Seminars and Colloquia by Series

Affine spheres over Polygons, Extremal length and a new classical minimal surface: a problem I can do and two I cannot

Series
Analysis Seminar
Time
Wednesday, September 21, 2022 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Michael WolfGeorgia Tech

In this introductory talk, we describe an older result (with David Dumas) that relates hyperbolic affine spheres over polygons to polynomial Pick differentials in the plane. All the definitions will be developed.  In the last few minutes, I will quickly introduce two analytic problems in other directions that I struggle with.

New lift matroids for gain graphs

Series
Graph Theory Seminar
Time
Tuesday, September 20, 2022 - 15:45 for 1 hour (actually 50 minutes)
Location
Skiles 005
Speaker
Zach WalshGeorgia Tech

Given a graph G with edges labeled by a group, a construction of Zaslavsky gives a rank-1 lift of the graphic matroid M(G) that respects the group-labeling. For which finite groups can we construct a rank-t lift of M(G) with t > 1 that respects the group-labeling? We show that this is possible if and only if the group is the additive subgroup of a non-prime finite field. We assume no knowledge of matroid theory.

Necessary and Sufficient Conditions for Optimal Control of Semilinear Stochastic Partial Differential Equations

Series
PDE Seminar
Time
Tuesday, September 20, 2022 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 006
Speaker
Lukas WesselsGeorgia Tech and Technische Universität Berlin

In this talk, we consider a finite-horizon optimal control problem of stochastic reaction-diffusion equations. First we apply the spike variation method which relies on introducing the first and second order adjoint state. We give a novel characterization of the second order adjoint state as the solution to a backward SPDE. Using this representation, we prove the maximum principle for controlled SPDEs. 

As another application of our characterization of the second order adjoint state, we derive additional necessary optimality conditions in terms of the value function. These results generalize a classical relationship between the adjoint states and the derivatives of the value function to the case of viscosity differentials.

The last part of the talk is devoted to sufficient optimality conditions. We show how the necessary conditions lead us directly to a non-smooth version of the classical verification theorem in the framework of viscosity solutions.

This talk is based on joint work with Wilhelm Stannat:  W. Stannat, L. Wessels, Peng's maximum principle for stochastic partial differential equations, SIAM J. Control Optim., 59 (2021), pp. 3552–3573 and W. Stannat, L. Wessels, Necessary and Sufficient Conditions for Optimal Control of Semilinear Stochastic Partial Differential Equations, https://arxiv.org/abs/2112.09639, 2022.

Efficient Krylov subspace methods for uncertainty quantification

Series
Applied and Computational Mathematics Seminar
Time
Monday, September 19, 2022 - 14:00 for 1 hour (actually 50 minutes)
Location
Skiles 005 and https://gatech.zoom.us/j/98355006347
Speaker
Julianne ChungEmory University
Uncertainty quantification for linear inverse problems remains a challenging task, especially for problems with a very large number of unknown parameters (e.g., dynamic inverse problems), for problems where computation of the square root and inverse of the prior covariance matrix are not feasible, and for hierarchical problems where the mean is not known a priori. This work exploits Krylov subspace methods to develop and analyze new techniques for large-scale uncertainty quantification in inverse problems. We assume that generalized Golub-Kahan based methods have been used to compute an estimate of the solution, and we describe efficient methods to explore the posterior distribution. We present two methods that use the preconditioned Lanczos algorithm to efficiently generate samples from the posterior distribution. Numerical examples from dynamic photoacoustic tomography and atmospheric inverse modeling, including a case study from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite, demonstrate the effectiveness of the described approaches.

Hyperbolic models for CAT(0) spaces by Abdul Zalloum

Series
Geometry Topology Seminar
Time
Monday, September 19, 2022 - 14:00 for 1 hour (actually 50 minutes)
Location
Speaker
Abdalrazzaq (Abdul) ZalloumUniversity of Toronto

Two of the most well-studied topics in geometric group theory are CAT(0) cube complexes and mapping class groups. This is in part because they both admit powerful combinatorial-like structures that encode their (coarse) geometry: hyperplanes for the former and curve graphs for the latter. In recent years, analogies between the two theories have become more apparent. For instance: there are counterparts of curve graphs for CAT(0) cube complexes and rigidity theorems for such counterparts that mirror the surface setting, and both can be studied using the machinery of hierarchical hyperbolicity. However, the considerably larger class of CAT(0) spaces is left out of this analogy, as the lack of a combinatorial-like structure presents a difficulty in importing techniques from those areas. In this talk, I will speak about recent work with Petyt and Spriano where we bring CAT(0) spaces into the picture by developing analogues of hyperplanes and curve graphs for them. The talk will be accessible to everyone, and all the aforementioned terms will be defined.

