The metropolis algorithm

Computing in Science and Engineering

Volumn 2, Issue 1, 2000, Pages 65-69

  Beichl, Isabel ^a   Sullivan, Francis ^b  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

^b IDA Center for Computing Sciences   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0001834226     PISSN: 15219615     EISSN: None     Source Type: Journal    
DOI: 10.1109/5992.814660     Document Type: Article

References (6)

1. I. Beichl and F. Sullivan, "(Monte-Carlo) Time after Time," IEEE Computational Science & Eng., Vol. 4, No. 3, July-Sept. 1997, pp. 91-95.
2. N. Metropolis et al., "Equation of State Calculations by Fast Computing Machines," J. Chemical Physics, Vol. 21, 1953, pp. 1087-1092.
3. M. Jerrum and A. Sinclair, "The Markov Chain Monte Carlo Method: An Approach to Counting and Integration," Approximation Algorithms for NP-Hard Problems, Dorit Hochbaum, ed., PWS (Brooks/Cole Publishing), Pacific Grove, Calif., 1996, pp. 482-520.
4. V. Gore and M. Jerrum, "The Swendson-Wang Process Does Not Always Mix Rapidly," Proc. 29th ACM Symp. Theory of Computing, ACM Press, New York, 1997, pp. 157-165.
5. J.G. Propp and D.B. Wilson, "Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics," Random Structures and Algorithms, Vol. 9, Nos. 1 & 2, 1996, pp. 223-252.
6. I. Beichl and F. Sullivan, "Approximating the Permanent via Importance Sampling with Application to the Dimer Covering Problem," J. Computational Physics, Vol. 149, No. 1, Feb. 1999, pp. 128-147.