The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Microcanonical Monte Carlo Simulation
Abstract
A new algorithm for the simulation of statistical systems is presented. The procedure produces a random walk through configurations of a constant total energy. It is computationally simple and applicable to systems of both discrete and continuous variables.
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Citations
Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Cited by
Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
Statistical decay of very hot nuclei-the production of large clusters
Gross, D. H. E. (1990) · Reports on Progress in Physics · doi:10.1088/0034-4885/53/5/003 · Cited by 555
Theoretical estimates of the critical exponents of the superfluid transition inHe4by lattice methods
Campostrini, M., Hasenbusch, M., Pelissetto, A., & Vicari, E. (2006) · Physical Review B · doi:10.1103/physrevb.74.144506 · Cited by 270
Metadata
- Authors
- Creutz, M.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 1983-05-09
- Volume
- 50
- Issue
- 19
- Pages
- 1411-1414
- ISSN
- 0031-9007 (ISSN-L)
- OpenAlex
- W2034238820
- Cited by
- 579
- References
- 1
- FWCI
- 11.79
- Type
- journal article
- Language
- en
- Open access
- closed
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Microcanonical Monte Carlo Simulation. https://app.cochat.ai/papers/10.1103/physrevlett.50.1411
- The paper
- Creutz, M. (1983). Microcanonical Monte Carlo Simulation. Physical Review Letters. https://doi.org/10.1103/physrevlett.50.1411
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
