21/09/2012

 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.


28/09/2012

 11 heures


Salle de conférences



05/10/2012

 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 pseudomanifolds 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.


12/10/2012

 11 heures


Salle de conférences



19/10/2012

 11 heures


Salle de conférences


Julien Tailleur

 Statistical physics of runandtumble bacteria and other selfpropelled particles

 Suspensions of selfpropelled particles have attracted lots of interest
from the physics community over the last decade. Bacteria and algae are
prototypical selfpropelled particles but selfpropulsion can also be
met outside biology, for instance due to selfdiffusiophoresis. In this
talk, I will briefly review several types of selfpropelled 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.


26/10/2012

 11 heures


Salle de conférences










Francois Sicard (Université de Bourgogne)


Reconstructing the freeenergy 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, allatom 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 allatom 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 allatom MD. This issue can be
addressed by accelerating the exploration of the conformational space
in (allatom) 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 WellTempered
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 freeenergy
landscape of the small and very diffusive Metenkephalin pentapeptide.



Pierre Degond

 Modèles macroscopiques d'autoorganisation

 Les
phénomènes d'autoorganisation 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 agentscentrés (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.

















