When should lockdown be implemented? Devising cost-effective strategies for managing epidemics amid vaccine uncertainty
Doyle, N Cumming, F Thompson, R Tildesley, M PLoS Computational Biology volume 20 issue 7 (18 Jul 2024)
Mon, 26 Aug 2024

14:00 - 15:00
L6

Analytic K-theory for bornological spaces

Devarshi Mukherjee
(University of Münster)
Abstract

We define a version of algebraic K-theory for bornological algebras, using the recently developed continuous K-theory by Efimov. In the commutative setting, we prove that this invariant satisfies descent for various topologies that arise in analytic geometry, generalising the results of Thomason-Trobaugh for schemes. Finally, we prove a version of the Grothendieck-Riemann-Roch Theorem for analytic spaces. Joint work with Jack Kelly and Federico Bambozzi. 

Tue, 29 Oct 2024

14:00 - 15:00
L6

Endomorphisms of Gelfand—Graev representations

Jack G Shotton
(University of Durham)
Abstract

Let G be a reductive group over a finite field F of characteristic p. I will present work with Tzu-Jan Li in which we determine the endomorphism algebra of the Gelfand-Graev representation of the finite group G(F) where the coefficients are taken to be l-adic integers, for l a good prime of G distinct from p. Our result can be viewed as a finite-field analogue of the local Langlands correspondence in families. 

Large and unequal life expectancy declines during the COVID-19 pandemic in India in 2020
Gupta, A Hathi, P Banaji, M Gupta, P Kashyap, R Paikra, V Sharma, K Somanchi, A Sudharsanan, N Vyas, S Science Advances volume 10 issue 29 (19 Jul 2024)
Fri, 09 Aug 2024
16:00
L1

Topology and the Curse of Dimensionality

Gunnar Carlsson
(Stanford University)
Abstract

The "curse of dimensionality" refers to the host of difficulties that occur when we attempt to extend our intuition about what happens in low dimensions (i.e. when there are only a few features or variables)  to very high dimensions (when there are hundreds or thousands of features, such as in genomics or imaging).  With very high-dimensional data, there is often an intuition that although the data is nominally very high dimensional, it is typically concentrated around a much lower dimensional, although non-linear set. There are many approaches to identifying and representing these subsets.  We will discuss topological approaches, which represent non-linear sets with graphs and simplicial complexes, and permit the "measuring of the shape of the data" as a tool for identifying useful lower dimensional representations.

Dark matter line searches with the Cherenkov Telescope Array
Abe, S Abhir, J Abhishek, A Acero, F Acharyya, A Adam, R Aguasca-Cabot, A Agudo, I Aguirre-Santaella, A Alfaro, J Alfaro, R Alvarez-Crespo, N Alves Batista, R Amans, J Amato, E Ambrosi, G Angel, L Aramo, C Arcaro, C Arnesen, T Arrabito, L Asano, K Ascasibar, Y Aschersleben, J Journal of Cosmology and Astroparticle Physics volume 2024 issue 07 (19 Jul 2024)
Extending SkyLLH software for neutrino point source analyses with 10
years of IceCube public data
Bellenghi, C Karl, M Wolf, M (24 Aug 2023) http://arxiv.org/abs/2308.12733v1
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