Mixing of the Glauber Dynamics for the Ferromagnetic Potts Model.
- Submitting institution
-
University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 96279
- Type
- D - Journal article
- DOI
-
10.1002/rsa.20569
- Title of journal
- Random Structures & Algorithms
- Article number
- -
- First page
- 21
- Volume
- 48
- Issue
- 1
- ISSN
- 10429832
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
https://doi.org/10.1002/rsa.20569
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
B - Algorithms and Complexity
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The Potts Model has received significant scrutiny in both CS and Physics. We present several new results determining whether the dynamics mixes rapidly or not in the ferromagnetic case – these were the first results of this type for the ferromagnetic case. Novel proof techniques were developed using a mix of probabilistic reasoning, extremal combinatorics, and graph theory. The work has been picked up by leaders in the field, e.g. cited in “Efficient sampling and counting algorithms for the Potts model on Z^d at all temperatures” Christian Borgs, Jennifer Chayes, Tyler Helmuth, Will Perkins, Prasad Tetali, STOC 2020: 738–751 https://doi.org/10.1145/3357713.3384271.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -