18:00
The hat: an aperiodic monotile
The theory of tilings in the plane touches on diverse areas of mathematics, physics and beyond. Aperiodic sets of tiles, such as the famous Penrose tiling that you see as you walk into the Mathematical Institute, admit tilings of the plane without any translational symmetry. The Penrose tiling is made of two elementary shapes, or tiles, and mathematicians have long wondered about the existence of a single tile that could tile the plane aperiodically. Earlier this year such a shape was discovered: the hat! This hat turned out to be the first of a whole family, and is being celebrated across a two-day meeting in Oxford.
For this public talk, organised in partnership with the Clay Mathematics Institute, Chaim Goodman-Strauss (National Museum of Mathematics/University of Arkansas), one of the authors of this new work, will give an overview of the hat.
This will be followed by a panel discussion featuring Craig Kaplan (University of Waterloo), Marjorie Senechal (Smith College) and Roger Penrose (University of Oxford) as well as Chaim Goodman-Strauss. The discussion, about the impact of this new discovery and future directions will be chaired by Henna Koivusalo (University of Bristol).
Register The whole programme on 20th July will be highly accessible, so please do come along earlier if you can.
ScreeNOT: Optimal Singular Value Thresholding and Principal Component Selection in Correlated Noise
Abstract
Principal Component Analysis (PCA) is a fundamental and ubiquitous tool in statistics and data analysis.
The bare-bones idea is this. Given a data set of n points y_1, ..., y_n, form their sample covariance S. Eigenvectors corresponding to large eigenvalues--namely directions along which the variation within the data set is large--are usually thought of as "important" or "signal-bearing"; in contrast, weak directions are often interpreted as "noise", and discarded along the proceeding steps of the data analysis pipeline. Principal component (PC) selection is an important methodological question: how large should an eigenvalue be so as to be considered "informative"?
Our main deliverable is ScreeNOT: a novel, mathematically-grounded procedure for PC selection. It is intended as a fully algorithmic replacement for the heuristic and somewhat vaguely-defined procedures that practitioners often use--for example the popular "scree test".
Towards tackling PC selection systematically, we model the data matrix as a low-rank signal plus noise matrix Y = X + Z; accordingly, PC selection is cast as an estimation problem for the unknown low-rank signal matrix X, with the class of permissible estimators being singular value thresholding rules. We consider a formulation of the problem under the spiked model. This asymptotic setting captures some important qualitative features observed across numerous real-world data sets: most of the singular values of Y are arranged neatly in a "bulk", with very few large outlying singular values exceeding the bulk edge. We propose an adaptive algorithm that, given a data matrix, finds the optimal truncation threshold in a data-driven manner under essentially arbitrary noise conditions: we only require that Z has a compactly supported limiting spectral distribution--which may be a priori unknown. Under the spiked model, our algorithm is shown to have rather strong oracle optimality properties: not only does it attain the best error asymptotically, but it also achieves (w.h.p.) the best error--compared to all alternative thresholds--at finite n.
This is joint work with Matan Gavish (Hebrew University of Jerusalem) and David Donoho (Stanford).
13:00
Evaluating one-loop string amplitudes
Abstract
Scattering amplitudes in string theory are written as formal integrals of correlations functions over the moduli space of punctured Riemann surfaces. It's well-known, albeit not often emphasized, that this prescription is only approximately correct because of the ambiguities in defining the integration domain. In this talk, we propose a resolution of this problem for one-loop open-string amplitudes and present their first evaluation at finite energy and scattering angle. Our method involves a deformation of the integration contour over the modular parameter to a fractal contour introduced by Rademacher in the context of analytic number theory. This procedure leads to explicit and practical formulas for the one-loop planar and non-planar type-I superstring four-point amplitudes, amenable to numerical evaluation. We plot the amplitudes as a function of the Mandelstam invariants and directly verify long-standing conjectures about their behavior at high energies.
17:15
Evaluating one-loop string amplitudes
Abstract
Scattering amplitudes in string theory are written as formal integrals of correlations functions over the moduli space of punctured Riemann surfaces. It's well-known, albeit not often emphasized, that this prescription is only approximately correct because of the ambiguities in defining the integration domain. In this talk, we propose a resolution of this problem for one-loop open-string amplitudes and present their first evaluation at finite energy and scattering angle. Our method involves a deformation of the integration contour over the modular parameter to a fractal contour introduced by Rademacher in the context of analytic number theory. This procedure leads to explicit and practical formulas for the one-loop planar and non-planar type-I superstring four-point amplitudes, amenable to numerical evaluation. We plot the amplitudes as a function of the Mandelstam invariants and directly verify long-standing conjectures about their behavior at high energies.