In the vanishing viscosity limit from the Navier-Stokes to Euler equations on domains with boundaries, a main difficulty comes from the mismatch of boundary conditions and, consequently, the possible formation of a boundary layer. Within a purely interior framework, Constantin and Vicol showed that the two-dimensional viscosity limit is justified for any arbitrary but finite time under the assumption that on each compactly contained subset of the domain, the enstrophies are bounded uniformly along the viscosity sequence. Within this framework, we upgrade to local strong convergence of the vorticities under a similar assumption on the p-enstrophies, p > 2. The talk is based on a recent publication with Christian Seis and Emil Wiedemann.

The discrete Hodge Laplacian offers a way to extract network topology and geometry from higher-ordered networks. The operator is inspired by concepts from algebraic topology and differential geometry and generalises the graph Laplacian. In particular, it allows to relate global structure of networks to the local properties of nodes. In my talk, I will talk about some general behaviour of the Hodge Laplacian and then continue to show how to use the extracted information to a) to use trajectory data infer the topology of the underlying network while simultaneously classifying the trajectories and b) to extract cell differentiation trees from single-cell data, an exciting new application in computational genomics.    

The normal covering number $\gamma(G)$ of a finite group $G$ is the minimal size of a collection of proper subgroups whose conjugates cover the group. This definition is motivated by number theory and related to the concept of intersective polynomials. For the symmetric and alternating groups we will see how these numbers are closely connected to some elementary (as in "relating to basic concepts", not "easy") problems in additive combinatorics, and we will use this connection to better understand the asymptotics of $\gamma(S_n)$ and $\gamma(A_n)$ as $n$ tends to infinity.