Week of April 2, 2023

Mon Apr 3, 2023
12:00pm - zoom - Probability and Analysis Webinar
Serhii Myroshnychenko - (Lakehead University)
TBA

https://sites.google.com/view/paw-seminar

4:00pm to 5:00pm - RH 340N - Geometry and Topology
Morgan Opie - (UCLA)
A classification of rank 3 vector bundles on complex projective 5-space
4:00pm to 5:00pm - - Applied and Computational Mathematics
Junyuan Joanne Lin - (Loyola Marymount University)
Laplacian Matrices of Graphs: Algorithms and Applications for Large-Scale Computations

Graphs provide a powerful mathematical model for a variety of networks, from social to neuronal networks. The Laplacian matrix of a graph, which captures its structural properties, is essential for solving linear systems that arise in large-scale computations across various application domains. In this talk, we will explore the characteristics of Laplacian matrices, drawing on mathematical concepts from linear algebra. We will demonstrate the mathematical equivalence between solving linear graph Laplacian systems and solving clustering problems in Machine Learning. Finally, we will present original algorithms that are robust and scalable for solving large real-life biology and social networks. Our research aims to provide a comprehensive understanding of the Laplacian matrices of graphs and their applications in solving real-world problems.

Tue Apr 4, 2023
4:00pm to 5:00pm - RH 306 - Number Theory
Anh Hoang Trong Nam - (University of Minnesota)
Configuration spaces and applications in arithmetic statistics

In the last dozen years, topological methods have been shown to produce a new pathway to study arithmetic statistics over function fields, most notably in Ellenberg-Venkatesh-Westerland's work on the Cohen-Lenstra conjecture. More recently, Ellenberg, Tran and Westerland proved the upper bound in Malle's conjecture over function fields by studying the twisted homology of configuration spaces. In this talk, we will give an overview of their framework and extend their techniques to study other questions in arithmetic statistics. As an example, we will demonstrate how this extension can be used to study the asymptotic average of the quadratic character of the resultant of polynomials over finite fields, answering a question of Ellenberg-Shusterman.

Wed Apr 5, 2023
1:00pm to 2:00pm - 440R Rowland Hall - Combinatorics and Probability
Gilyoung Cheong - (UCI)
The Smith normal form of a polynomial of a random integral matrix
Given a prime $p$, let $P(t)$ be a non-constant monic polynomial in $t$ over the ring $\mathbb{Z}_{p}$ of $p$-adic integers. Let $X_n$ be the $n \times n$ uniformly random (0,1)-matrix over $\mathbb{Z}_{p}$. We compute the asymptotic distribution of the cokernel of $P(X_n)$ as $n$ goes to infinity. When $P(t)$ is square-free modulo $p$, this lets us compute the asymptotic distribution of the Smith normal form of $P(X_n)$. In fact, we shall consider the same problem with a more general random matrix $X_n$, which also includes the example of a Haar-random matrix. Our work crucially uses a recent work of W. Sawin and M. M. Wood which shows that the moments of finite size modules over any ring determine their distribution. This is joint work with Myungjun Yu. https://arxiv.org/abs/2303.09125
Thu Apr 6, 2023
1:00pm - RH 510R - Algebra
Matthew Harper - (UC Riverside)
A Generalization of the Alexander Polynomial from Quantum sl3

The Alexander polynomial can be constructed as an R-matrix invariant associated with representations of unrolled restricted quantum sl2 at a fourth root of unity. These highest representations V(t) are parameterized by nonzero complex numbers t which determine the polynomial variable. In this talk, we discuss a generalization to a multivariable link invariant computed from higher rank quantum groups at a fourth root of unity, with an emphasis on g=sl3.

 

We will review the representation theory of the sl2 case before moving to sl3. We then sketch a proof of the following theorem: For any knot K, the two-variable sl3 polynomial is equal to the Alexander polynomial when evaluated at (t1,t2) such that the representation V(t1,t2) is reducible. We compare the sl3 invariant with other knot invariants, such as the Jones polynomial, by giving specific examples. Unlike many well known knot invariants, the sl3 invariant can detect knot mutation.