PhD Thesis Defense: Gourav Khullar

12:00–1:00 pm ERC 401

Gourav Khullar "Stellar Mass Assembly in Galaxy Clusters and High-Redshift Gravitationally Lensed Galaxies"

Advisor: Prof. Michael D Gladders

A major challenge in the field of extragalactic astrophysics is understanding when the most massive galaxies form the bulk of their stars, and determining the specific pathways they take to assemble stellar mass across a wide range of redshifts and environments. In this thesis, I describe my work to characterize stellar populations in massive galaxies at two epochs — redshifts ~0.5 and ~5.

I use spectra of galaxies in massive South Pole Telescope galaxy clusters to address the question: on what timescales do galaxies that end up in clusters form their stars, and does the cluster sample matter when studying these properties? This mass-limited cluster sample across redshifts 0.3 < z < 1.5 allows me to constrain star formation histories and formation redshifts of 900 quiescent galaxies in clusters, as a function of cluster environment and mass. This study explores mass-dependent evolution in cluster quiescent galaxies and characterizes galaxy evolution across a descendent-antecedent cluster sample.

On the other ‘end’ of the redshift scale, I describe the discovery and characterization of high-redshift lensed galaxies by the COOL-LAMPS collaboration, including COOL J1241+2219 (CJ1241), a lensed galaxy at z = 5.04 that is the brightest galaxy known at z > 5 (at AB magnitude z~20.5). Using ground-based spectrophotometric data and SED fitting analyses, we find CJ1241 to be an intrinsically luminous and massive star-forming galaxy near the epoch of reionization. With anticipated multi-wavelength spectroscopic data, including from an approved JWST Cycle 1 Program (GO 2566, PI: Khullar), I describe the anticipated improvements in constraints on old stellar populations, dust and metallicity in CJ1241. I also show first results aimed at comparing CJ1241 and other COOL-LAMPS discovered lensed massive galaxies at z>3 with their potential descendents — quiescent massive lensed galaxies at lower redshifts. Finally, I describe efforts to create efficient machine learning-based frameworks — specifically using simulation-based inference (SBI) — to calculate posterior distributions of key galaxy parameters, and motivate future efforts to study stellar mass assembly in massive galaxies across different epochs.

Event Type

PhD Thesis Defenses

May 20