The Metropolis Algorithm

Author

Beichl, Isabel ; Sullivan, Francis

Author_Institution

Nat. Inst. of Stand. & Technol., Gaithersburg, MD, USA

Volume

2

Issue

1

fYear

2000

Firstpage

65

Lastpage

69

Abstract

The Metropolis Algorithm has been the most successful and influential of all the members of the computational species that used to be called the "Monte Carlo method". Today, topics related to this algorithm constitute an entire field of computational science supported by a deep theory and having applications ranging from physical simulations to the foundations of computational complexity. Since the rejection method invention (J. von Neumann), it has been developed extensively and applied in a wide variety of settings. The Metropolis Algorithm can be formulated as an instance of the rejection method used for generating steps in a Markov chain.

Keywords

Markov processes; Monte Carlo methods; probability; Markov chain; Metropolis Algorithm; Monte Carlo method; computational complexity; computational science; computational species; deep theory; physical simulations; rejection method; Computational complexity; Computational modeling; Distributed computing; Distribution functions; Hospitals; Monte Carlo methods; Physics computing; Probability distribution; Sampling methods;

fLanguage

English

Journal_Title

Computing in Science & Engineering

Publisher

ieee

ISSN

1521-9615

Type

jour

DOI

10.1109/5992.814660

Filename

814660