Finding general solutions to a mechanical system is often far too much to ask. Instead, we look for more tractable, special solutions, such as the equilibria. If the system is symmetric with respect to a group action then we can also look for the relative equilibria: these are solutions contained to a group orbit. Famous examples include the circular solutions of Euler and Lagrange in the 3-body problem. In this talk I will present a new formalism for finding relative equilibria by defining a 'web structure' on shape space, and demonstrate this by classifying the relative equilibria for the spherical 3-body problem.

We introduce a mixed characteristic analog of log canonical centers in characteristic \(0\) and centers of \(F\)-purity in positive characteristic, which we call centers of perfectoid purity. We show that their existence detects (the failure of) normality of the ring. We also show the existence of a special center of perfectoid purity that detects the perfectoid purity of \(R\), analogously to the splitting prime of Aberbach and Enescu, and investigate its behavior under étale morphisms.

The Euclidean distance geometry (EDG) problem concerns the reconstruction of point configurations in R^n from prior partial knowledge of pairwise inter-point distances, often accompanied by assumptions on the prior being noisy, incomplete or unlabeled. Instances of this problem appear across diverse domains, including dimensionality reduction techniques in machine learning, predicting molecular conformations in computational chemistry, and sensor network localization for acoustic vision. This talk provides a concise (inexhaustive) overview of the typical priors that arise in EDG problems. We will then turn to a specific instance motivated by Cryo-Electron Microscopy (cryo-EM), where recovering the 3-dimensional structure of proteins can be reformulated as an EDG problem with partially labeled distances. For this problem, we will outline a generic recovery result and present a recovery algorithm that is polynomial-time in fixed dimension. The algorithm achieves exact recovery when distances are noiseless and is robust to small levels of noise.

Inequalities for Minkowski sums of convex bodies play a central role in convex geometry and additive combinatorics. A particular  example is the Plünnecke–Ruzsa-type inequality, which also has a geometric analogue for convex bodies. In this talk, we begin by introducing such geometric inequalities and highlighting some of the open problems related to them. We then present functional analogues of Plünnecke–Ruzsa-type inequalities using the alpha-sum, a generalized sup-convolution. Our focus is on integral inequalities for alpha-concave functions, a class that extends log-concave functions. We conclude by discussing sharp constants in the case of decreasing log-concave functions supported on the positive orthant.

We study extremal properties of spherical random polytopes, the convex
hull of random points chosen from the unit Euclidean sphere in Rn. The extremal
properties of interest are the expected values of the maximum and minimum surface area among facets.
We determine the asymptotic growth in every fixed dimension, up to absolute constants.