Extending the Reshetikhin-Turaev TQFT
Abstract
A d-dimensional TQFT is a topological invariant which assigns (d-1)-dimensional manifolds to vector spaces and d-dimensional cobordisms to linear maps. In the early 90s, Reshetikhin and Turaev constructed examples of these in the case d=3, using the data of certain types of linear categories. In this talk, I will provide an overview of this construction, and then explore how this might be meaningfully extended downwards to assign 1-manifolds to "2-vector spaces". Minimal knowledge of category theory assumed!
14:00
The canonical dimension: a different approach to investigate the wavefront set
Abstract
An important invariant in the complex representation theory of reductive p-adic groups is the wavefront set, because it contains information about the character of such a representation. In this talk, Mick Gielen will introduce a new invariant called the canonical dimension, which can be said to measure the size of a representation and which has a close relation to the wavefront set. He will then state some results he has obtained about the canonical dimensions of compactly induced representations and show how they teach us something new about the wavefront set. This illustrates a completely new approach to studying the wavefront set, because the methods used to obtain these results are very different from the ones usually used.
15:00
Non-Definability of Free Independence
Abstract
QI groups and QI rigidity
Abstract
consider the group of maps preserving its large scale geometry. These
maps are called quasiisometries and the associated group is called the
QI group. Determining the QI group of a metric space is, in general, a
hard problem. Few QI groups are known explicitly, and most of these
results arise from a phenomenon called QI rigidity, which essentially
says that QI(X)=Isom(X). In this talk we will explore these concepts and
give a partial answer to the question which groups can arise as QI
groups of metric spaces. This talk is based on joint work with Joe
MacManus and Lawk Mineh.
13:00
Dowker duality: new proofs and generalizations
Abstract
I will present short, new proofs of Dowker duality using various poset fiber lemmas. I will introduce modifications of joins and products of simplicial complexes called relational join and relational product complexes. Using the relational product complex, I will then discuss generalizations of Dowker duality to settings of relations among three (or more) sets.
13:00
Intrinsic bottleneck distance in merge tree space
Abstract
Merge trees are a topological descriptor of a filtered space that enriches the degree zero barcode with its merge structure. The space of merge trees comes equipped with an interleaving distance dI , which prompts a naive question: is the interleaving distance between two merge trees equal to the bottleneck distance between their corresponding barcodes? As the map from merge trees to barcodes is not injective, the answer as posed is no, but as proposed by Gasparovic et al., we explore intrinsic metrics dI and dB realized by infinitesimal path length in merge tree space, which do indeed coincide. This result suggests that in some special cases the bottleneck distance (which can be computed quickly) can be substituted for the interleaving distance (in general, NP-hard).
Cutting along hyperplanes
Abstract
You can cut a cake in half, a pizza into slices, but can you cut an infinite group? I'll tell you about my sensei's secret cutting technique and demonstrate a couple of examples. There might be some spectral goodies at the end too.
Improving acylindrical actions on trees
Abstract
16:00
Matrix-product state skeletons in Onsager-integrable quantum chains
Abstract
Matrix-product state (MPS) skeletons are connected networks of local one-dimensional quantum lattice models with ground states admitting an MPS representation with finite bond dimension. In this talk, I will discuss how such skeletons underlie certain families of models obeying the Onsager algebra, and how these simple ground states provide a route to explicitly computing correlation functions.