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.

Monte Carlo Optimization, Simulation and Sensitivity of Queueing Networks

Abstract: Antithetic and Common Random Variables in Simulation of Complex Stochastic Systems. Multidimensional Control Variates in Monte Carlo Simulation. Stochastic Optimization Via Stochastic Approximation. Perturbation Analysis for Sensitivity and Optimization of Complex Queueing Networks. Monte Carlo Optimization. Appendixes. References. Index.

Adaptative Monte Carlo Method, A Variance Reduction Technique

Abstract: In this article we propose an adaptative variance reduction method for Monte Carlo simulations. The method uses importance sampling scheme based on a change of drift. The change of drift is selected adaptatively through the Monte Carlo computation by using a suitable sequence of approximation. We state and prove theoretical results supporting the use of the method. We develop two applications of the procedure for variance reduction in a Monte Carlo computation in finance and in reliability.

Population Monte Carlo algorithms

Abstract: We give a cross-disciplinary survey on “population” Monte Carlo algorithms.In these algorithms, a set of “walkers” or “particles” is used as a representation of a high-dimensional vector. The computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms — “quantum Monte Carlo”, “transfer-matrix Monte Carlo”, “Monte Carlo filter (particle filter)”, “sequential Monte Carlo” and “PERM” etc. Here we discuss them in a coherent framework. We also touch on related algorithms —genetic algorithms and annealed importance sampling.

A novel approach for introducing the electron-electron and electron-impurity interactions in particle-based simulations

Abstract: A new method for employed electron-electron (e-e) and electron-ion (e-i) interactions in Monte Carlo particle based simulators is presented. By using a corrected Coulomb force in conjunction with a proper cutoff range, the "double" counting of the long range interaction is eliminated while reducing the simulation time for molecular dynamics by a factor of 1000. The proposed method naturally incorporated the multi-ion contributions, local distortions in the scattering potential due to the movement of the free charges, and carrier-density fluctuations. The doping dependence of the low-field mobility obtained from three-dimensional (3-D) resistor simulation closely follows experimental results, thus proving the correctness of the proposed approach.

Monte Carlo methods in electronic structures for large systems.

Abstract: Quantum Monte Carlo methods have recently made it possible to calculate the electronic structure of relatively large molecular systems with very high accuracy. These large systems range from positron complexes [NH2,Ps] with ∼10 electrons to C20 isomers with 120 electrons, to silicon crystal structures of 250 atoms and 1000 valence electrons. The techniques for such calculations and a sampling of applications are reviewed.