## Seminar Categories

This page lists seminar series that have events scheduled between two months ago and twelve months from now and have speaker information available.

- Applied and Computational Mathematics Seminar (4)
- Climate Seminar (203)
- Colloquium (9)
- Combinatorics Seminar (2)
- Commutative Algebra Seminar (2)
- Dynamical Systems (6)
- IMA Data Science Lab Seminar (11)
- IMA/MCIM Industrial Problems Seminar (6)
- MCFAM Seminar (8)
- PDE Seminar (5)
- Probability Seminar (10)
- Special Events and Seminars (10)

## Current Series

Wed Sep 16 |
## Probability Seminar4:00pm - Via ZoomTail bounds for the averaged empirical distribution on a geodesic in first-passage percolation Wai-Kit Lam, UMN Consider $\mathbb{Z}^d$ with nearest-neighbor edges. In first-passage percolation, we place i.i.d. nonnegative weights $(t_e)$ on the edges, and study the induced graph metric $T(x,y)$. A geodesic is a minimizing path for this metric. In a joint work with M. Damron, C. Janjigian and X. Shen, we study the empirical distribution on a geodesic $\gamma$ from $0$ to $x$: $\nu^x(B) := (number of edges e in \gamma with t_e \in B) / (number of edges e in \gamma)$. We establish bounds for the averaged empirical distribution $E \nu^x(B)$, particularly showing that if the law of $t_e$ has finite moments of any order strictly larger than 1, then roughly speaking the limiting averaged empirical distribution has all moments. |

Wed Sep 23 |
## Probability Seminar9:00am - Via ZoomForest fire processes and near-critical percolation with heavy-tailed impurities Pierre Nolin, City University of Hong Kong We discuss models of forest fires (or epidemics): on a given planar lattice, all vertices are initially vacant, and then become occupied at rate 1. If an occupied vertex is hit by lightning, which occurs at a (typically very small) rate, all the vertices connected to it "burn" instantaneously, i.e. they become vacant. We want to analyze the behavior of such processes near and beyond the critical time (the time after which, in the absence of fires, infinite connected components would emerge). We are led to introduce a percolation model where regions ("impurities") are removed from the lattice, in an independent fashion. These impurities are not only microscopic, but also allowed to be mesoscopic. We are interested in whether the connectivity properties of percolation remain of the same order as without impurities, for values of the percolation parameter close to the critical value. This generalizes a celebrated result by Kesten for near-critical percolation (that can be viewed as critical percolation with single-site impurities). This talk is based on a joint work with Rob van den Berg (CWI and VU, Amsterdam). |

Wed Sep 30 |
## Probability Seminar4:00pm - Via ZoomEmpirical measures, geodesic lengths, and a variational formula in first-passage percolation Erik Bates, University of WisconsinMadison We consider the standard first-passage percolation model on |

Wed Oct 07 |
## Probability Seminar4:00pm - Via ZoomThe r-to-p norm of non-negative random matrices Souvik Dhara, MIT For an n\times n matrix A_n, the r\to p operator norm is defined as \|A_n\|_{r\to p}:= \sup_{x \in R^n:\|x\|_r\leq 1 } \|A_n\|_p for r, p\geq 1. For different choices of r and p, this norm corresponds to key quantities that arise in diverse applications including matrix condition number estimation, clustering of data, and finding oblivious routing schemes in transportation networks. This talk considers r\to p norms of symmetric random matrices with nonnegative entries, including adjacency matrices of Erdos-Renyi random graphs, matrices with positive sub-Gaussian entries, and certain sparse matrices. For 1< p\leq r< \infty, the asymptotic normality, as n\to\infty, of the appropriately centered and scaled norm \|A_n\|_{r\to p} is established. Furthermore, a sharp \ell_\infty-approximation for the unique maximizing vector in the definition of \|A_n\|_{r\to p} is obtained, which may be of independent interest. In fact, the vector approximation result is shown to hold for a broad class of deterministic sequence of matrices having certain asymptotic expansion properties. The results obtained can be viewed as a generalization of the seminal results of F\"{u}redi and Koml\'{o}s (1981) on asymptotic normality of the largest singular value of a class of symmetric random matrices, which corresponds to the special case r=p=2 considered here. In the general case with 1< p\leq r < \infty, the spectral methods are no longer applicable, which requires a new approach, involving a refined convergence analysis of a nonlinear power method and establishing a perturbation bound on the maximizing vector. This is based on a joint work with Debankur Mukherjee (Georgia Tech) and Kavita Ramanan (Brown University). |

