Laboratoire J. A. Dieudonné

Séminaire de l'équipe Systèmes dynamiques, interactions en physique, biologie et chimie


Contact: Bruno Marcos


11 heures

Salle de séminaires physique (Fizeau)
Eric Bertin (ENS Lyon)

On the statistical physics of macroscopic interacting entities

Numerous systems of interest can be considered as composed of a large number of macroscopic interacting "entities", these entities being either real objects or more abstract mathematical modes. Examples range from physical systems like granular matter, foams, or turbulent flows, to complex systems outside physics like bird flocks or social systems. The dynamics of the involved macroscopic entities differs from that of standard microscopic particles, due for instance to energy dissipation in collisions between grains, or to selfishness in the decision process of social agents, thus questioning the possibility to apply standard statistical physics approaches to such systems. This issue is illustrated on several simple solvable models.


11 heures

Salle de conférences


11 heures

Salle de conférences
Valentin Bonzom (Perimeter Institute Waterloo)

 Random tensor models

The study of random tensors generalizes random matrices to objects with d>2 indices. Remarkably, Feynman expansions in tensor models generate sums over triangulations of pseudo-manifolds in dimension d. Such models have been actively developed and solved in the past two years. I will introduce a suitable ensemble of random tensors and present the main results I have obtained: universality at large N (large size of the tensor), a notion of continuum limit and existence of critical behaviors, and a new algebra which generalizes the Virasoro algebra found in matrix models and provides gluing rules for triangulations in dimension d.

11 heures

Salle de conférences


11 heures

Salle de conférences
Julien Tailleur

Statistical physics of run-and-tumble bacteria and other self-propelled particles

Suspensions of self-propelled particles have attracted lots of interest from the physics community over the last decade. Bacteria and algae are prototypical self-propelled particles but self-propulsion can also be met outside biology, for instance due to self-diffusiophoresis. In this talk, I will briefly review several types of self-propelled particles and describe how one can build a statistical physics treatment of their collective behavior. I will describe various interesting features of these suspensions, such as ratchet effects, effective temperature and pattern formation.

11 heures

Salle de conférences


Pas de séminaire




Francois Sicard (Université de Bourgogne)

Reconstructing the free-energy landscape of protein with biased MD simulations: Metadynamics and dihedral Principal Component Analysis

Since the late 1980s emerges the idea that a global overview of the protein's energy surface is of paramount importance for a quantitative understanding of the relationships between structure, dynamics, stability, and functional behavior of proteins. Thanks to continuous increase of the computing power and of the reliability of empirical force fields, all-atom molecular dynamics (MD) simulations become a widely employed computational technique to simulate the dynamics of complex systems such as proteins through discrete integration of the Newtons's equations of motions of each atom. However in several cases all-atom MD simulations are still not competitive to describe the protein conformational dynamics, due to the fact that using an atomistic model is computationally expensive, as sufficiently realistic potential energy functions are intrinsically complex. Moreover, most phenomena of interest take place on times scales that are orders of magnitude larger than the accessible time that can be currently simulated with classical all-atom MD. This issue can be addressed by accelerating the exploration of the conformational space in (all-atom) MD simulations. In this case, a large variety of methods referred to as enhanced sampling techniques have been proposed. They exploit a methodology aimed at accelerating rare events and based on constrained MD. Metadynamics (metaD) belongs to this class of methods: it enhances the sampling of the conformational space of a system along a few selected degrees of freedom, named collective variables (CVs) and reconstructs the probability distribution as a function of these CVs. However, the succes of metaD depends on the critical choice of a reasonable number of relevant CVs. All the relevant slow varying degrees of freedom must be catched by the CVs. In addition, the number of CVs must be small enough to avoid exceedingly long computational time, while being able to distinguish among the different conformational states of the system. Consequently, identifying a set of CVs appropriate for describing complex processes involves a right understanding of the physics and chemistry of the process under study. Choosing a correct set of CVs thus remains a challenge, as a whole, independently of the enhanced sampling technique one could consider.

I will present that coupling Well-Tempered Metadynamics, i.e. the most recent variant of the method, with a set of CVs generated from a dihedral Principal Component Analysis on the Ramachandran dihedral angles (describing the backbone structure of the protein) provides an efficient reconstruction of the free-energy landscape of the small and very diffusive Met-enkephalin pentapeptide.

Pierre Degond

Modèles macroscopiques d'auto-organisation

Les phénomènes d'auto-organisation et d’émergence apparaissent au sein de systèmes constitués d’agents autonomes interagissant localement sans leader. Ils s’observent dans tous les domaines (physique, biologique, sociaux) et à toutes les échelles au point qu’ils doivent être considérés comme la norme plutôt que l’exception. Pourtant, leur étude théorique en est encore à ses balbutiements car ils posent des questions fondamentalement nouvelles que les méthodes classiques de la théorie cinétique et de la physique statistique peinent à résoudre. Une des questions fondamentales est l’obtention (quasi)-rigoureuse de modèles macroscopiques à partir des modèles agents-centrés (ou particulaires). L’une des difficultés rencontrées est la perte des lois de conservation (comme celles de l’impulsion), qui sont la pierre angulaire des modèles continus en physique. Nous discuterons de cette difficulté et des moyens d’y remédier en prenant l’exemple de dynamiques d’alignement qui ont suscité beaucoup de travaux dans les quinze dernières années.