Computational Statistical Physics

Detailed account of computational statistical physics, including theoretical foundations and modern, computational applications.

Lucas Böttcher (Author), Hans J. Herrmann (Author)

9781108841429, Cambridge University Press

Hardback, published 26 August 2021

268 pages
26 x 20.8 x 2 cm, 0.75 kg

Providing a detailed and pedagogical account of the rapidly-growing field of computational statistical physics, this book covers both the theoretical foundations of equilibrium and non-equilibrium statistical physics, and also modern, computational applications such as percolation, random walks, magnetic systems, machine learning dynamics, and spreading processes on complex networks. A detailed discussion of molecular dynamics simulations is also included, a topic of great importance in biophysics and physical chemistry. The accessible and self-contained approach adopted by the authors makes this book suitable for teaching courses at graduate level, and numerous worked examples and end of chapter problems allow students to test their progress and understanding.

Preface
Part I. Stochastic Methods: 1. Random Numbers
2. Random-Geometrical Models
3. Equilibrium Systems
4. Monte-Carlo Methods
5. Phase Transitions
6. Cluster Algorithms
7. Histogram Methods
8. Renormalization Group
9. Learning and Optimizing
10. Parallelization
11. Non-Equilibrium Systems
Part II. Molecular Dynamics: 12. Basic Molecular Dynamics
13. Optimizing Molecular Dynamics
14. Dynamics of Composed Particles
15. Long-Range Potentials
16. Canonical Ensemble
17. Inelastic Collisions in Molecular Dynamics
18. Event-Driven Molecular Dynamics
19. Non-Spherical Particles
20. Contact Dynamics
21. Discrete Fluid Models
22. Ab-Initio Simulations
References
Index.

Subject Areas: Mathematical & statistical software [UFM], Statistical physics [PHS], Mathematical modelling [PBWH]