- AutorIn
- Martin Weigel
- Lev Yu. Barash
- Michal Borovský
- Wolfhard Janke
- Lev N. Shchur
- Titel
- Population annealing
- Untertitel
- Massively parallel simulations in statistical physics
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa2-849236
- Quellenangabe
- Journal of Physics : Conference Series
Erscheinungsjahr: 2017
Jahrgang: 921
ISSN: 1742-6596
Artikelnummer: 012017 - Erstveröffentlichung
- 2017
- Abstract (EN)
- The canonical technique for Monte Carlo simulations in statistical physics is importance sampling via a suitably constructed Markov chain. While such approaches are quite successful, they are not particularly well suited for parallelization as the chain dynamics is sequential, and if replicated chains are used to increase statistics each of them relaxes into equilibrium with an intrinsic time constant that cannot be reduced by parallel work. Population annealing is a sequential Monte Carlo method that simulates an ensemble of system replica under a cooling protocol. The population element makes it naturally well suited for massively parallel simulations, and bias can be systematically reduced by increasing the population size. We present an implementation of population annealing on graphics processing units and discuss its behavior for different systems undergoing continuous and first-order phase transitions.
- Andere Ausgabe
- Link zur Erstveröffentlichung
Link: https://dx.doi.org/10.1088/1742-6596/921/1/012017 - Freie Schlagwörter (EN)
- Statistical Physics; Parallel Simulations; Population annealing
- Klassifikation (DDC)
- 530
- Verlag
- IOP Publishing, Bristol
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa2-849236
- Veröffentlichungsdatum Qucosa
- 25.04.2023
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
- CC BY 4.0