When learning very formal material one comes to a stage where one thinks one has understood the material. Confronted with a "realiife" problem, the passivity of this understanding sometimes becomes painfully elear. To be able to solve the problem, ideas, methods, etc. need to be ready at hand. They must be mastered (become active knowledge) in order to employ them successfully. Starting from this idea, the leitmotif, or aim, of this book has been to elose this gap as much as possible. How can this be done? The material presented here was born out of a series of lectures at the Summer School held at Figueira da Foz (Portugal) in 1987. The series of lectures was split into two concurrent parts. In one part the "formal material" was presented. Since the background of those attending varied widely, the presentation of the formal material was kept as pedagogic as possible. In the formal part the general ideas behind the Monte Carlo method were developed. The Monte Carlo method has now found widespread appli cation in many branches of science such as physics, chemistry, and biology. Because of this, the scope of the lectures had to be narrowed down. We could not give a complete account and restricted the treatment to the ap plication of the Monte Carlo method to the physics of phase transitions. Here particular emphasis is placed on finite-size effects.
Appropriately for a book having the title "Computer Simulation Methods in Theoretical Physics", this book begins with a disclai mer. It does not and cannot give a complete introduction to simu lational physics. This exciting field is too new and is expanding too rapidly for even an attempt to be made. The intention here is to present a selection of fundamental techniques that are now being widely applied in many areas of physics, mathematics, chem istry and biology. It is worth noting that the methods are not only applicable in physics. They have been successfully used in other sciences, showing their great flexibility and power. This book has two main chapters (Chaps. 3 and 4) dealing with deterministic and stochastic computer simulation methods. Under the heading "deterministic" are collected methods involving classical dynamics, i.e. classical equations of motion, which have become known as the molecular dynamics simulation method. The se cond main chapter deals with methods that are partly or entirely of a stochastic nature. These include Brownian dynamics and the Monte Carlo method. To aid understanding of the material and to develop intuition, problems are included at the end of each chapter. Upon a first reading, the reader is advised to skip Chapter 2, which is a general introduction to computer simUlation methods.
Our aim in this book is to present and enlarge upon those aspects of parallel computing that are needed by practitioners of computational science. Today al most all classical sciences, such as mathematics, physics, chemistry and biology, employ numerical methods to help gain insight into nature. In addition to the traditional numerical methods, such as matrix inversions and the like, a whole new field of computational techniques has come to assume central importance, namely the numerical simulation methods. These methods are much less fully developed than those which are usually taught in a standard numerical math ematics course. However, they form a whole new set of tools for research in the physical sciences and are applicable to a very wide range of problems. At the same time there have been not only enormous strides forward in the speed and capability of computers but also dramatic new developments in computer architecture, and particularly in parallel computers. These improvements offer exciting prospects for computer studies of physical systems, and it is the new techniques and methods connected with such computer simulations that we seek to present in this book, particularly in the light of the possibilities opened up by parallel computers. It is clearly not possible at this early stage to write a definitive book on simulation methods and parallel computing.
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