Seminars and Colloquia by Series

The Distribution of Class Groups for Number Fields

Series
Job Candidate Talk
Time
Monday, February 21, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
online
Speaker
Jiuya WangUniversity of Georgia

Class group is a central object of the study in number theory. We will give an overview of our understanding of the distribution of class groups, with an emphasis on recent progress. In particular, we will explain how the use of symmetry in multiple ways turns out to be an essential tool to obtain many new results on the distribution of class groups.

https://bluejeans.com/555956601/7083

Zarankiewicz problem, VC-dimension, and incidence geometry

Series
Job Candidate Talk
Time
Thursday, February 17, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
https://gatech.bluejeans.com/939739653/6882
Speaker
Cosmin PohoataYale University
The Zarankiewicz problem is a central problem in extremal graph theory, which lies at the intersection of several areas of mathematics. It asks for the maximum number of edges in a bipartite graph on $2n$ vertices, where each side of the bipartition contains $n$ vertices, and which does not contain the complete bipartite graph $K_{s,t}$ as a subgraph. One of the many reasons this problem is rather special among Turán-type problems is that the extremal graphs in question, whenever available, always seem to have to be of algebraic nature, in particular witnesses to basic intersection theory phenomena. The most tantalizing case is by far the diagonal problem, for which the answer is unknown for most values of $s=t$, and where it is a complete mystery what the extremal graphs could look like. In this talk, we will discuss a new phenomenon related to an important variant of this problem, which is the analogous question in bipartite graphs with bounded VC-dimension. We will present several new consequences in incidence geometry, which improve upon classical results. Based on joint work with Oliver Janzer.
 

Stochastic and Convex Geometry for the Analysis of Complex Data

Series
Job Candidate Talk
Time
Thursday, February 10, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
https://gatech.bluejeans.com/532559688
Speaker
Eliza O’ReillyCalifornia Institute of Technology

Many modern problems in data science aim to efficiently and accurately extract important features and make predictions from high dimensional and large data sets. While there are many empirically successful methods to achieve these goals, large gaps between theory and practice remain.  A geometric viewpoint is often useful to address these challenges as it provides a unifying perspective of structure in data, complexity of statistical models, and tractability of computational methods.  As a consequence, an understanding of problem geometry leads both to new insights on existing methods as well as new models and algorithms that address drawbacks in existing methodology.

 In this talk, I will present recent progress on two problems where the relevant model can be viewed as the projection of a lifted formulation with a simple stochastic or convex geometric description. In particular, I will first describe how the theory of stationary random tessellations in stochastic geometry can address computational and theoretical challenges of random decision forests with non-axis-aligned splits. Second, I will present a new approach to convex regression that returns non-polyhedral convex estimators compatible with semidefinite programming. These works open a number of future research directions at the intersection of stochastic and convex geometry, statistical learning theory, and optimization.

Understanding Statistical-vs-Computational Tradeoffs via Low-Degree Polynomials

Series
Job Candidate Talk
Time
Thursday, February 3, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
https://bluejeans.com/500115320/1408
Speaker
Alex WeinUC Berkeley/Simons Institute

A central goal in modern data science is to design algorithms for statistical inference tasks such as community detection, high-dimensional clustering, sparse PCA, and many others. Ideally these algorithms would be both statistically optimal and computationally efficient. However, it often seems impossible to achieve both these goals simultaneously: for many problems, the optimal statistical procedure involves a brute force search while all known polynomial-time algorithms are statistically sub-optimal (requiring more data or higher signal strength than is information-theoretically necessary). In the quest for optimal algorithms, it is therefore important to understand the fundamental statistical limitations of computationally efficient algorithms.

I will discuss an emerging theoretical framework for understanding these questions, based on studying the class of "low-degree polynomial algorithms." This is a powerful class of algorithms that captures the best known poly-time algorithms for a wide variety of statistical tasks. This perspective has led to the discovery of many new and improved algorithms, and also many matching lower bounds: we now have tools to prove failure of all low-degree algorithms, which provides concrete evidence for inherent computational hardness of statistical problems. This line of work illustrates that low-degree polynomials provide a unifying framework for understanding the computational complexity of a wide variety of statistical tasks, encompassing hypothesis testing, estimation, and optimization.