Wed Oct 21 |
## Probability Seminar4:00pm - Via ZoomOn microscopic derivation of a continuum mean-curvature flow Sunder Sethuraman, University of Arizona We derive a continuum mean-curvature flow as a scaling limit of a class of zero-range + Glauber interacting particle systems. The zero-range part moves particles while preserving particle numbers, and the Glauber part allows birth and death of particles, while favoring two levels of particle density. When the two parts are simultaneously seen in certain (different) time-scales, and the Glauber part is `bi-stable', a mean-curvature interface flow, incorporating a homogenized `surface tension' reflecting microscopic rates, between the two levels of particle density, can be captured as a limit of the mass empirical density. This is work with Perla El Kettani, Tadahisa Funaki, Danielle Hilhorst, and Hyunjoon Park. |

Wed Oct 28 |
## Probability Seminar4:00pm - Via ZoomRandom walks on dynamic random environments with non-uniform mixing Marcelo Hilário, The Federal University of Minas Gerais In this talk, we will discuss recent results on the limiting behavior of random walks on dynamic random environments. We will mainly discuss the case when then random walk evolves on one-dimensional random environments given by conservative interacting particle systems such as the simple symmetric exclusion process. Our results depend a great deal on space-time mixing properties imposed on the underlying environment and also on other features like the dimension and the type of allowed transitions. Conservation of particles leads to poor-mixing conditions which complicate the applicability of available tools and to overcome this difficulty we use renormalization to obtain the law of large numbers, large deviation estimates, and sometimes central limit theorems. The talk is based on several joint works with Oriane Blondel, Frank den Hollander, Daniel Kious, Renato dos Santos, and Vladas Sidoravicius. |

Wed Nov 04 |
## Probability Seminar4:00pm - Via ZoomHypercontractivity, Convexity, and Lower Deviations Petros Valettas, University of Missouri The concentration of measure phenomenon is an indispensable tool in the study of high-dimensional phenomena. |

Wed Nov 18 |
## Probability Seminar9:00am - Via ZoomQuantitative estimates for the effect of disorder on low-dimensional lattice systems Ron Peled, Tel Aviv University The addition of an arbitrarily weak random field to low-dimensional classical statistical physics models leads to the "rounding" of first-order phase transitions at all temperatures, as predicted in 1975 by Imry and Ma and proved rigorously in 1989 by Aizenman and Wehr. This phenomenon was recently quantified for the two-dimensional random-field Ising model (RFIM), proving that it exhibits exponential decay of correlations at all temperatures. The RFIM analysis relies on monotonicity (FKG) properties which are absent in many other classical models. The talk will present new results on the quantitative aspects of the phenomenon for general systems with discrete and continuous symmetries, including Potts, spin O(n), spin glass and height function models. |

Wed Dec 02 |
## Probability Seminar9:00am - Via ZoomSome properties of the discrete membrane model Alessandra Cipriani, UT Delft The discrete membrane model (MM) is a random interface model for separating surfaces that tend to preserve curvature. It is a very close relative of the discrete Gaussian free field (DGFF), for which instead the most likely interfaces are those preserving the mean height. However working with the two models presents some key differences, in that in the MM the shape is driven by the biharmonic operator, while the DGFF is essentially a Gaussian perturbation of harmonic functions. In particular, a lot of tools (electrical networks, random walk representation of the covariance) are available for the DGFF and lack in the MM. In this talk we will review some basic properties of the MM, and we will investigate a random walk representation for the covariances of the MM and what it can bring forth in terms of scaling limits of its extremes. This talk is based on joint works, partly ongoing, with Biltu Dan, Rajat Subhra Hazra (ISI Kolkata) and Rounak Ray (TU/e). |

Wed Dec 09 |
## Probability Seminar4:00pm - Via ZoomOn the extension complexity of random polytopes Lisa Sauermann, IAS Sometimes, it is possible to represent a complicated polytope as a projection of a much simpler polytope. To quantify this phenomenon, the extension complexity of a polytope P is defined to be the minimum number of facets in a (possibly higher-dimensional) polytope from which P can be obtained as a (linear) projection. In this talk, we discuss some results on the extension complexity of random polytopes. For a fixed dimension d, we consider random d-dimensional polytopes obtained as the convex hull of independent random points either in the unit ball or on the unit sphere. In both cases, we prove that the extension complexity is typically on the order of the square root of number of vertices of the polytope. Joint work with Matthew Kwan and Yufei Zhao |

