Wednesday, December 1, 2004
| Topic |
Self-assembling DNA Model and related problems |
| Speaker |
Ana Staninska |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
I will describe a theoretical model of self-assembly inspired by DNA
nano-technology and DNA computing, and introduce related mathematical problems.
This model consists of tiles that assemble into graph-like complexes, which
assembled "properly" can represent a solution to a given problem. It can
be shown that the computational power is equivalent to solving NP complete
problems.
Wednesday, November 24, 2004
| Topic |
Stopping Times and the Evolution of Random Structures |
| Speaker |
Greg McColm |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
One increasingly popular area of applied probability to combinatorics is the
evolution of random structures, especially of random graphs. Such
“evolutions” can be used to study the behavior of assembly, accretion,
and development. One of the fundamental questions is *when* an important threshhold
is crossed. This is a stopping time problem. We look at some of the basic notions
in this field.
Wednesday, November 17, 2004
| Topic |
Products of Random Circulant Matrices, II |
| Speaker |
Ed Cureg |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Wednesday, November 10, 2004
| Topic |
Products of Random Circulant Matrices |
| Speaker |
Ed Cureg |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
An n by n matrix of the form
a(0) a(1) a(2) .... a(n-1)
a(n-1)a(0) a(1) .... a(n-2)
... ... ...
... ... ...
a(1) a(2) a(3) ... a(0)
is called a circulant matrix. Such matrices have been studied in the context of
random walks, BCH codes, smoothing of data, analysis of random number generators,
etc. (See Diaconis, Proc. of Symposium of Appl. Math. 40, AMS, 37-58, 1989).
In this talk we discuss some basic properties of such matrices and consider the
problem of convergence in distribution of products of i.i.d. circulants.
Orthogonal matrices play a key role in our solution.
Wednesday, October 27, 2004
| Topic |
Weak and weak*-convergence II |
| Speaker |
Professor Arunava Mukherjea |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
To continue last week's discussion, I'll prove my old result that in a
non-compact group, the random walk escapes to infinity.
In other words, if G is a locally compact Hausdorff non-compact
group containing the support S(P) of a probability measure
P such that no compact subgroup of G contains
S(P), then for any compact subset K of
G, Pr(Z(n) in K) tends to zero as
n tends to infinity, where Z(n) is the random
walk induced by P.
Wednesday, October 20, 2004
| Topic |
Weak and weak*-convergence |
| Speaker |
Professor Arunava Mukherjea |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
This will be mostly an introductory talk. New results in this context will
be presented by others later in the semester.
Wednesday, October 13, 2004
| Topic |
Planar Graphs, Random Walks and Heat Content |
| Speaker |
Dr. Patrick McDonald
New College at Sarasota |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
There is a well-known and well-studied relationship between Brownian motion,
boundary value problems and the geometry of Euclidean domains. This relationship
gives rise to discrete analogs relating random walks, problems for discrete
difference operators and the geometry of graphs embedded in Euclidean spaces. In
this talk we survey the discrete material, developing techniques for moving
between categories and using these techniques to discuss recent results. In
particular, we will construct a pair of isospectral graphs and prove that these
graphs are distinguished by their heat content.
The talk is aimed at a general mathematical audience and is reasonably
self-contained. In particular, we develop those probabilistic and geometric tools
which we will require.
Wednesday, October 6, 2004
| Topic |
Local Limit Theorems for Random Integer Partitions |
| Speaker |
Professor Ljuben Mutafchiev |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
Certain power series expansions will be used to prove a local limit theorem for
the length of the side of a Durfee square in a random partition of a positive
integer n as n tends to infinity.
Wednesday, September 29, 2004
| Topic |
Hypergroups: Examples, Idempotent and Invariant Probability
Measures II |
| Speaker |
Norbert Youmbi |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Wednesday, September 22, 2004
| Topic |
Hypergroups: Examples, Idempotent and Invariant Probability Measures |
| Speaker |
Norbert Youmbi |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
A semihypergroup (Hypergroup) is a locally compact space on which the vector
space of finite regular Borel measures has a convolution structure preserving the
probability measures. The class of semihypergroups (Hypergroups) includes the
class of locally compact topological semigroups (Groups). Hypergroups generalizes
in many aspects locally compsc groups. Many n-dimensional hypergroups
are obtained from orthogonal polynomials on spaces on which no structure of a
group could be defined. We will give some practical examples of hypergroups as
well as presenting some results on invariants and idempotent probability measures
on semihypergroups.
Wednesday, September 15, 2004
| Topic |
Random Fibonacci Sequences |
| Speaker |
Edgardo Cureg |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
Viswanath's determination of the rate of growth of
(|xn|), where xn+1
= \pm xn + x_{n-1}, n \ge 1$, $x_0 = x_1 = 1$, and the $+$ and $-$ signs
each occur with probability $1/2$.
The techniques involved in the solution illustrate an interplay between the
theory of random matrix products, the Stern-Brocot tree, fractal measures, and
computer simulations. We also present some generalizations of the random Fibonacci
sequence.
Wednesday, September 8, 2004
| Topic |
When convergence in distribution of products of d
by d i.i.d. matrices is determined essentially by their skeletons |
| Speaker |
Professor Arunava Mukherjea |
| Time |
4:00-5:00 p.m. |
| Place |
PHY 118 |
Abstract
Two nonnegative matrices A and B have the same skeleton
if A(i,j) > 0 whenever
B(i,j) > 0 and conversely.