At Los Alamos in the late 1940s and early 1950s a group of researchers led by Metropolis, including
John von Neumann and
Stanislaw Ulam, developed the
Monte Carlo method. This is a class of computational approaches that rely on repeated random sampling to compute their results, named in reference to Ulam's relatives' love for the casinos of Monte Carlo. Metropolis was deeply involved in the very first use of the Monte Carlo method, rewiring the
ENIAC computer to perform simulations of a nuclear core in 1948. This landmark paper showed the first numerical simulations of a
liquid and introduced a new Monte Carlo computational method for doing so. In applications of the Monte Carlo method to problems in statistical mechanics prior to the introduction of the Metropolis algorithm, a large number of random configurations of the system would be generated, the properties of interest (such as energy or density) would be computed for each configuration, and then a
weighted average computed where the weight of each configuration was its
Boltzmann factor, e^{-E/kT}, where E is the
energy, T is the
temperature, and k is the
Boltzmann constant. The key contribution of the paper was the idea that The algorithm for generating samples from the
Boltzmann distribution was later generalized by
W.K. Hastings and has become widely known as the
Metropolis–Hastings algorithm. In recent years a controversy has arisen as to whether Metropolis actually made significant contributions to the
Equation of State Calculations paper. ==Associations and honors==