Equation of State Calculations by Fast Computing Machines is an article published by Nicholas Metropolis, Arianna W. Rosenbluth, Marshall N. Rosenbluth, Augusta H. Teller, and Edward Teller in the Journal of Chemical Physics in 1953. This paper proposed what became known as the Metropolis Monte Carlo algorithm, which forms the basis for Monte Carlo statistical mechanics simulations of atomic and molecular systems. The attribution of the method to Metropolis is unfortunate, as "Metropolis played no role in its development other than providing computer time". In fact, the theoretical work was done by Marshall N. Rosenbluth, who later gained renown as one of the greatest plasma physicists of the 20th century.
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. In statistical mechanics applications prior to the introduction of the Metropolis algorithm, the method consisted of generating a large number of random configurations of the system, computing the properties of interest (such as energy or density) for each configuration, and then producing a weighted average where the weight of each configuration is its Boltzmann factor, exp(−E/kT), where E is the energy, T is the temperature, and k is Boltzmann's constant. The key contribution of the Metropolis paper was the idea that
This change makes the sampling focus on the low-energy configurations, which contribute the most to the Boltzmann average, resulting in improved convergence. To choose configurations with a probability exp(−E/kT) that can be weighed evenly, the authors devised the following algorithm: 1) each configuration is generated by a random move on the previous configuration and the new energy is computed; 2) if the new energy is lower, the move is always accepted; otherwise the move is accepted with a probability of exp(−ΔE/kT). When a move is rejected, the last accepted configuration is counted again for the statistical averages and is used as a base for the next attempted move.