Nicholas Metropolis
| Nicholas Metropolis | |
|---|---|
 |
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| Born | Nicholas Constantine Metropolis June 11, 1915 Chicago, Illinois, United States |
| Died | October 17, 1999 (aged 84) Los Alamos, New Mexico, United States |
| Citizenship | American |
| Fields | Physicist, Mathematician |
| Institutions | Los Alamos National Laboratory |
| Alma mater | University of Chicago |
| Known for | |
| Notable awards | Computer Pioneer Award (1984) |
Nicholas Constantine Metropolis (Greek: Νικόλαος Μητρόπουλος, June 11, 1915 – October 17, 1999) was a Greek-American physicist.
Metropolis received his BSc (1937) and PhD (1941) degrees in physics at the University of Chicago. Shortly afterwards, Robert Oppenheimer recruited him from Chicago, where he was at the time collaborating with Enrico Fermi and Edward Teller on the first nuclear reactors, to the Los Alamos National Laboratory. He arrived in Los Alamos in April 1943, as a member of the original staff of fifty scientists.
After World War II, he returned to the faculty of the University of Chicago as an assistant professor. He came back to Los Alamos in 1948 to lead the group in the Theoretical Division that designed and built the MANIAC I computer in 1952 that was modeled on the IAS machine, and the MANIAC II in 1957. (He chose the name MANIAC in the hope of stopping the rash of such acronyms for machine names, but may have, instead, only further stimulated such use.) (John von Neumann may have encouraged him to use this acronym.) From 1957 to 1965 he was Professor of Physics at the University of Chicago and was the founding Director of its Institute for Computer Research. In 1965 he returned to Los Alamos where he was made a Laboratory Senior Fellow in 1980.
At Los Alamos, in the 1950s, a group of researchers led by Metropolis, including John von Neumann and Stanislaw Ulam, developed the Monte Carlo method. Generally speaking, the Monte Carlo method is a statistical approach to solve deterministic many-body problems. In 1953 Metropolis co-authored the first paper on a technique that was central to the method now known as simulated annealing. This landmark paper showed the first numerical simulations of a liquid. The algorithm for generating samples from the Boltzmann distribution was later generalized by W.K. Hastings to become the Metropolis-Hastings algorithm. He is credited as part of the team that came up with the name Monte Carlo method in reference to a colleague's relative's love for the casinos of Monte Carlo. 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, , where is the energy, is the temperature, and is the Boltzmann constant. The key contribution of the Metropolis paper was the idea that
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