  In my lectures at the Les Houches Summer School 2008, I discussed central
concepts of computational statistical physics, which I felt would be accessible
to the very cross-cultural audience at the school.
  I started with a discussion of sampling, which lies at the heart of the Monte
Carlo approach. I specially emphasized the concept of perfect sampling, which
offers a synthesis of the traditional direct and Markov-chain sampling
approaches. The second lecture concerned classical hard-sphere systems, which
illuminate the foundations of statistical mechanics, but also illustrate the
curious difficulties that beset even the most recent simulations. I then moved
on, in the third lecture, to quantum Monte Carlo methods, that underly much of
the modern work in bosonic systems. Quantum Monte Carlo is an intricate
subject. Yet one can discuss it in simplified settings (the single-particle
free propagator, ideal bosons) and write direct-sampling algorithms for the two
cases in two or three dozen lines of code only. These idealized algorithms
illustrate many of the crucial ideas in the field. The fourth lecture attempted
to illustrate aspects of the unity of physics as realized in the Ising model
simulations of recent years.
  More details on what I discussed in Les Houches, and wrote up (and somewhat
rearranged) here, can be found in my book, "Statistical Mechanics: Algorithms
and Computations", as well as in recent papers. Computer programs are available
for download and perusal at the book's web site www.smac.lps.ens.fr.
