The past few years have witnessed a substantial growth in the number of applications for optimization algorithms in solving problems in the field of physics. Examples include determining the structure of molecules, estimating the parameters of interacting galaxies, the ground states of electronic quantum systems, the behavior of disordered magnetic materials, and phase transitions in combinatorial optimization problems.
This book serves as an introduction to the field, while also presenting a complete overview of modern algorithms. The authors begin with the relevant foundations from computer science, graph theory and statistical physics, before moving on to thoroughly explain algorithms - backed by illustrative examples. They include pertinent mathematical transformations, which in turn are used to make the physical problems tractable with methods from combinatorial optimization. Throughout, a number of interesting results are shown for all physical examples. The final chapter provides numerous practical hints on software development, testing programs, and evaluating the results of computer experiments.
Rezensionen / Stimmen
"...accessible to both physicists and computer scientists, this work explains the theoretical models and practical situations in physics which optimization problems occur..." (SciTech Book News, Vol. 26, No. 2, June 2002)
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Physiker, Angewandte Physiker, Ingenieure, Informatiker, Mathematiker
Illustrationen
5
195 s/w Abbildungen, 5 s/w Tabellen
illustrations
Maße
Höhe: 24 cm
Breite: 17 cm
Dicke: 23 mm
Gewicht
ISBN-13
978-3-527-40307-3 (9783527403073)
Schweitzer Klassifikation
Dr. Alexander K. Hartmann is a young scientist who has recently done interesting work applying optimization methods to several problems from physics.
Professor Heiko Rieger is an internationally well known expert in the physics of disordered systems. He has numerous publications which have led to important progress of this field.
Introduction to Optimization
Complexity Theory
Graphs
Simple Graph Algorithms
Introduction to Statistical Physics
Maximum-Flow Methods
Minimum-Cost Flow Problems
Genetic Algorithms
Monte-Carlo Methods
Approximation Methods for Spin Glasses
Matching Algorithms
Branch-and-Bound Methods
Practical Issues