert E. Thomas , Daniel Opalka , Catherine Overy , Peter J. Knowles , Ali Alavi , George H. Booth

We consider Monte Carlo algorithms for the simulation of charged lattice gases with purely local dynamics. We study the mobility of particles as a function of temperature and show that the poor mobility of particles at low temperatures is…

Statistical Mechanics · Physics 2007-05-23 L. Levrel , A. C. Maggs

We develop a theoretical approach to the protein folding problem based on out-of-equilibrium stochastic dynamics. Within this framework, the computational difficulties related to the existence of large time scale gaps in the protein folding…

Quantitative Methods · Quantitative Biology 2009-11-13 M. Sega , P. Faccioli , F. Pederiva , G. Garberoglio , H. Orland

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

In this work, we introduce a simple modification of the Monte Carlo algorithm, which we call step Monte Carlo (sMC). The sMC approach allows to simulate processes far from equilibrium and obtain information about the dynamic properties of…

Other Condensed Matter · Physics 2023-12-15 Dariusz Sztenkiel

Two coarse-grained models for polymer chains in dense glass-forming polymer melts are studied by computer simulation: the bond-fluctuation model on a simple cubic lattice, where a bond-length potential favors long bonds, is treated by…

Soft Condensed Matter · Physics 2007-05-23 K. Binder , J. Baschnagel , C. Bennemann , W. Paul

We present a lattice-gas (generalised Ising) model for liquid droplets on solid surfaces. The time evolution in the model involves two processes: (i) Single-particle moves which are determined by a kinetic Monte Carlo algorithm. These…

Soft Condensed Matter · Physics 2019-11-06 Mounirah Areshi , Dmitri Tseluiko , Andrew J. Archer

We present a novel way of performing kinetic Monte Carlo simulations which does not require an {\it a priori} list of diffusion processes and their associated energetics and reaction rates. Rather, at any time during the simulation,…

Materials Science · Physics 2009-11-11 Oleg Trushin , Altaf Karim , Abdelkader Kara , Talat S. Rahman

We present a method to model the interaction and the dynamics of atoms excited to Rydberg states. We show a way to solve the optical Bloch equations for laser excitation of the frozen gas in good agreement with the experiment. A second…

Atomic Physics · Physics 2009-11-13 Amodsen Chotia , Matthieu Viteau , Thibault Vogt , Daniel Comparat , Pierre Pillet

We provide evidence that the energy landscapes of folded proteins do not shift with temperature, but the onset of functional dynamics is associated with its effective sampling. The motion of the backbone is described by three distinct…

Soft Condensed Matter · Physics 2007-05-23 Canan Baysal , Ali Rana Atilgan

In recent work [Coretti et al., The Journal of Chemical Physics, 2018, 149, 191102], a new algorithm to solve numerically the dynamics of the shell model for polarization was presented. The approach, broadly applicable to systems involving…

Statistical Mechanics · Physics 2020-06-24 Sara Bonella , Alessandro Coretti , Rodolphe Vuilleumier , Giovanni Ciccotti

The behavior of a Lattice Monte Carlo algorithm (if it is designed correctly) must approach that of the continuum system that it is designed to simulate as the time step and the mesh step tend to zero. However, we show for an algorithm for…

Statistical Mechanics · Physics 2010-08-23 Mykyta V. Chubynsky , Gary W. Slater

Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools.…

Biological Physics · Physics 2019-11-25 Frank Noé , Gianni De Fabritiis , Cecilia Clementi
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