This book details the necessary numerical methods, the theoretical background and foundations and the techniques involved in creating computer particle models, including linked-cell method, SPME-method, tree codes, amd multipol technique. It illustrates modeling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. The text offers step-by-step explanations of numerical simulation, providing illustrative code examples. With the description of the algorithms and the presentation of the results of various simulations from fields such as material science, nanotechnology, biochemistry and astrophysics, the reader of this book will learn how to write programs capable of running successful experiments for molecular dynamics.

First time paperback of successful physics monograph. Copyright © Libri GmbH. All rights reserved.

This book presents computer simulations using molecular dynamics techniques in statistical physics, with a focus on macromolecular systems. The numerical methods are introduced in the form of computer algorithms and can be implemented in computers using any desired computer programming language, such as Fortran 90, C/C++, and others. The book also explains how some of these numerical methods and their algorithms can be implemented in the existing computer programming software of macromolecular systems, such as the CHARMM program. In addition, it examines a number of advanced concepts of computer simulation techniques used in statistical physics as well as biological and physical systems. Discussing the molecular dynamics approach in detail to enhance readers understanding of the use of this method in statistical physics problems, it also describes the equations of motion in various statistical ensembles to mimic real-world experimental conditions. Intended for graduate students and research scientists working in the field of theoretical and computational biophysics, physics and chemistry, the book can also be used by postgraduate students of other disciplines, such as applied mathematics, computer sciences, and bioinformatics. Further, offering insights into fundamental theory, it as a valuable resource for expert practitioners and programmers and those new to the field.

This book describes the mathematical underpinnings of algorithms used for molecular dynamics simulation, including both deterministic and stochastic numerical methods. Molecular dynamics is one of the most versatile and powerful methods of modern computational science and engineering and is used widely in chemistry, physics, materials science and biology. Understanding the foundations of numerical methods means knowing how to select the best one for a given problem (from the wide range of techniques on offer) and how to create new, efficient methods to address particular challenges as they arise in complex applications. Aimed at a broad audience, this book presents the basic theory of Hamiltonian mechanics and stochastic differential equations, as well as topics including symplectic numerical methods, the handling of constraints and rigid bodies, the efficient treatment of Langevin dynamics, thermostats to control the molecular ensemble, multiple time-stepping, and the dissipative particle dynamics method.

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.

Computer simulation is an essential tool in studying the chemistry and physics of liquids. Simulations allow us to develop models and to test them against experimental data. This book is an introduction and practical guide to the molecular dynamics and Monte Carlo methods.

7.1 Introduction -- 7.2 Rotational Energy Exchange Models -- 7.2.1 Constant Collision Number -- 7.2.2 The Parker Model -- 7.2.3 Variable Probability Exchange Model of Boyd -- 7.2.4 Nonequilibrium Direction Dependent Model -- 7.2.5 Model Results -- 7.3 Vibrational Energy Exchange Models -- 7.3.1 Constant Collision Number -- 7.3.2 The Millikan-White Model -- 7.3.3 Quantized Treatment for Vibration -- 7.3.4 Model Results -- 7.4 Dissociation Chemical Reactions -- 7.4.1 Total Collision Energy Model -- 7.4.2 Redistribution of Energy Following a Dissociation Reaction -- 7.4.3 Vibrationally Favored Dissociation Model -- 7.5 General Chemical Reactions -- 7.5.1 Reaction Rates and Equilibrium Constant -- 7.5.2 Backward Reaction Rates in DSMC -- 7.5.3 Three-Body Recombination Reactions -- 7.5.4 Post-Reaction Energy Redistribution and General Implementation -- 7.5.5 DSMC Solutions for Reacting Flows -- 7.6 Summary -- Appendix A: Generating Particle Properties -- Appendix B: Collisional Quantities -- Appendix C: Determining Post-Collision Velocities -- Appendix D: Macroscopic Properties -- Appendix E: Common Integrals -- References -- Index

Provides hands-on knowledge enabling students of and researchers in chemistry, biology, and engineering to perform molecular simulations This book introduces the fundamentals of molecular simulations for a broad, practice-oriented audience and presents a thorough overview of the underlying concepts. It covers classical mechanics for many-molecule systems as well as force-field models in classical molecular dynamics; introduces probability concepts and statistical mechanics; and analyzes numerous simulation methods, techniques, and applications. Molecular Simulations: Fundamentals and Practice starts by covering Newton's equations, which form the basis of classical mechanics, then continues on to force-field methods for modelling potential energy surfaces. It gives an account of probability concepts before subsequently introducing readers to statistical and quantum mechanics. In addition to Monte-Carlo methods, which are based on random sampling, the core of the book covers molecular dynamics simulations in detail and shows how to derive critical physical parameters. It finishes by presenting advanced techniques, and gives invaluable advice on how to set up simulations for a diverse range of applications. -Addresses the current need of students of and researchers in chemistry, biology, and engineering to understand and perform their own molecular simulations -Covers the nitty-gritty ? from Newton's equations and classical mechanics over force-field methods, potential energy surfaces, and probability concepts to statistical and quantum mechanics -Introduces physical, chemical, and mathematical background knowledge in direct relation with simulation practice -Highlights deterministic approaches and random sampling (eg: molecular dynamics versus Monte-Carlo methods) -Contains advanced techniques and practical advice for setting up different simulations to prepare readers entering this exciting field Molecular Simulations: Fundamentals and Practice is an excellent book benefitting chemist, biologists, engineers as well as materials scientists and those involved in biotechnology.

On May 21-24, 1997 the Second International Symposium on Algorithms for Macromolecular Modelling was held at the Konrad Zuse Zentrum in Berlin. The event brought together computational scientists in fields like biochemistry, biophysics, physical chemistry, or statistical physics and numerical analysts as well as computer scientists working on the advancement of algorithms, for a total of over 120 participants from 19 countries. In the course of the symposium, the speakers agreed to produce a representative volume that combines survey articles and original papers (all refereed) to give an impression of the present state of the art of Molecular Dynamics. The 29 articles of the book reflect the main topics of the Berlin meeting which were i) Conformational Dynamics, ii) Thermodynamic Modelling, iii) Advanced Time-Stepping Algorithms, iv) Quantum-Classical Simulations and Fast Force Field and v) Fast Force Field Evaluation.

This book constitutes the refereed proceedings of the 14th International Conference on High-Performance Computing, HiPC 2007, held in Goa, India, in December 2007. The 53 revised full papers presented together with the abstracts of five keynote talks were carefully reviewed and selected from 253 submissions. The papers are organized in topical sections on a broad range of applications including I/O and FPGAs, and microarchitecture and multiprocessor architecture.