In Person in Marlar and/or Virtual Brown Bag Lunch
Monday November 7, 2022 at 12:00 Link Below
Join BBL Zoom Meeting
Presentation in Marlar 37-252/37-272 for those wishing to attend in person
Aritra Ghosh, Yale at 12:05 (in person )
Estimating Galaxy Morphological Parameters for ~8 Million Galaxies in the Hyper Suprime-Cam Wide Survey using Bayesian Machine Learning
Abstract: In this talk, I will introduce GaMPEN — an ML framework that can predict full Bayesian posteriors for morphological parameters of galaxies – it produces 40% more accurate uncertainties at 1/100th of the run-time compared to light-profile fitting algorithms. Using GaMPEN, we have created one of the largest morphological catalogs currently available, containing ~8 million Hyper Suprime-Cam (HSC) galaxies with estimates of bulge-to-total light ratio, effective radius, flux, and their associated uncertainties. Currently, we are using this catalog to probe the relationship of morphology with the environment and the buildup of mass, shutting down star formation in these galaxies.
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Yanlong Shi, CalTech at 12:30 pm (remote)
Accretion and feedback of seed BHs in giant molecular clouds
Abstract: I will introduce our recent progress in simulations of BH accretion and feedback in star-forming giant molecular clouds, especially the possibility of hyper-Eddington accretion. In the first part, I will talk about the condition without BH feedback, which is the necessary condition for hyper-Eddington accretion. The second half will contain the simulation with radiative-inefficient feedback models for BH and a parameter survey of BH feedback, including radiation, jets, and cosmic ray.
Bio: Yanlong is a 5th-year graduate student at Caltech working on BH accretion/feedback, he is also highly interested in cosmology with large-scale structures.