Levich Institute Seminar Announcement, 11/29/2011
Steinman Hall, Room #312
(Chemical Engineering Conference Room)
Professor Matthieu Wyart
New York University
Department of Physics
"Shear Flow Near the Jamming Threshold"
The viscosity of a suspension of immersed hard particles was computed early on by Einstein at low packing fraction. What happens at large packing fraction ? As the latter increases toward the random close packing, the viscosity diverges and the dynamics becomes more and more correlated. Similar observations are made in dry granular flows and in simple numerical models of suspensions where hydrodynamic interactions are neglected. These observations support that dense flows are governed by a dynamical critical point. At the heart of this problem lies a geometrical question: how can particles move while still avoiding each other at high density? We investigate these matters by means of numerical simulations and scaling arguments.
BRIEF ACADEMIC/EMPLOYMENT HISTORY
I studied physics and mathematics at the Ecole Polytechnique in France, and did a master in theoretical physics at the Ecole Normale de Paris. I did my PhD at the CEA saclay during which I visited the University of Chicago. After a post-doc at Harvard I spent a year at Janelia farm. I am currently at NYU where I started in September, 2010.
RECENT RESEARCH INTERESTS:
One focus of my research group at NYU is the physics of disorder. Currently, we are particularly interested in systems that self-organize in amorphous configurations, such as a pile of sand or molecular glasses. Basic properties of these solids are mysterious, ranging from force propagation to their ability to flow or jam as minute changes are imposed on them. Recently, we have contributed in understanding how several properties of these solids are controlled by a critical point corresponding to the geometrical problem of randomly packing spheres. This leads to a new handle to study hard problems like the glass transition, that are being explored.
Another focus is the quantitative characterization and modeling of behaviors. On the one hand, we are interested in understanding how neurons control behavior at a cellular level. We explore this question in one of the simplest nervous systems, C.elegans, which comprises of 302 neurons, in collaboration with Aravi Samuel's lab at Harvard and Mitya Chklovskii at Janelia farm. Another approach is to understand behavior at a strategic level, which we explore both in C.elegans and in financial markets.