Monte Carlo molecular modeling

About: Monte Carlo molecular modeling is a research topic. Over the lifetime, 11307 publications have been published within this topic receiving 409122 citations.

Optimized monte carlo methods

Abstract: I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, such as Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. Reweighted data analysis and multihistogramming are also discussed. I introduce simulated tempering, and, as an example, its application to the random field Ising model. I illustrate parallel tempering, and discuss some crucial technical details such as thermalization and volume scaling. I give a general perspective by discussing umbrella methods and the multicanonical approach.

Surrogate models for uncertainty quantification: An overview

Abstract: Uncertainty quantification has become a hot topic in computational sciences in the last decade. Indeed computer models (a.k.a simulators) are becoming more and more complex and demanding, yet the knowledge of the input parameters to feed into the model is usually limited. Based on the available data and possibly expert knowledge, parameters are represented by random variables. Of crucial interest is the propagation of the uncertainties through the simulator so as to estimate statistics of the quantities of interest. Monte Carlo simulation, a popular technique based on random number simulation, is unaffordable in practice when each simulator run takes minutes to hours. In this contribution we shortly review recent techniques to bypass Monte Carlo simulation, namely surrogate models. The basics of polynomial chaos expansions and low-rank tensor approximations are given together with hints on how to derive the statistics of interest, namely moments, sensitivity indices or probabilities of failure.

Randomness-induced second-order transition in the two-dimensional eight-state Potts model: A Monte Carlo study.

Abstract: We have studied the effect of quenched, bond randomness on the nature of the phase transition in the two-dimensional eight-state Potts model. Through extensive Monte Carlo simulations, we confirm that the phase transition changes from first order to second order. A finite-size-scaling analysis of several thermodynamic quantities strongly suggests that the critical exponents fall into the universality class of the two-dimensional Ising model.

Simulation and prediction of vapour-liquid equilibria for chain molecules

Abstract: Monte Carlo simulations of phase equilibria for Lennard-Jones chains of intermediate length are performed in the Gibbs ensemble using configurational bias sampling. Simulations of phase equilibria for square-well chains of up to 100 segments are performed using the NPT-μ method and newly proposed Monte Carlo moves. A two-reference-fluid equation of state is developed to describe the pressure-volume-temperature properties of square-well and Lennard-Jones chains. The phase envelopes predicted by such an equation are in good agreement with results of simulations. This equation is also shown to be superior to models derived from first-order thermodynamic perturbation theory (TPT1).

A Monte Carlo calculation on the scattering of electrons in copper

Abstract: The Monte Carlo method described by Green in 1963 has been used to investigate the scattering of 29 kev electrons in a copper target. The results are compared with experimental data and are used to suggest how theoretical expressions obtained for an infinite solid may be modified to apply to the practical case of a semi-infinite target.