The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Fast Monte Carlo algorithm for site or bond percolation
Open accessAbstract
We describe in detail an efficient algorithm for studying site or bond percolation on any lattice. The algorithm can measure an observable quantity in a percolation system for all values of the site or bond occupation probability from zero to one in an amount of time that scales linearly with the size of the system. We demonstrate our algorithm by using it to investigate a number of issues in percolation theory, including the position of the percolation transition for site percolation on the square lattice, the stretched exponential behavior of spanning probabilities away from the critical point, and the size of the giant component for site percolation on random graphs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Cited by
The Anatomy of the Facebook Social Graph
Ugander, J., Karrer, B., Backstrom, L., & Marlow, C. (2011) · arXiv · doi:10.48550/arxiv.1111.4503 · Cited by 819
Flexible transparent conductive materials based on silver nanowire networks: a review
Langley, D., Giusti, G., Mayousse, C., Celle, C., Bellet, D., & Simonato, J.-P. (2013) · Nanotechnology · doi:10.1088/0957-4484/24/45/452001 · Cited by 709
Percolation on complex networks: Theory and application
Li, M., Liu, R.-R., Lü, L., Hu, M.-B., Xu, S., & Zhang, Y.-C. (2021) · Physics Reports · doi:10.1016/j.physrep.2020.12.003 · Cited by 365
Metadata
- Authors
- Newman, M. E. J., & Ziff, R. M.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2001-06-27
- Volume
- 64
- Issue
- 1
- Pages
- 016706-016706
- ISSN
- 1063-651X (ISSN-L)
- 1095-3787
- OpenAlex
- W2022819543
- Cited by
- 536
- References
- 1
- FWCI
- 4.50
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fast Monte Carlo algorithm for site or bond percolation. https://app.cochat.ai/papers/10.1103/physreve.64.016706
- The paper
- Newman, M. E. J., & Ziff, R. M. (2001). Fast Monte Carlo algorithm for site or bond percolation. Physical Review E. https://doi.org/10.1103/physreve.64.016706
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.