Wed Jan 20 |
## Probability Seminar4:00pm - via ZoomGrothendieck L_p problem for Gaussian matrices Arnab Sen, UMN Consider the optimization problem where we maximize the quadratic form of a large Gaussian matrix over the unit L_p ball. The case p = 2 corresponds to the top eigenvalue of the Gaussian Orthogonal Ensemble. On the other hand, when p = ?,the maximum value is the ground state energy of the mean-field Ising spin glass model and its limit can be expressed by the Parisi formula. In the talk, I will describe the limit of this optimization problem for general p and discuss some results on the behavior of optimizers along with some open problems. This is joint work with Wei-Kuo Chen. |

Wed Jan 27 |
## Probability Seminar9:00am - via ZoomThe two-dimensional continuum random field Ising model Rongfeng Sun, National University of Singapore In this talk, I will explain how to construct the two-dimensional continuum random field Ising model via scaling limits of a random field perturbation of the critical two-dimensional Ising model with diminishing disorder strength. Almost surely with respect to the continuum random field given by a white noise, the law of the magnetisation field is singular with respect to that of the two-dimensional continuum pure Ising model constructed by Camia, Garban and Newman. Based on joint work with Adam Bowditch. |

Wed Feb 03 |
## Probability Seminar4:00pm - via ZoomPlanar percolation and Benjamini-Schramm conjecture Zhongyang Li, University of Connecticut I will show that for a non-amenable, locally finite, connected, transitive, planar graph with one end, any automorphism invariant site percolation on the graph does not have exactly 1 infinite 1-cluster and exactly 1 infinite 0-cluster a.s. If we further assume that the site percolation is insertion-tolerant and a.s. there exists a unique infinite 0-cluster, then a.s. there are no infinite 1-clusters. I will also discuss how to apply these results to solve two conjectures of Benjamini and Schramm in 1996. |

Wed Feb 10 |
## Probability Seminar9:00am - via ZoomThe height of Mallows trees Louigi Addario-Berry, McGill University Mallows trees are the search trees corresponding to Mallows permutations. Mallows permutations are a parameterized family of random permutations interpolating between the uniformly random permutation and the identity permutation. The corresponding search trees interpolate between random binary search trees and paths. I'll present what we know about the height and structure of such trees, as well as future research possibilities on the subject. |

Wed Feb 17 |
## Probability Seminar4:00pm - via ZoomThe heat and the landscape Bálint Virág, University of Toronto If lengths 1 and 2 are assigned randomly to each edge in the planar grid, what are the fluctuations of distances between far away points? This problem is open, yet we know, in great detail, what to expect. The directed landscape, a universal random plane geometry, provides the answer to such questions. In some models, such as directed polymers, the stochastic heat equation, or the KPZ equation, random plane geometry hides in the background. Principal component analysis, a fundamental statistical method, comes to the rescue: BBP statistics can be used to show that these models converge to the directed landscape. |

Wed Feb 24 |
## Probability Seminar4:00pm - via ZoomFurther Simplifying the Glass Problem Patrick Charbonneau, Duke University The random Lorentz gas (RLG) is a minimal model of both transport in heterogenous media and structural glasses. Yet these two perspectives are fundamentally inconsistent, as the dynamical arrest is continuous in the former and discontinuous in the latter. This tension hinders our understanding of either phenomenon, as well as of the RLG itself. By considering an exact solution of the RLG in the infinite- dimensional d ? ? limit as well as numerics in d = 2 . . . 20 we here resolve this paradox. Our results reveal the importance of instantonic corrections, related to rare cage escapes, in unifying glass and percolation physics. This advance suggests a starting point for a first-principle description of hopping processes in structural glasses. We also conjecture tighter formal bounds on the asymptotic d ? ? RLG percolation threshold, which may further enlighten our understanding of that model. |

