Particle models play an important role in many applications in physics, chemistry and biology. These can be studied on the computer with the help of molecular dynamics simulations. This book presents in detail the necessary numerical methods, the theoretical background and foundations and the techniques involved, including linked-cell method, SPME-method, tree codes, amd multipol technique. It illustrates such aspects as modeling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. The text goes on to offer detailed explanations of the different steps 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 step by step how to write programs capable of running successful experiments for molecular dynamics.

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.

Computer Simulation - a Key Technology.- From the Schrödinger Equation to Molecular Dynamics.- The Linked Cell Method for Short-Range Potentials.- Parallelization.- Extensions to More Complex Potentials and Molecules.- Time Integration Methods.- Mesh-Based Methods for Long-Range Potentials.- Tree Algorithms for Long-Range Potentials.- Applications from Biochemistry and Biophysics.- Prospects.