A Guide to Monte Carlo Simulations in Statistical PhysicsCambridge University Press, 13.11.2014 Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This fourth edition contains extensive new material describing numerous powerful algorithms not covered in previous editions, in some cases representing new developments that have only recently appeared. Older methodologies whose impact was previously unclear or unappreciated are also introduced, in addition to many small revisions that bring the text and cited literature up to date. This edition also introduces the use of petascale computing facilities in the Monte Carlo arena. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory. |
Inhalt
11 | |
comments | 41 |
Simple sampling Monte Carlo methods | 51 |
Importance sampling Monte Carlo methods | 74 |
More on importance sampling Monte Carlo methods | 144 |
Offlattice models | 212 |
1 | 268 |
2 | 277 |
Quantum Monte Carlo methods | 319 |
3 | 332 |
34456 | 396 |
a brief introduction | 408 |
6 | 409 |
Monte Carlo studies of biological molecules | 465 |
Outlook | 477 |
511 | |
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A Guide to Monte Carlo Simulations in Statistical Physics David Landau,Kurt Binder Eingeschränkte Leseprobe - 2021 |
Häufige Begriffe und Wortgruppen
algorithm antiferromagnet applied approach average Binder bond calculated canonical ensemble chain Chapter Chem chemical potential cluster coexistence configuration consider correlation length critical exponents critical point degrees of freedom density described determine discussed distribution dynamics equation equilibrium error estimate example ferromagnet field finite size effects finite size scaling flipping fluctuations fluid free energy groundstate Hamiltonian Heisenberg histogram integration interactions interface internal energy Ising model Ising square lattice kinetic Landau Lett magnetization Metropolis monomers Monte Carlo methods Monte Carlo simulation nearest neighbor obtained off-lattice order parameter order transition particles partition function percolation periodic boundary conditions phase transition Phys physical polymer Potts model probability problem properties quantum random number random walk randomly relaxation renormalization sampling Section shown in Fig simple space specific heat spin glass spin-flip square lattice surface techniques thermodynamic tricritical point two-dimensional variables