Wed Mar 03 |
## Probability Seminar4:00pm - via ZoomOn the TAP equations for the Sherrington-Kirkpatrick Model Christian Brennecke, Harvard University In this talk, I will review the Thouless-Anderson-Palmer (TAP) equations for the classical Sherrington-Kirkpatrick spin glass and present a dynamical derivation, valid at sufficiently high temperature. In our derivation, the TAP equations follow as a simple consequence of the decay of the two point correlation functions. The methods can also be used to establish decay of higher order correlation functions. We illustrate this by proving a suitable decay bound on the three point functions which implies an analogue of the TAP equations for the two point functions. The talk is based on joint work with A. Adhikari, P. von Soosten and H.T. Yau. |

Wed Mar 10 |
## Probability Seminar4:00pm - via ZoomProbability Seminar TBD |

Wed Mar 17 |
## Probability Seminar9:00am - via ZoomTriviality of the geometry of mixed p-spin spherical Hamiltonians with external field David Belius, University of Basel Isotropic Gaussian random fields on the sphere are paradigmatic high dimensional complex functions. Due to their appearance in spin glass models in statistical physics, they are also known as mixed p-spin spherical Hamiltonians. One manifestation of the complexity is the presence, in general, of an exponentially large number of critical points. In this talk I will present a result stating that in the presence of a deterministic linear term (external field in the physics terminology) with strength above a certain threshold, the geometry of such functions trivializes in the sense that the only critical points of the random function are then one maximum and one minimum. This extends work of Fyodorov '13, which identified the trivial regime for the special case of pure p-spin Hamiltonians with random external field, and makes mathematically rigorous part of the results of work of Ros et al '19 which derived this claim for pure p-spin Hamiltonians with deterministic external field using physics methods. Our main tool is the Kac-Rice formula for computing the expected number of critical points of random functions. Based on joint work with Jiri Cerny, Shuta Nakajima, and Marius Schmidt. |

Wed Mar 24 |
## Probability Seminar4:00pm - via ZoomProbability Seminar TBD |

Wed Mar 31 |
## Probability Seminar4:00pm - via ZoomExtremal and critical eigenvalue statistics of random matrices Benjamin Landon, MIT We discuss recent results on classes of random eigenvalue statistics of critical or extremal nature. The study of the largest gap between consecutive eigenvalues of random matrices was first urged by Diaconis with the goal of understanding the correspondence between random matrices and number theory. We present a comparison theorem that shows that this quantity is universal within the class of generalized Wigner matrices. The fluctuations of a single bulk eigenvalue and the eigenvalue counting function were determined by Gustavsson for the GUE. We discuss the universality of these quantities for general classes of matrices, and lower order corrections showing that these quantities are essentially on the boundary between universal and non-universal fluctuations. Joint work with P. Lopatto, J. Marcinek and P. Sosoe |

Wed Apr 07 |
## Probability Seminar9:00am - via ZoomBranching random walks, characteristic polynomials, and zeta: log-correlation, moments, and extrema Emma Bailey, University of Bristol In this talk I will introduce three log-correlated processes and present results on their moments (and moments of moments), and how these relate to their extremes. This study features connections with integrable systems (in particular Toeplitz and Hankel determinants), RH problems, the Fyodorov-Hiary-Keating conjectures, Painlev\'e equations, Young diagrams and Gelfand-Tsetlin patterns, large deviations and more.
This talk will include work joint with Louis-Pierre Arguin, Theo Assiotis, Jon Keating. |

Wed Apr 14 |
## Probability Seminar9:00am - via ZoomMultiple Equilibria and Resilience in Large Complex Systems: beyond May-Wigner model Yan Fyodorov, King's College London I will discuss two different models of randomly coupled N>>1 autonomous differential equations with the aim of counting their fixed points (aka equilibria), and classifying them by their ''instability index'', i.e. the number of unstable directions. In the first model ( studied in a joint paper with G. Ben Arous & B. Khoruzhenko) characterized by both translational and rotational statistical symmetry of the vector field, we estimate the probability of an equilibrium to have a given index in a phase with exponentially many equilibria. In the second model (studied with S. Belga Fedeli & J. Ipsen) characterized by only rotational statistical symmetry around a chosen stable equilibrium, we find a characteristic distance beyond which the multitude of equilibria prevents a trajectory to go towards the stable equilibrium. This may help to shed some light on ''resilience'' mechanisms of complex ecosystems. |

Wed Apr 21 |
## Probability Seminar4:00pm - via ZoomProbability Seminar TBD |