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(1) Presentation(s)

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Mar. 13/12/2022 14:00 Salle des Séminaires, Bâtiment 21, Etage 4

Séminaire
KLAMSER Juliane (L2C)
Can Monte Carlo methods be used to simulate active-matter systems?

(Physique Statistique)


Sommaire:

"All known life forms are based on self-propelled entities uniting to create large-scale structures and movements. If this didn't happen, organisms would be limited to using much slower, passive processes such as diffusion to move DNA and proteins around inside cells or tissues, and many of life's complex structures and functions might never have evolved."[G. Popkin, Nature 2016] A central question in the field of active matter concerns the emergent collective phenomena when individual particles move persistently, i.e. when particles overcome a characteristic finite distance without changing their direction of motion. Although considerable effort has been put to develop analytical approaches to describe the statistical physics of active matter, the state of the art is far from comparable to equilibrium statistical physics. Our advances therefore mainly rely on numerical studies where many active-matter models have been proposed and simulated. However, few attempts have been made to develop an algorithmic toolbox for those models. In equilibrium, the detailed-balance condition allows exploiting the unphysical moves of Monte Carlo (MC) approaches to efficiently simulate large systems. As there is no analog of detailed balance for active matter, the construction of MC algorithms that faithfully capture continuous-time active-matter models is not straightforward. I will present a realization of kinetic MC analogs of the work-horse models of self-propelled particles, namely Active-Ornstein Uhlenbeck, Active Brownian, and Run-and-Tumbles particles.


Pour plus d'informations, merci de contacter Berthier L.