Algebraic groups, moduli spaces of matroids, and the field with one element

Series
Algebra Seminar
Time
Monday, September 19, 2022 - 13:30 for 1 hour (actually 50 minutes)
Location
Clough 125 Classroom
Speaker
Matt BakerGeorgia Institute of Technology

 I will give an introduction to Oliver Lorscheid’s theory of ordered blueprints – one of the more successful approaches to “the field of one element” – and sketch its relationship to Tits models for algebraic groups and moduli spaces of matroids. The basic idea for these applications is quite simple: given a scheme over Z defined by equations with coefficients in {0,1,-1}, there is a corresponding “blue model” whose K-points (where K is the Krasner hyperfield) sometimes correspond to interesting combinatorial structures. For example, taking closed K-points of a suitable blue model for a split reductive group scheme G over Z gives the Weyl group of G, and taking K-points of a suitable blue model for the Grassmannian G(r,n) gives the set of matroids of rank r on {1,...,n}.

From walls to cube complexes by Abdul Zalloum

Series
Geometry Topology Seminar Pre-talk
Time
Monday, September 19, 2022 - 13:00 for 1 hour (actually 50 minutes)
Location
Speaker
Abdalrazzaq (Abdul) ZalloumUniversity of Toronto

A geodesic metric space is said to be CAT(0) if triangles are at most as fat as triangles in the Euclidean plane. A CAT(0) cube complex is a CAT(0) space which is built by gluing Euclidean cubes isometrically along faces. Due to their fundamental role in the resolution of the virtual Haken's conjecture, CAT(0) cube complexes have since been a central object of study in geometric group theory and their study has led to ground-breaking advances in 3–manifold theory. The class of groups admitting proper cocompact actions on CAT(0) cube complexes is very broad and it includes hyperbolic 3-manifolds, most non-geometric 3 manifold groups, small cancelation groups and many others. 

 

A revolutionary work of Sageev shows that the entire structure of a CAT(0) cube complexes is encoded in its hyperplanes and the way they interact with one another. I will discuss Sageev's theorem which provides a recipe for constructing group actions on CAT(0) cube complexes using some very simple and purely set theoretical data.

On a conjecture of Graham on the p-divisibility of central binomial coefficients

Series
Combinatorics Seminar
Time
Friday, September 16, 2022 - 15:00 for 1 hour (actually 50 minutes)
Location
Skiles 202
Speaker
Ernie CrootGeorgia Institute of Technology

I will discuss an old conjecture of Ron Graham on whether there are infinitely many integers $n$ so that $\mathrm{gcd}({{2n} \choose n}, 105)=1$, as well as recent progress on a version of this problem where 105 is replaced with a product of $r$ distinct primes. This is joint work with Hamed Mousavi and Maxie Schmidt.

Smooth structures on open 4-manifolds II

Series
Geometry Topology Working Seminar
Time
Friday, September 16, 2022 - 14:00 for 1.5 hours (actually 80 minutes)
Location
Skiles 006
Speaker
John EtnyreGeorgia Tech

Please Note: One of the most interesting and surprising features of manifold topology is the existence of topological 4-manifold that admit infinitely many smooth structures. In these talks I will discuss what is known about these “exotic” smooth structures on open manifolds, starting with R^4 and then moving on to other open 4-manifolds. We will also go over various constructions and open questions about these manifolds.

When dynamics meet machine learning

Series
Time
Friday, September 16, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
Online
Speaker
Molei TaoGeorgia Tech

https://gatech.zoom.us/j/95197085752?pwd=WmtJUVdvM1l6aUJBbHNJWTVKcVdmdz09

Abstract:  The interaction of machine learning and dynamics can lead to both new methodology for dynamics, and deepened understanding and/or efficacious algorithms for machine learning. This talk will give examples in both directions. Specifically, I will first discuss data-driven learning and prediction of mechanical dynamics, for which I will demonstrate one strong benefit of having physics hard-wired into deep learning models; more precisely, how to make symplectic predictions, and how that probably improves the accuracy of long-time predictions. Then I will discuss how dynamics can be used to better understand the implicit biases of large learning rates in the training of machine learning models. They could lead to quantitative escapes from local minima via chaos, which is an alternative mechanism to commonly known noisy escapes due to stochastic gradients. I will also report how large learning rates bias toward flatter minimizers, which arguably generalize better.

Pages