Transition Matrix Monte Carlo Method

We analyze a new Monte Carlo method which uses transition matrix in the space of energy. This method gives an efficient reweighting technique. The associated artificial dynamics is a constrained random walk in energy, producing the result that correlation time is proportional to the specific heat.Comment: LaTeX, 8 pages, 1 figur

Self-Learning Monte Carlo Method

Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of general and efficient update algorithm for large size systems close to phase transition or with strong frustrations, for which local updates perform badly. In this work, we propose a new general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup.Comment: add more refs and correct some typo

Optimized Monte Carlo Method for glasses

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other optimized Monte Carlo methods. Using the algorithm, we obtain finite size effects in the specific heat. This effect points to the existence of a large correlation length measurable in equal time correlation functions.Comment: Proceedings of "X International workshop on Disordered Systems" held in Molveno (Italy), March 200

Introduction to the Diffusion Monte Carlo Method

A self-contained and tutorial presentation of the diffusion Monte Carlo method for determining the ground state energy and wave function of quantum systems is provided. First, the theoretical basis of the method is derived and then a numerical algorithm is formulated. The algorithm is applied to determine the ground state of the harmonic oscillator, the Morse oscillator, the hydrogen atom, and the electronic ground state of the H2+ ion and of the H2 molecule. A computer program on which the sample calculations are based is available upon request.Comment: RevTeX 3.0, 14 pages, 8 EPS figures (included

The Coupled Electron-Ion Monte Carlo Method

In these Lecture Notes we review the principles of the Coupled Electron-Ion Monte Carlo methods and discuss some recent results on metallic hydrogen.Comment: 38 pages, 6 figures, Lecture notes for the International School of Solid State Physics, 34th course: "Computer Simulation in Condensed Matter: from Materials to Chemical Biology", 20 July-1 August 2005 Erice (Italy). To appear in Lecture Notes in Physics (2006