Past Events

We obtain upper bounds for the Steklov eigenvalues of warped products Ω × h Σ , where Ω is a compact Riemannian manifold with boundary and Σ is a closed Riemannian manifold, under assumptions on the L p -norm of the warping function h . The upper...

The first half of the talk will center on modeling the interplay between human behavior and disease outbreaks, as well as discussing survey-collected human behavior data from all 50 states of the United States during the first two years of the COVID...

We investigate the Steklov eigenvalue problem in the exterior of a bounded Euclidean domain. In particular, we prove the equivalence of several formulations of this problem previously proposed in the literature. We derive geometric eigenvalue...

Low-rank methods have proven their utility as a complexity reduction technique for kinetic equations, both in the collisionless and collisional regimes (see, e.g., the recent review article https://doi.org/10.1016/j.jcp.2025.114191). Since the...

In his seminal 1973 thesis, Philippe Delsarte identified two important families of association schemes deserving of in-depth study: the P-polynomial association schemes and the Q-polynomial association schemes. P-polynomial association schemes are...

The log-rank conjecture is a longstanding open problem with multiple equivalent formulations in complexity theory and mathematics. In its linear-algebraic form, it asserts that the rank and partitioning number of a Boolean matrix are quasi...

The incipient infinite cluster is a critical percolation cluster that is conditioned on being infinitely large. Even though the condition has probability zero, Kesten demonstrated the first such construction for critical two-dimensional percolation...

The rainbow and the brain have in common that frequencies are produced. In both cases there is a function of frequency, f, called the power spectral density (PSD). In both cases invasive investigation spoils the investigated object. This talk will...

I will give an introduction to Poisson geometry, starting with its role in the dynamics of physical systems and its relationship to symplectic geometry. Through the use of illustrative examples, I will highlight some of the basic features of Poisson...

Machine learning is transforming the way we approach the laws of nature. PhysicsML — the fusion of machine learning with physics-based modeling — is rapidly advancing fields from computational biology and climate forecasting to product design and...