The Monte Carlo Method in Condensed Matter Physics

1. Front Matter

   Pages I-XVI

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2. Introduction

   • Kurt Binder

   Pages 1-22

3. Vectorisation of Monte Carlo Programs for Lattice Models Using Supercomputers

   • David P. Landau

   Pages 23-51

4. Parallel Algorithms for Statistical Physics Problems

   • Dieter W. Heermann, Anthony N. Burkitt

   Pages 53-74

5. New Monte Carlo Methods for Improved Efficiency of Computer Simulations in Statistical Mechanics

   • Robert H. Swendsen, Jian-Sheng Wang, Alan M. Ferrenberg

   Pages 75-91

6. Simulation of Random Growth Processes

   • Hans J. Herrmann

   Pages 93-120

7. Recent Progress in the Simulation of Classical Fluids

   • Dominique Levesque, Jean Jarques Weis

   Pages 121-204

8. Monte Carlo Techniques for Quantum Fluids, Solids and Droplets

   • Kevin E. Schmidt, David M. Ceperley

   Pages 205-248

9. Quantum Lattice Problems

   • Hans De Raedt, Wolfgang von der Linden

   Pages 249-284

10. Simulations of Macromolecules

    • Artur Baumgärtner

    Pages 285-316

11. Percolation, Critical Phenomena in Dilute Magnets, Cellular Automata and Related Problems

    • Dietrich Stauffer

    Pages 317-328

12. Interfaces, Wetting Phenomena, Incommensurate Phases

    • Walter Selke

    Pages 329-354

13. Spin Glasses, Orientational Glasses and Random Field Systems

    • Allan P. Young, Joseph D. Reger, Kurt Binder

    Pages 355-383

14. Back Matter

    Pages 385-393

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The Monte Carlo method is now widely used and commonly accepted as an important and useful tool in solid state physics and related fields. It is broadly recognized that the technique of "computer simulation" is complementary to both analytical theory and experiment, and can significantly contribute to ad­ vancing the understanding of various scientific problems. Widespread applications of the Monte Carlo method to various fields of the statistical mechanics of condensed matter physics have already been reviewed in two previously published books, namely Monte Carlo Methods in Statistical Physics (Topics Curro Phys. , Vol. 7, 1st edn. 1979, 2ndedn. 1986) and Applications of the Monte Carlo Method in Statistical Physics (Topics Curro Phys. , Vol. 36, 1st edn. 1984, 2nd edn. 1987). Meanwhile the field has continued its rapid growth and expansion, and applications to new fields have appeared that were not treated at all in the above two books (e. g. studies of irreversible growth phenomena, cellular automata, interfaces, and quantum problems on lattices). Also, new methodic aspects have emerged, such as aspects of efficient use of vector com­ puters or parallel computers, more efficient analysis of simulated systems con­ figurations, and methods to reduce critical slowing down at i>hase transitions. Taken together with the extensive activity in certain traditional areas of research (simulation of classical and quantum fluids, of macromolecular materials, of spin glasses and quadrupolar glasses, etc.

• Monte Carlo method
• computer simulation
• condensed matter
• condensed matter physics
• statistical physics

• Institut für Physik, Johannes-Gutenberg-Universität Mainz, Mainz, Fed. Rep. of Germany

  Kurt Binder

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