Irreversible Monte Carlo methods for particle simulations | Vidéo | Carmin.tv

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Irreversible Monte Carlo methods for particle simulations

De Anthony Maggs

Apparaît dans la collection : On Future Synergies for Stochastic and Learning Algorithms / Sur les synergies futures autour des algorithmes d'apprentissage et stochastiques

The two workhorses of molecular simulation are molecular dynamics and Markov-chain Monte Carlo. In this talk we compare them with an alternative: 'Event chain Monte Carlo' in which detailed balance is replaced by the weaker balance condition. We characterise the large scale dynamics of each method pointing out where event chains can give rise to more efficient or more accurate calculations. By optimising the splitting of interactions in event chain methods we show (in hard sphere systems) that we are able to further accelerate the sampling of density modes.

Informations sur la vidéo

Date de captation 28/09/2021
Date de publication 18/11/2021
Institut CIRM
Licence CC BY NC ND
Langue Anglais
Audience Chercheurs
Réalisateur(s) Guillaume Hennenfent
Format MP4

Données de citation

DOI 10.24350/CIRM.V.19817703
Citer cette vidéo Maggs, Anthony (28/09/2021). Irreversible Monte Carlo methods for particle simulations. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19817703
URL https://dx.doi.org/10.24350/CIRM.V.19817703

Domaine(s)

Mécanique statistique

Bibliographie

LEI, Ze, KRAUTH, Werner, et MAGGS, A. C. Event-chain Monte Carlo with factor fields. Physical Review E, 2019, vol. 99, no 4, p. 043301. - https://doi.org/10.1103/PhysRevE.99.043301
FAULKNER, Michael F., QIN, Liang, MAGGS, A. C., et al. All-atom computations with irreversible Markov chains. The Journal of chemical physics, 2018, vol. 149, no 6, p. 064113. - https://doi.org/10.1063/1.5036638
LI, Botao, TODO, Synge, MAGGS, Anthony C., et al. Multithreaded event-chain Monte Carlo with local times. Computer Physics Communications, 2021, vol. 261, p. 107702. - https://doi.org/10.1016/j.cpc.2020.107702

Document(s)

https://www.cirm-math.fr/RepOrga/2389/Slides/Maggs.pdf

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