14:00
14:00
Uniqueness of Lagrangian trajectories for weak solutions of the two- and three-dimensional Navier-Stokes equations
Abstract
I will discuss recent results concerning the uniqueness of Lagrangian particle trajectories associated to weak solutions of the Navier-Stokes equations. In two dimensions, for which the weak solutions are unique, I will present a mcuh simpler argument than that of Chemin & Lerner that guarantees the uniqueness of these trajectories (this is joint work with Masoumeh Dashti, Warwick). In three dimensions, given a particular weak solution, Foias, Guillopé, & Temam showed that one can construct at leaset one trajectory mapping that respects the volume-preserving nature of the underlying flow. I will show that under the additional assumption that $u\in L^{6/5}(0,T;L^\infty)$ this trajectory mapping is in fact unique (joint work with Witek Sadowski, Warsaw).
17:00
Singular solutions for homogeneous quantum Boltzmann equations
14:30
Killed Branching Random Walks
Abstract
The problem is related to searching in trees. Suppose we are given a complete binary tree (a rooted tree in which the root has degree 2 and every other vertex has degree 3) with independent, identically distributed random edge weights (say copies of some random variable X, which need not be non-negative). The depth d(v) of a vertex v is the number of edges on the path from v to the root. We give each vertex v the label S_v which is the sum of the edge weights on the path from v to the root. For positive integers n, we let M_n be the maximum label of any vertex at depth n, and let M^* = max {M_n: n =0,1,...}. It is of course possible that M^* is infinity.
Under suitable moment assumptions on X, it is known that there is a constant A such that M_n/n --> A almost surely and in expectation. We call the cases A>0, A=0, and A< 0 supercritical, critical, and subcritical, respectively. When A <= 0 it makes sense to try to find the vertex of maximum weight M* in the whole tree. One possible strategy is to only explore the subtree T_0 containing the root consisting only of vertices of non-negative weight. With probability bounded away from zero this strategy finds the vertex of maximum weight. We derive precise information about the expected running time for this strategy. Equivalently, we derive precise information about the random variable |T_0|. In the process, we also derive rather precise information about M*. This answers a question of David Aldous.
Generating Tree Amplitudes in N=4 SYM and N=8 SG
Abstract
Representation theory and randomization: why the permutation character of a generalized wreath product is important
14:00
14:30
Unsolved problems related to chromatic polynomials
Abstract
For any simple graph G and any positive integer lambda, let
P(G,lambda) denote the number of mappings f from V(G) to
{1,2,..,lambda} such that f(u) not= f(v) for every two adjacent
vertices u and v in G. It can be shown that
P(G,lambda) = \sum_{A \subseteq E} (-1)^{|A|} lambda^{c(A)}
where E is the edge set of G and c(A) is the number of components
of the spanning subgraph of G with edge set A. Hence P(G,lambda)
is really a polynomial of lambda. Many results on the chromatic
polynomial of a graph have been discovered since it was introduced
by Birkhoff in 1912. However, there are still many unsolved
problems and this talk will introduce the progress of some
problems and also some new problems proposed recently.