On Gapped Ground State Phases of Quantum Lattice Models

Series
Job Candidate Talk
Time
Monday, January 31, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Amanda YoungTechnical University Munich

Quantum spin systems are many-body physical models where particles are bound to the sites of a lattice. These are widely used throughout condensed matter physics and quantum information theory, and are of particular interest in the classification of quantum phases of matter. By pinning down the properties of new exotic phases of matter, researchers have opened the door to developing new quantum technologies. One of the fundamental quantitites for this classification is whether or not the Hamiltonian has a spectral gap above its ground state energy in the thermodynamic limit. Mathematically, the Hamiltonian is a self-adjoint operator and the set of possible energies is given by its spectrum, which is bounded from below. While the importance of the spectral gap is well known, very few methods exist for establishing if a model is gapped, and the majority of known results are for one-dimensional systems. Moreover, the existence of a non-vanishing gap is generically undecidable which makes it necessary to develop new techniques for estimating spectral gaps. In this talk, I will discuss my work proving non-vanishing spectral gaps for key quantum spin models, and developing new techniques for producing lower bound estimates on the gap. Two important models with longstanding spectral gap questions that I recently contributed progress to are the AKLT model on the hexagonal lattice, and Haldane's pseudo-potentials for the fractional quantum Hall effect. Once a gap has been proved, a natural next question is whether it is typical of a gapped phase. This can be positively answered by showing that the gap is robust in the presence of perturbations. Ensuring the gap remains open in the presence of perturbations is also of interest, e.g., for the development of robust quantum memory. A second topic I will discuss is my research studying spectral gap stability.

URL for the talk: https://bluejeans.com/602513114/7767

 

 

Coloring hypergraphs of small codegree, and a proof of the Erdős–Faber–Lovász conjecture

Series
Job Candidate Talk
Time
Thursday, January 20, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Thomas KellyUniversity of Birmingham

Meeting link: https://bluejeans.com/961048334/8189

A long-standing problem in the field of graph coloring is the Erdős–Faber–Lovász conjecture (posed in 1972), which states that the chromatic index of any linear hypergraph on $n$ vertices is at most $n$, or equivalently, that a nearly disjoint union of $n$ complete graphs on at most $n$ vertices has chromatic number at most $n$.  In joint work with Dong Yeap Kang, Daniela Kühn, Abhishek Methuku, and Deryk Osthus, we proved this conjecture for every sufficiently large $n$.  Recently, we also solved a related problem of Erdős from 1977 on the chromatic index of hypergraphs of small codegree.  In this talk, I will survey the history behind these results and discuss some aspects of the proofs.

Long-time dynamics of dispersive equations

Series
Job Candidate Talk
Time
Tuesday, January 18, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Gong ChenUniversity of Toronto

Please Note: https://bluejeans.com/910698769/4854

Through the pioneering numerical computations of Fermi-Pasta-Ulam (mid 50s) and Kruskal-Zabusky (mid 60s) it was observed that nonlinear equations modeling wave propagation asymptotically decompose as a superposition of “traveling waves” and “radiation”. Since then, it has been a widely believed (and supported by extensive numerics) that “coherent structures” together with radiations describe the long-time asymptotic behavior of generic solutions to nonlinear dispersive equations. This belief has come to be known as the “soliton resolution conjecture”.  Roughly speaking it tells that, asymptotically in time, the evolution of generic solutions decouples as a sum of modulated solitary waves and a radiation term that disperses. This remarkable claim establishes a drastic “simplification” to the complex, long-time dynamics of general solutions. It remains an open problem to rigorously show such a description for most dispersive equations.  After an informal introduction to dispersive equations, I will survey some of my recent results towards understanding the long-time behavior of dispersive waves and the soliton resolution using techniques from both partial differential equations and inverse scattering transforms.

Turbulent Weak Solutions of the 3D Euler Equations

Series
Job Candidate Talk
Time
Thursday, January 13, 2022 - 11:00 for 1 hour (actually 50 minutes)
Location
ONLINE
Speaker
Matthew NovackIAS

Meeting link: https://bluejeans.com/912860268/9947

The Navier-Stokes and Euler equations are the fundamental models for describing viscous and inviscid fluids, respectively. Based on ideas which date back to Kolmogorov and Onsager, solutions to these equations are expected to dissipate energy, which in turn suggests that such solutions are somewhat rough and thus only weak solutions. At these low regularity levels, however, one may construct wild weak solutions using convex integration methods. In this talk, I will discuss the motivation and methodology behind joint work with Tristan Buckmaster, Nader Masmoudi, and Vlad Vicol in which we construct wild solutions to the Euler equations which deviate from the predictions of Kolmogorov's classical K41 phenomenological theory of turbulence.

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