The DOI matches its Crossref record.
Over-relaxation method for the Monte Carlo evaluation of the partition function for multiquadratic actions
Abstract
I formulate a successive over-relaxation (SOR) procedure for the Monte Carlo evaluation of the Euclidean partition function for multiquadratic actions (such as the Yang-Mills action with canonical gauge fixing). A convergence analysis for the quadratic-action (Abelian) case shows that as thermalization proceeds the mean nodal fields relax according to the difference equation arising from the standard SOR analysis of the associated classical Euclidean field equation. Hence, SOR should accelerate the thermalization process, just as it accelerates convergence in the numerical solution of second-order elliptic differential equations.
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
Cited by
(2003) · Cited by 1,680
Neal, R. M. (2003) · The Annals of Statistics · doi:10.1214/aos/1056562461 · Cited by 1,361
Introduction to Monte Carlo Methods
Mackay, D. J. C. (1998) · Learning in Graphical Models · doi:10.1007/978-94-011-5014-9_7 · Cited by 572
Metadata
- Authors
- Adler, S. L.
- Venue
- Physical Review D
- Publisher
- American Physical Society (APS)
- Published
- 1981-06-15
- Volume
- 23
- Issue
- 12
- Pages
- 2901-2904
- ISSN
- 0556-2821 (ISSN-L)
- OpenAlex
- W1977671418
- Cited by
- 223
- References
- 0
- FWCI
- 0.62
- Type
- journal article
- Language
- en
- Open access
- closed
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: Over-relaxation method for the Monte Carlo evaluation of the partition function for multiquadratic actions. https://app.cochat.ai/papers/10.1103/physrevd.23.2901
- The paper
- Adler, S. L. (1981). Over-relaxation method for the Monte Carlo evaluation of the partition function for multiquadratic actions. Physical Review D. https://doi.org/10.1103/physrevd.23.2901
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.