Fitting manifolds to data.

Charlie Fefferman
Princeton University
April 7, 2018

The problems come in two flavors.
Extrinsic Flavor: Given a point cloud in R^N sampled from an unknown probability density, how can we decide whether that probability density is concentrated near a low-dimensional manifold M with reasonable geometry? If such an M exists, how can we find it? (Joint work with S. Mitter and H. Narayanan)

Protein Folding Characterization via Persistent Homology

Marcio Gameiro
University of Sao Paolo
April 7, 2018

We use persistent homology to analyze predictions of protein folding by trying to identify global geometric structures that contribute to the error when the protein is misfolded. The goal is to find correlations between global geometric structures, as measured by persistent homology, and the failure to predict the correct folding. This technique could be useful in guiding the energy minimization techniques to the correct minimum corresponding to the desired folding.

Exceptional holonomy and related geometric structures: Examples and moduli theory.

Simon Donaldson
Stonybrook University
April 4, 2018

We will discuss the constructions of compact manifolds with exceptional holonomy (in fact, holonomy $G_{2}$),  due to Joyce and Kovalev.  These both use “gluing constructions”. The first involves de-singularising quotient spaces and the second constructs a 7-manifold from “building blocks” derived from Fano threefolds.  We will explain how the local moduli theory is determined by a period map and discuss connections between the global moduli problem and Riemannian convergence theory (for manifolds with bounded Ricci curvature).