Self-sustained clusters as drivers of computational hardness in p-spin models
- Submitting institution
-
Aston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 21491338
- Type
- D - Journal article
- DOI
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10.1103/PhysRevB.96.024415
- Title of journal
- Physical Review B
- Article number
- 024415
- First page
- -
- Volume
- 96
- Issue
- 2
- ISSN
- 1098-0121
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2017
- URL
-
-
- 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
- No
- Number of additional authors
-
2
- Research group(s)
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A - Aston Institute of Urban Technology and the Environment (ASTUTE)
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Understanding the microscopic manifestation of ergodicity-breaking and resulting metastability in disordered spin systems has been a challenge for over 40 years. We present the concept of self-sustained clusters as a driver for the emergence of slow-moving variables and computational-hardness, with potential wide-ranging implications on our ability to improve optimisation algorithms. The research, which is part of an ongoing international collaboration (Hong Kong) was funded by the Leverhulme Trust (RPG-2013-48, £155,624), published in 3 separate papers (https://doi.org/10.1103/PhysRevE.97.062154, https://doi.org/10.1103/PhysRevE.88.032132) and was presented in 6 conferences (e.g., StatPhys26, Lyon, CONES London 2016, Phase Transitions in Discrete Structures Frankfurt 2016), in two by invitation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
