Optimal bailout strategies resulting from the drift controlled
supercooled Stefan problem
Cuchiero, C Reisinger, C Rigger, S (02 Nov 2021) http://arxiv.org/abs/2111.01783v3
Hypercontractivity meets random convex hulls: analysis of randomized multivariate cubatures
Hayakawa, S Lyons, T Oberhauser, H Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (17 May 2023)
Spatial Heterogeneity Localizes Turing Patterns in Reaction-Cross-Diffusion Systems
Gaffney, E Krause, A Maini, P Wang, C (18 Oct 2022)
Thu, 24 Nov 2022
16:00
L5

Weyl Subconvexity, Generalized $PGL_2$ Kuznetsov Formulas, and Optimal Large Sieves

Ian Petrow
(UCL)
Abstract

Abstract: We give a generalized Kuznetsov formula that allows one to impose additional conditions at finitely many primes.  The formula arises from the relative trace formula. I will discuss applications to spectral large sieve inequalities and subconvexity. This is work in progress with M.P. Young and Y. Hu.

 

Mon, 07 Nov 2022
15:00
N3.12

The Gauss problem for central leaves.

Valentijn Karemaker
(University of Utrecht)
Abstract

For a family of finite sets whose cardinalities are naturally called class numbers, the Gauss problem asks to determine the subfamily in which every member has class number one. We study the Siegel moduli space of abelian varieties in characteristic $p$ and solve the Gauss problem for the family of central leaves, which are the loci consisting of points whose associated $p$-divisible groups are isomorphic. Our solution involves mass formulae, computations of automorphism groups, and a careful analysis of Ekedahl-Oort strata in genus $4$. This geometric Gauss problem is closely related to an arithmetic Gauss problem for genera of positive-definite quaternion Hermitian lattices, which we also solve.

Thu, 24 Nov 2022
16:00
Virtual

The Legendre Memory Unit: A neural network with optimal time series compression

Chris Eliasmith
(University of Waterloo)

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Further Information
Abstract

We have recently proposed a new kind of neural network, called a Legendre Memory Unit (LMU) that is provably optimal for compressing streaming time series data. In this talk, I describe this network, and a variety of state-of-the-art results that have been set using the LMU. I will include recent results on speech and language applications that demonstrate significant improvements over transformers. I will discuss variants of the original LMU that permit effective scaling on current GPUs and hold promise to provide extremely efficient edge time series processing.

Thu, 17 Nov 2022
14:00
L6

Dispersive Sum Rules in AdS${}_2$

Waltraut Knop
(Stony Brook)

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It is also possible to join online via Zoom.

Abstract

Dispersion relations for S-matrices and CFT correlators translate UV consistency into bounds on IR observables. In this talk, I will begin with briefly introducing dispersionrelations in 2D flat space which will guide the analogous discussion in AdS2/CFT1. I will introduce a set of functionals acting on the 1D CFT. These will allow us to prove bounds on higher-derivative couplings in weakly coupled non-gravitational EFTs in AdS2. At the leading order in the bulk-point limit, the bounds agree with the flat-space result. Furthermore we can compute the leading universal effect of finite AdS radius on the bounds.

Mon, 24 Oct 2022
16:00
L6

Recasting Selmer Schemes

Jay Swar
Abstract

The Chabauty-Kim method is an effective algorithm for finding the $S$-integral points of hyperbolic curves by directly using the hyperbolicity in group-cohomological arguments. Central objects in the theory are affine spaces known as a Selmer schemes. We'll introduce the CK method and Selmer schemes, and demonstrate some additional structures possessed by Selmer schemes which can aid in implementing the CK method.
 

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