Seminars and Colloquia by Series

A polynomial time algorithm for the fractional $ f $-density

Series
Graph Theory Seminar
Time
Tuesday, February 21, 2023 - 15:45 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Guoning YuGeorgia State University

The edge-coloring problem (ECP) for a multigraph $G=(V, E)$ is to color its edges with minimum number of colors such that no two adjacent vertices receive the same color. ECP can be naturally formulated as an integer program, and its linear programming relaxation is referred to as the fractional edge-coloring problem (FECP). The optimal value of ECP (resp. FECP) is called the chromatic index (resp. fractional chromatic index) of $G$, denoted by $\chi^{\prime}(G)$ (resp. $\chi^*(G)$). Let $\Delta(G)$ be the maximum degree of $G$ and let $ \mathcal{W}^*(G) $ be the fractional density of $G$, defined by $$ \mathcal{W}^*(G) = \max _{U \subseteq V,|U| \geq 2}\frac{|E(U)|}{\lfloor|U|/2\rfloor}. $$ Seymour showed that $\chi^*(G)=\max \{\Delta(G), \mathcal{W}^*(G)\}$. Moreover, the Goldberg-Seymour Conjecture is confirmed Chen, Jing, and Zang states that $\chi^{\prime}(G) \leq \max \{\Delta(G)+1,\lceil\mathcal{W}^*(G)\rceil\}$. Chen, Zang and Zhao developed an algorithm that calculates $ \mathcal{W}^*(G) $ in strongly polynomial time. Inspired by their results, we consider the fractional $ f $-edge-coloring problem ($ f $-FECP) for a given function $ f:V\to \mathbb N_+ $, which is a generalization of FECP: each spanning subgraph induced by a color class has degree at most $ f(v) $ at each vertex $ v\in V $. We give a strongly polynomial-time algorithm for calculating the corresponding fractional $ f $-density $$ \mathcal{W}^*_{f}(G)=\max _{U \subseteq V,|U| \geq 2}\frac{|E(U)|}{\lfloor f(U) / 2\rfloor}. $$

On co-dimension one stability of the soliton for the 1D focusing cubic Klein-Gordon equation

Series
PDE Seminar
Time
Tuesday, February 21, 2023 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Jonas LührmannTexas A&M University

Solitons are particle-like solutions to dispersive evolution equations 
whose shapes persist as time goes by. In some situations, these solitons 
appear due to the balance between nonlinear effects and dispersion, in 
other situations their existence is related to topological properties of 
the model. Broadly speaking, they form the building blocks for the 
long-time dynamics of dispersive equations.

In this talk I will present joint work with W. Schlag on long-time decay 
estimates for co-dimension one type perturbations of the soliton for the 
1D focusing cubic Klein-Gordon equation (up to exponential time scales), 
and I will discuss our previous work on the asymptotic stability of the 
sine-Gordon kink under odd perturbations. While these two problems are 
quite similar at first sight, we will see that they differ by a subtle 
cancellation property, which has significant consequences for the 
long-time dynamics of the perturbations of the respective solitons.

Anderson Localization in dimension two for singular noise

Series
Mathematical Physics and Analysis Working Seminar
Time
Tuesday, February 21, 2023 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Omar HurtadoUC Irvine

We will discuss the work of Ding-Smart (2019) which showed Anderson localization at the bottom of the spectrum for random discrete Schroedinger operators with arbitrary bounded noise, i.e. without any supposition of regularity of the distribution. In this talk, we will discuss at a high level the basic idea behind a multi-scale analysis, as well as the usual ingredients involved in one: resolvent decay at large scales and the Wegner-type estimate.

We will then discuss the obstacles posed by singular distributions, and the various methods used to overcome these obstacles in various regimes, discussing briefly the transfer matrix method used for d=1 by Carmona-Klein-Martinelli (1987) before examining the unique continuation principles used by Bourgain-Kenig (2005) and the Ding-Smart work which are used in d=2 in the continuum and discrete cases respectively, highlighting the unique challenges arising in the discrete case.

On obstructing Lagrangian concordance

Series
Geometry Topology Seminar
Time
Monday, February 20, 2023 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Angela WuLousiana State University

Two knots are said to be concordant if they jointly form the boundary of a cylinder in four-dimensional Euclidean space. In the symplectic setting, we say they are Lagrangian concordant if the knots are Legendrian and the cylinder is Lagrangian. Interestingly, Lagrangian concordance is, unlike smooth concordance, not a symmetric relation. In this talk, I'll discuss various strategies that can be used to obstruct Lagrangian concordance, from basic invariants of Legendrian knots, to the Chekanov-Eliashberg DGA, to building new obstructions from Weinstein cobordisms.

