State of the Universe

Improving galaxy cluster mass estimation with machine learning

by Dr. Digvijay Wadekar (IAS, Princeton)

Thursday, January 20, 2022 from to (Asia/Kolkata)
at A 304 and Zoom Meeting: https://zoom.us/j/82512956967?pwd=angyQ0ZDdHZUdzFUbjkybmxsWFNFUT09 Meeting ID: 825 1295 6967 Passcode: 384194
Description
Accurately estimating masses of galaxy clusters is needed to extract cosmological information from them. It is, therefore, crucial to find combinations of observable properties of clusters which have a low-scatter relationship with their masses. Machine learning (ML) tools provide a quick and efficient way of looking for low-scatter relations in abstract high- dimensional parameter spaces. I will present a new and a more accurate method for estimating cluster masses which combines observables from CMB and X-ray surveys. More generally, I will show how ML tools can be useful for estimating distances and masses of astrophysical objects, making mock catalogs, and extracting cosmological information from non-linear scales.