Georgia Institute of Technology College of Sciences

Isospectral reductions decrease the dimension of the adjacency matrix while keeping all the eigenvalues. This is achieved by using rational functions in the entries of the reduced matrix. I will show how it's done through an example. I will also discuss about the eigenvectors and generalized eigenvectors before and after reductions.

The (type A) Hecke algebra H_n(q) is an n!-dimensional q-analog of the symmetric group. A related trace space of certain functions on H_n(q) has dimension equal to the number of integer partitions of n. If we could evaluate all functions belonging to some basis of the trace space on all elements of some basis of H_n(q), then by linearity we could evaluate em all traces on all elements of H_n(q). Unfortunately there is no simple published formula which accomplishes this. We will consider a basis of H_n(q) which is related to structures called wiring diagrams, and a combinatorial rule for evaluating one trace basis on all elements of this wiring diagram basis. This result, the first of its kind, is joint work with Justin Lambright and Ryan Kaliszewski.

A low-diameter decomposition (LDD) of an undirected graph G is a partitioning of G into components of bounded diameter, such that only a small fraction of original edges are between the components. This decomposition has played instrumental role in the design of low-stretch spanning tree, spanners, distributed algorithms etc. A natural question is whether such a decomposition can be efficiently maintained/updated as G undergoes insertions/deletions of edges. We make the first step towards answering this question by designing a fully-dynamic graph algorithm that maintains an LDD in sub-linear update time. It is known that any undirected graph G admits a spanning tree T with nearly logarithmic average stretch, which can be computed in nearly linear-time. This tree decomposition underlies many recent progress in static algorithms for combinatorial and scientific flows. Using our dynamic LDD algorithm, we present the first non-trivial algorithm that dynamically maintains a low-stretch spanning tree in \tilde{O}(t^2) amortized update time, while achieving (t + \sqrt{n^{1+o(1)}/t}) stretch, for every 1 \leq t \leq n. Joint work with Sebastian Krinninger.

I will discuss two topics in Dynamical Systems. A uniformly hyperbolic dynamical system preserving Borel probability measure μ is called fair dice like or FDL if there exists a finite Markov partition ξ of its phase space M such that for any integers m and j(i), 1 ≤ j(i) ≤ q one has μ ( C(ξ, j(0)) ∩ T^(-1) C(ξ, j(1)) ∩ ... ∩ T^(-m+1)C(ξ, j(m-1)) ) = q^(-m) where q is the number of elements in the partition ξ and C(ξ, j) is element number j of ξ. I discuss several results about such systems concerning finite time prediction regarding the first hitting probabilities of the members of ξ. Then I will discuss a natural modification to all billiard models which is called the Physical Billiard. For some classes of billiard, this modification completely changes their dynamics. I will discuss a particular example derived from the Ehrenfests' Wind-Tree model. The Physical Wind-Tree model displays interesting new dynamical behavior that is at least as rich as some of the most well studied examples that have come before.