Scalable Bayesian optimal experimental design for efficient data acquisition

Series
Applied and Computational Mathematics Seminar
Time
Monday, February 20, 2023 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 005 and https://gatech.zoom.us/j/98355006347
Speaker
Peng ChenGeorgia Tech CSE

Bayesian optimal experimental design (OED) is a principled framework for maximizing information gained from limited data in Bayesian inverse problems. Unfortunately, conventional methods for OED are prohibitive when applied to expensive models with high-dimensional parameters. In this talk, I will present fast and scalable computational methods for large-scale Bayesian OED with infinite-dimensional parameters, including data-informed low-rank approximation, efficient offline-online decomposition, projected neural network approximation, and a new swapping greedy algorithm for combinatorial optimization.

 

Legendrian knots and their invariants

Series
Geometry Topology Seminar Pre-talk
Time
Monday, February 20, 2023 - 12:45 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Angela WuLousiana State University

Legendrian knots are smooth knots which are compatible with an ambient contact structure. They are an essential object of study in contact and symplectic geometry, and many easily posed questions about these knots remain unanswered. In this talk I will introduce Legendrian knots, their properties, some of their invariants. Expect lots of pictures.

Some results on a simple model of kinetic theory

Series
CDSNS Colloquium
Time
Friday, February 17, 2023 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006; Zoom streaming available
Speaker
Federico BonettoGeorgia Tech

Please Note: Zoom link: https://gatech.zoom.us/j/91390791493?pwd=QnpaWHNEOHZTVXlZSXFkYTJ0b0Q0UT09

In 1955, Mark Kac introduced a simple model to study the evolution of a gas of particles undergoing pairwise collisions. Although extremely simplified in such a way to be rigorously treatable, the model maintains interesting aspects of gas dynamics. In recent years, we worked with M. Loss and others to extend the analysis to more "realistic" versions of the original model.

I will introduce the Kac model and present some standard and more recent results. These results refer to a system with a fixed number of particles and at fixed kinetic energy (micro canonical ensemble) or temperature (canonical ensemble). I will introduce a "Grand Canonical" version of the Kac system and discuss new results on it.

Maximizing minimum eigenvalue in constant dimension.

Series
ACO Student Seminar
Time
Friday, February 17, 2023 - 13:00 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Adam BrownGeorgia Tech Math

In the minimum eigenvalue problem we are given a collection of rank-1 symmetric matrices, and the goal is to find a subset whose sum has large minimum eigenvalue, subject to some combinatorial constraints. The constraints on which subsets we can select, could be cardinality, partition, or more general matroid base constraints. Using pipage rounding and a matrix concentration inequality, we will show a randomised algorithm which achieves a (1- epsilon) approximation for the minimum eigenvalue problem when the matrices have constant size, subject to any matroid constraint.

The bulk of the talk will be background on “pipage rounding, pessimistic estimators and matrix concentration” adapted from the paper with that title by Nicholas J. A. Harvey and Neil Olver. The application to the minimum eigenvalue problem is joint work with Aditi Laddha and Mohit Singh.

Bernoulli decompositions and applications to Schroedinger operators

Series
Mathematical Physics and Analysis Working Seminar
Time
Friday, February 17, 2023 - 12:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Omar HurtadoGeorgia Institute of Technology

We will discuss work of Michael Aizenman, Francois Germinet, Abel Klein, and Simone Warzel from 2007 on optimal Bernoulli decompositions of random variables and applications thereof. We will briefly discuss the basic properties of such decompositions, and demonstrate the existence of decompositions for which the contribution of the Bernoulli disorder is optimized in various ways.

We will then go through a proof of almost sure spectral localization (at the bottom of the spectrum) for continuous random Schroedinger operators with arbitrary bounded disorder. This proof relies on a Bernoulli decomposition of the disorder combined with a slightly stronger variant of the 2005 result from Jean Bourgain and Carlos Kenig showing such localization when the disorder is Bernoulli.

Estimation of smooth functionals in high-dimensional and infinite-dimensional models

Series
Stochastics Seminar
Time
Thursday, February 16, 2023 - 15:30 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Vladimir KoltchinskiiGeorgia Tech

The problem of estimation of smooth functionals of unknown parameters of statistical models will be discussed in the cases of high-dimensional log-concave location models (joint work with Martin Wahl) and infinite dimensional Gaussian models with unknown covariance operator. In both cases, the minimax optimal error rates have been obtained in the classes of H\”older smooth functionals with precise dependence on the sample size, the complexity of the parameter (its dimension in the case of log-concave location models or the effective rank of the covariance in the case of Gaussian models)  and on the degree of smoothness of the functionals. These rates are attained for different types of estimators based on two different methods of bias reduction in functional estimation.

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