I am co-organizing a virtual Probability Seminar with Wei-Kuo Chen and Arnab Sen at University of Minnesota for
the Spring 2026 semester. Please email me to get the Zoom link for the seminar series.
The seminar is held on Fridays at 2:30pm (Eastern Time), unless otherwise noted below.
| 01/30/2026 | Sergey Bobkov (U Minnesota) |
| Title: Quantified Cramer-Wold continuity theorem for Kantorovich and Zolotarev distances. | |
| Abstract: Upper bounds for the Kantorovich and Zolotarev distances for
probability measures on multidimensional Euclidean spaces are given in
terms of similar distances between one dimensional projections of the
measures. This quantifies the Cramer-Wold continuity theorem about the
weak convergence of probability measures. Joint work with Friedrich Götze. | |
| 02/06/2026 | Jiaqi Liu (Lehigh) |
| Title: Conformal loop ensemble and its geometric properties. | |
| Abstract The conformal loop ensemble (CLE) is a natural conformally invariant probability measure on infinite collections of non-crossing loops, where each loop looks like an SLE curve. CLE has been proven or conjectured to describe the scaling limit of interfaces of many statistical physics models. Understanding its geometric properties is useful for explaining how it emerges in these scaling limits. In this talk, we focus on the extremal distance, which gives a conformally invariant way of measuring the distance between two loops. We show that the reweighted distribution of extremal distances between CLE loops can be expressed as linear combinations of first exit times and last hitting times of a one-dimensional Brownian motion. This is based on joint work with Nina Holden and Xin Sun. | |
| 02/13/2026 | Arnab Chatterjee (TU Dortmund) |
| Title: Belief Propagation Guided Decimation on random k-XORSAT. | |
| Abstract: We analyse the performance of Belief Propagation Guided Decimation, a physics-inspired message passing algorithm, on the random k-XORSAT problem. Specifically, we derive an explicit threshold up to which the algorithm succeeds with a strictly positive probability \Omega(1) that we compute explicitly, but beyond which the algorithm with high probability fails to find a satisfying assignment. In addition, we analyse a thought experiment called the decimation process for which we identify a (non-) reconstruction and a condensation phase transition. The main results of the present work confirm physics predictions from [RTS: J. Stat. Mech. 2009] that link the phase transitions of the decimation process with the performance of the algorithm, and improve over partial results from a recent article [Yung: Proc. ICALP 2024]. | |
| 02/20/2026 | Ruoyu Wu (Iowa State) |
| Title: TBA | |
| Abstract: TBA | |
| 02/28/2026 | TBA |
| Title: TBA. | |
| Abstract: TBA. | |
| 03/06/2026 | TBA |
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| Abstract: TBA | |
| 03/13/2026 | Spring Break at LU and UMN |