We describe a new algorithm that approaches Monte Carlo simulation in statistical physics in a different way. Instead of sampling the probability distribution at a fixed temperature, a random walk is performed in energy space to directly extract an estimate for the density of states. The canonical probability can then be found at any temperature by weighting by the appropriate Boltzmann factor, and thermodynamic properties can be determined from suitable derivatives of the partition function.
