Introduction To Monte Carlo Algorithms
by Werner Krauth
Publisher: CNRS-Laboratoire de Physique Statistique 1998
Number of pages: 43
In these lectures, the author discusses the fundamental principles of thermodynamic and dynamic Monte Carlo methods in a simple light-weight fashion. The keywords are Markov chains, Sampling, Detailed Balance, A Priori Probabilities, Rejections, Ergodicity, "Faster than the clock algorithms".
Home page url
Download or read it online for free here:
by Johannes Grotendorst, Stefan Bluegel, Dominik Marx - NIC
This volume focuses on the application of electronic structure calculations and dynamical simulation techniques covering aspects of solid state physics, surface and nanoscience, chemical reactions and dynamics, magnetism and electron transport, etc.
by Morten Hjorth-Jensen - University of Oslo
These notes should train you in an algorithmic approach to problems in the sciences, represented here by the unity of three disciplines, physics, mathematics and informatics. This trinity outlines the emerging field of computational physics.
by Allen B. Downey - Green Tea Press
An introduction to physical modeling using a computational approach. Taking a computational approach makes it possible to work with more realistic models than what you typically see in a first-year physics class, such as friction and drag.
by Eric Ayars - California State University, Chico
Contents: Useful Introductory Python; Python Basics; Basic Numerical Tools; Numpy, Scipy, and MatPlotLib; Ordinary Differential Equations; Chaos; Monte Carlo Techniques; Stochastic Methods; Partial Differential Equations; Linux; Visual Python; etc.