Electronic Theses and Dissertations

Mason Ruby

Date

2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Physics

Committee Chair

Francisco Muller-Sanchez

Committee Member

Benjamin Keller

Committee Member

Joseph Mazzarella

Committee Member

Xiao Shen

Abstract

While super massive black holes (SMBHs) are known to exist at the center of all massive galaxies, we have yet to understand the processes by which gas flows from kpc scales to within pcs of the SMBH, thereby accreting and triggering an active galactic nucleus (AGN). Additionally, while AGN-driven feedback in the form of kpc-scale winds and jets is induced to explain the observed excess quenching of star-formation, the mechanisms of AGN-driven feedback and its relevance compared to star-formation-driven feedback are not well understood. AGN feeding and feedback are instrumental to SMBH-galaxy coevolution, and determining the processes involved is imperative for understanding how SMBHs have grown throughout cosmic history, the regulation of star formation, the incidence of AGN in the local universe, and the population of supermassive black hole binaries (SMBHBs) that can emit gravitational waves observable by gravitational wave experiments such as NANOGrav and LISA. Therefore, I present an analysis of the drivers of AGN fueling and the mechanisms involved in AGN feedback to better understand the SMBH-galaxy connection. Markarian 266 (a galaxy merger containing dual AGN) is studied via high-resolution integral field unit (IFU) spectroscopy assisted with adaptive optics (AO), enabling a characterization of mechanisms driving AGN fueling at sub-kpc scales and an AGN-driven outflow in the southwest nucleus. The same techniques are applied to AGN in the isolated galaxies NGC 4388 and NGC 4151, revealing a helical outflow in NGC 4388 possibly driven by a SMBHB and a molecular gas torus in NGC 4151. To provide further context, machine learning techniques are applied to the NASA/IPAC Extragalactic Database Local Volume Sample (NED LVS) to detect AGN, enabling a more complete estimation of the AGN fraction in the local universe. Additionally, NED LVS AGN are used to evaluate the completeness of traditional AGN detection methods at infrared and optical wavelengths (WISE colors and optical emission line diagnostics). These methods are then used to characterize both known AGN and the AGN candidates predicted by machine learning models. Results suggest that the local AGN fraction may be as high as 20% and that many AGN are undetected by WISE colors and emission line diagnostics due to obscuration.

Comments

Data is provided by the student

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Open Access

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