Bayesian forward modeling of galaxy clustering and cross-correlation measurements

May 02, 2022 - 11:00 am to 12:00 pm
Location

Campus, Varian 355

Speaker
Minh Nguyen (University of Michigan) In Person and zoom https://stanford.zoom.us/j/824047074

Zoom info:https://stanford.zoom.us/j/824047074

Email sibirrer@stanford.edu for password.

The forward modeling of galaxy clustering program aims at modeling the galaxy data directly at the field level. Given a three-dimensional map of galaxies from a galaxy redshift survey, this framework jointly infers the underlying Dark Matter field, and relevant astrophysical-cosmological processes. With high signal-to-noise galaxy surveys like DESI, the information gain offered by the former will be significant for many analyses. In this talk, I will present, as applications of forward modeling, two cross-correlation measurements of: 1) the kinematic Sunyaev-Zel'dovich effect and 2) the galaxy intrinsic alignment process. I will show in details how these measurements can benefit from the forward modeling framework and discuss how the improvements translate into future cosmological constraints.