The program is: Monte Carlo computation of Integrals, Importance sampling, Markov Chains and Detailed Balance, The Metropolis Algorithm, Critical slowing down, Cluster algorithms, Monte Carlo in continuous time, Kawasaki algorithm: local and non-local, Coupled chemical reactions: the Gillespie algorithm.

One of the first papers on Monte Carlo methods N. Metropolis and S. Ulam,

M.E.J. Newman and G.T. Barkema, "Monte Carlo Methods in Statistical Physics" (Oxford University Press). (This is an excellent and very detailed book about Monte Carlo simulations in classical Statistical Physics, where the emphasis is on lattice models).

D. Frenkel and B. Smit, "Understanding molecular simulations", Academic Press (2002). (A very detailed and good book, containing also some material on Molecular Dynamics simulations).

B.A. Berg,

An online course on Monte Carlo simulation is provided by P. Coddington,

D. T. Gillespie,

Estimating pi with the hit-and-miss method

Applet for Ising model simulations (I) - This applet gives the possibility of choosing between different algorithms (Single spin flip, Wolff, Kawasaki....)

Applet for Ising model simulations (II) - This applet is very fast, but only restricted to single spin flip. It shows also magnetization and energy plots produced while the simulation runs

Uniform Random Numbers with a gap

Estimating the area of a circle of radius 1 using the hit-and-miss method

A simple example of Markov process via matrix products and direct Monte Carlo simulation

How to select efficiently from q states according to a given probability distribution (q large)

(to run these codes in Octave copy them on a file, say file.m, and they type

(Stefanos Nomidis & Danai Laskaratou)

The Wolff algorithm is a cluster algorithm for the Ising model which does not suffer from the critical slowing down as the single spin flip Metropolis algorithm. In this assignment the student uses the Wolff algorithm to compute the autocorrelation time τ for the two dimensional Ising model at the critical point T=Tc. Show that tau diverges as a power law as a function of the lattice size L: τ ~ L^z and determine the value of the dynamical exponent z. Use finite size scaling ansatz to analyze the behavior of the magnetic susceptibility in the vicinity of the critical point and determine the exponents γ and ν. To solve this assignment check the book by Newman and Barkema where details are discussed.

(Jeroen Sweeck & x - Bram Verbeek & Arnaud De Coster)

The Kawasaki dynamics consists in swapping the positions of two opposite spins of an Ising model using Metropolis acceptance rule. In this way the total magnetization of the system remains conserved. There are different ways to implement the Kawasaki algorithm. One can use for instance a local or a non-local algorithm. In this assignment the student implements both algorithms as discussed in Problems 4.10 and 4.11 of the lecture notes. Facultative: The student may also try to implement a continuous time algorithm, as discussed in the book by Newman and Barkema.

(Ruben Ceulemans & x)

The Metropolis algorithm is very popular and simple to implement. However there are situations in which it does not work very well and there are more suitable Monte Carlo algorithms. This is the case of the Potts model, which is a generalization of the Ising model to more states per site. In this assignment the student compares the performances of the Metropolis and Heat Bath algorithms for the q-state Potts model (Problem 4.9 of the lecture notes).

(Frederik de Ceuster & Tim Loossens - Philip Ruijten & Joris Labie)

In the assignment about hard spheres the student learns to use the Monte Carlo algorithm for a continuum system (Problem 4.12 of the lecture notes). The scope of the problem is the calculation of the pair correlation function g(r). Faculatitve: from this quantity one can compute the pressure of the system using the virial theorem and compare the results with those of the virial expansion. Another possibility is to try some cluster algorithms which are quite easy to implement.

(Cedric Driesen & Stefanie Put)

The Gillespie algorithm is a Monte Carlo algorithm to simulate systems of coupled chemical reactions. The system is assumed to be well-mixed so that no spatial effects are taken into account. In this assignment the students solve the last three problems of the lecture notes (Birth-annihilation process, Lotka-Volterra Model, Brusselator).

(Marie Mulier & Randy Laevens)