Lingyuan Ji (Johns Hopkins)
Title: Standard Model Prediction for Cosmological 21cm Circular Polarization
Abstract: Before cosmic reionization, hydrogen atoms acquire a spin polarization quadrupole through interaction with the anisotropic 21-cm radiation field. The interaction of this quadrupole with anisotropies in the cosmic microwave background (CMB) radiation field gives a net spin orientation to the hydrogen atoms. The 21-cm radiation emitted by these spin-oriented hydrogen atoms is circularly polarized. Here, we reformulate succinctly the derivation of the expression for this circular polarization in terms of Cartesian (rather than spherical) tensors. We then compute the angular power spectrum of the observed Stokes-V parameter in the standard ΛCDM cosmological model and show how it depends on redshift, or equivalently, the observed frequency.
Taylor Faucett (UC Irvine)
Title: Physicists Learning from Machines Learning
Abstract:
Machine Learning methods are extremely powerful but often function as black-box problem solvers, providing improved performance at the expense of clarity. Our work describes a new machine learning approach which translates the strategy of a deep neural network into simple functions that are meaningful and intelligible to the physicist, without sacrificing performance improvements. We apply this approach to benchmark high-energy problems of fat-jet classification and electron identification. In each case, we find simple new observables which provide additional classification power and novel insights into the nature of the problem.