Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000010298297 | QC174.85.M64 N49 1999 | Open Access Book | Book | Searching... |
On Order
Summary
Summary
This book provides an introduction to Monte Carlo simulations in classical statistical physics and is aimed both at students beginning work in the field and at more experienced researchers who wish to learn more about Monte Carlo methods. The material covered includes methods for both equilibrium and out of equilibrium systems, and common algorithms like the Metropolis and heat-bath algorithms are discussed in detail, as well as more sophisticated ones such as continuous time Monte Carlo, cluster algorithms, multigrid methods, entropic sampling and simulated tempering. Data analysis techniques are also explained starting with straightforward measurement and error-estimation techniques and progressing to topics such as the single and multiple histogram methods and finite size scaling. The last few chapters of the book are devoted to implementation issues, including discussions of such topics as lattice representations, efficient implementation of data structures, multispin coding, parallelization of Monte Carlo algorithms, and random number generation. At the end of the book the authors give a number of example programmes demonstrating the applications of these techniques to a variety of well-known models.
Author Notes
MarkNewmanSanta Fe Institute, New Mexico.
Table of Contents
I Equilibrium Monte Carlo calculations |
1 Introduction |
2 The principles of equilibrium thermal Monte Carlo simulations |
3 The Ising model and the Metropolis algorithm |
4 Other algorithms for the Ising model |
5 The conserved-order-parameter Ising model |
6 Disordered spin models |
7 Ice models |
8 Analysing Monte Carlo data |
II Out-of-equilibrium calculations |
9 Principles of out-of-equilibrium Monte Carlo simulation |
10 Non-equilibrium simulations of the Ising model |
11 Monte Carlo simulations in surface science |
12 The repton model |
III Implementation |
13 Lattices and data structures |
14 Monte Carlo simulations on parallel computers |
15 Multispin coding |
16 Random numbers |