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The quantum Monte Carlo (QMC) method is gaining interest as a complement to basis set ab initio methods in cases where high accuracy computation of atomic and molecular properties is desired. This volume focuses on recent advances in this area. QMC as used here refers to methods that directly solve the Schrödinger equation, for example, diffusion and Green's function Monte Carlo, as well as variational Monte Carlo. The latter is an approach to computing atomic and molecular properties by the Monte Carlo method that has fundamental similarities to basis set methods with the exception that the l
Monte Carlo method. --- Quantum chemistry. --- Chemistry, Quantum --- Chemistry, Physical and theoretical --- Quantum theory --- Excited state chemistry --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Quantum Monte Carlo methods. --- QMC methods --- QMC techniques --- Quantum Monte Carlo techniques --- Monte Carlo method --- Quantum statistics
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Operational research. Game theory --- #PEDA *012.4 --- #SBIB:303H10 --- #SBIB:303H30 --- #SBIB:303H510 --- #PBIB:2003.3 --- Monte Carlo method --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Methoden en technieken: algemene handboeken en reeksen --- Kwalitatieve methoden: algemeen --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Engineering & Applied Sciences --- Applied Mathematics --- Monte Carlo method.
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Monte Carlo Simulation in Statistical Physics deals with the computer simulation of thermodynamic properties of many-body condensed-matter systems that use random numbers generated by a computer in physics and chemistry. It describes the theoretical background of several variants of these Monte Carlo methods and gives a systematic course by which newcomers can learn to perform such simulations and to analyze their results. This third edition has been updated and a new chapter on some important recent developments of the Monte Carlo methodology was added.
Monte Carlo method. --- Random walks (Mathematics). --- Statistical physics. --- Monte Carlo method --- Statistical physics --- Random walks (Mathematics) --- Monte-Carlo, Méthode de --- Physique statistique --- Promenades aléatoires (Mathématiques) --- Physics. --- Thermodynamics. --- Dynamical systems. --- Condensed matter. --- Physical chemistry. --- Mathematical Methods in Physics. --- Numerical and Computational Physics, Simulation. --- Complex Systems. --- Condensed Matter Physics. --- Physical Chemistry. --- Chemistry, Theoretical --- Physical chemistry --- Theoretical chemistry --- Chemistry --- Condensed materials --- Condensed media --- Condensed phase --- Materials, Condensed --- Media, Condensed --- Phase, Condensed --- Liquids --- Matter --- Solids --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical statistics --- Chemistry, Physical and theoretical --- Dynamics --- Heat --- Heat-engines --- Quantum theory --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Statistical methods --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes
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