Although Monte Carlo simulation (using the Metropolis algorithm, for example) appears very straightforward, there are in fact many problems and subtleties that can trap the unwary and produce unreliable results.

The following are some examples of common problems that arise in Monte Carlo simulations, along with examples of techniques to attempt to overcome them.

Paul Coddington, Northeast Parallel Architectures Center at Syracuse University, paulc@npac.syr.edu