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Here is an English translation of a 1955 paper by Walter Noll exposing fundamentals of statistical mechanics that are important in the modeling of small-scale behaviour and its link to macroscopic observations. Includes four invited papers on related topics.
By uniting basic concepts in equilibrium and time-dependent statistical mechanics with modern computational techniques, the book provides a comprehensive view of how theory proceeds from concepts to model construction to practical algorithms.
This coherent collection of theory, algorithms, and illustrative results presents the field of nonequilibrium molecular dynamics in detail.
This highly informative and carefully presented book comprises select proceedings of Foundation for Molecular Modelling and Simulation (FOMMS 2018). The contents are written by invited speakers centered on the theme Innovation for Complex Systems. It showcases new developments and applications of computational quantum chemistry, statistical mechanics, molecular simulation and theory, and continuum and engineering process simulation. This volume will serve as a useful reference to researchers, academicians and practitioners alike.
"There is a symbiotic relationship between theoretical nonequilibrium statistical mechanics on the one hand and the theory and practice of computer simulation on the other. Sometimes, the initiative for progress has been with the pragmatic requirements of computer simulation and at other times, the initiative has been with the fundamental theory of nonequilibrium processes. This book summarises progress in this field up to 1990"--Publisher's description.
Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practical use in the case studies used in the text. Since the first edition only five years ago, the simulation world has changed significantly -- current techniques have matured and new ones have appeared. This new edition deals with these new developments; in particular, there are sections on: - Transition path sampling and diffusive barrier crossing to simulaterare events - Dissipative particle dynamic as a course-grained simulation technique - Novel schemes to compute the long-ranged forces - Hamiltonian and non-Hamiltonian dynamics in the context constant-temperature and constant-pressure molecular dynamics simulations - Multiple-time step algorithms as an alternative for constraints - Defects in solids - The pruned-enriched Rosenbluth sampling, recoil-growth, and concerted rotations for complex molecules - Parallel tempering for glassy Hamiltonians Examples are included that highlight current applications and the codes of case studies are available on the World Wide Web. Several new examples have been added since the first edition to illustrate recent applications. Questions are included in this new edition. No prior knowledge of computer simulation is assumed.
This volume of proceedings contains an updated glance at recent developments in statistical physics. Topics discussed include structural and transport properties of colloidal suspensions and polymeric systems, Monte Carlo and Molecular Dynamics simulations of fluids, topological aspects of wetting and other critical phenomena, reaction-diffusion equations and the statistical mechanics of solids under stress.
Scientists are increasingly finding themselves engaged in research problems that cross the traditional disciplinary lines of physics, chemistry, biology, materials science, and engineering. Because of its broad scope, statistical mechanics is an essential tool for students and more experienced researchers planning to become active in such an interdisciplinary research environment. Powerful computational methods that are based in statistical mechanics allow complex systems to be studied at an unprecedented level of detail. This book synthesizes the underlying theory of statistical mechanics with the computational techniques and algorithms used to solve real-world problems and provides readers with a solid foundation in topics that reflect the modern landscape of statistical mechanics. Topics covered include detailed reviews of classical and quantum mechanics, in-depth discussions of the equilibrium ensembles and the use of molecular dynamics and Monte Carlo to sample classical and quantum ensemble distributions, Feynman path integrals, classical and quantum linear-response theory, nonequilibrium molecular dynamics, the Langevin and generalized Langevin equations, critical phenomena, techniques for free energy calculations, machine learning models, and the use of these models in statistical mechanics applications. The book is structured such that the theoretical underpinnings of each topic are covered side by side with computational methods used for practical implementation of the theoretical concepts.
This work contains a detailed review of classical and quantum mechanics, in-depth discussions of the most commonly used ensembles simultaneously with modern computational techniques such as molecular dynamics. It also covers important topics such as free-energy calculations, linear-response theory and critical phenomena.