Advisor: Dr. Mallory Molina & Dr. Kelly Holley-Bockelmann
Department of Physics and Astronomy at Vanderbilt University, Nashville, Tennessee
While it is well known that every massive galaxy (Mstellar ~ 10^11 M⊙) has a supermassive black hole (SMBH) at its center, it remains unclear how these objects formed, as we lack the technology to observe them in their primordial states. The population of black holes (BH) in nearby dwarf galaxies (Mstellar ~ 10^9 M⊙) serve as an observable analog of the first generation of SMBH seeds. We often search for BHs in dwarf galaxies by looking for the signatures of active galactic nuclei (AGN). Due to the wealth of all-sky data available, creating infrared color-color diagrams is one effective method. Unfortunately, infrared color cuts for dwarf galaxies are significantly contaminated by extreme star formation, leading to many false AGN detections and an inaccurate snapshot of their BH population. We will simulate starburst dwarf galaxies to identify the physical characteristics that cause extreme star formation to be misidentified as AGN. We will produce a suite of multi-wavelength observational constraints that can be used to minimize starburst contamination in future infrared AGN searches, with a focus on the ongoing DESI and LSST surveys. This work will help constrain the population of BHs in dwarf galaxies, which has important implications for the origin of SMBHs.
Advisor: Dr. Jeyhan Kartaltepe
School of Physics and Astronomy at Rochester Institute of Technology, Rochester, New York
My capstone research, “Cosmic Archeology: Examining the Structure of Galaxies Over Cosmic Time,” utilized JWST NIRCam near-infrared imaging from the COSMOS-Web treasury survey to examine the evolution of galaxy morphology at intermediate to high redshifts.
I performed multi-wavelength Sérsic profile fitting of the sources using Galfit and GalfitM; extracting morphological parameters including Sérsic indices, axis ratios, position angles, and flux radii. Additionally, I utilized MegaMorph’s GALAPAGOS2 to establish the framework for automating and parallelizing this fitting process on a high-performance computing cluster. This framework will facilitate the efficient analysis of large galaxy samples and contribute to a scalable pipeline for future morphological studies.