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Monte Carlo methods, 70 years after Metropolis et al. (1953)

The Monte Carlo method, which involves generating random numbers to solve physical problems, was originally proposed by John Von Neumann and Stanislaw Ulam. In 1953, Metropolis and colleagues published "Equation of State Calculations by Fast Computing Machines” [J. Chem. Phys. 21, 1087–1092, 1953] reporting the use of the Monte Carlo method in the first simulations of a condensed matter system.

Since 1953, a wide variety of algorithms based on the Monte Carlo method have been developed and applied to study classical systems ranging from liquids to proteins. Monte Carlo methods have been developed to provide enhanced sampling and explore rare events in classical systems, extended to model dynamical processes, and employed to solve quantum problems related to electronic structures and nuclear quantum effects.

Today, the Monte Carlo method is widely used for classical, quantum, and dynamical simulations. This special issue celebrates the 70th anniversary of the seminal publication of Metropolis et al. in The Journal of Chemical Physics by demonstrating the vitality of the Monte Carlo method in contemporary research.

Guest Editors: Edward Maginn, Ilja Siepmann, Julian Tirado Rives, Daan Frenkel, Claudia Filippi, Kristen Fichthorn, Yuko Okamoto, Werner Krauth, with JCP Editors Carlos Vega, John Straub, and Francesco Sciortino.

Miroslav Suruzhon; Khaled Abdel-Maksoud; Michael S. Bodnarchuk; Antonella Ciancetta; Ian D. Wall; Jonathan W. Essex
Luca Tonti; Fabián A. García Daza; José Manuel Romero-Enrique; Alessandro Patti
Archana Verma; Nicholas E. Jackson
Philipp Ströker; Karsten Meier
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