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Discovering the Missing Population of AGN Pairs with Chandra

dc.contributor.authorFoord, Adi
dc.date.accessioned2020-10-04T23:34:49Z
dc.date.availableNO_RESTRICTION
dc.date.available2020-10-04T23:34:49Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/2027.42/163194
dc.description.abstractAlthough the first supermassive black hole (SMBH) was observed over 100 years ago, the details regarding how they form, evolve, and impact their surroundings remain active topics of research. In fact, only over the past 5 years has the existence of black holes been confirmed via the advent of detectors such as the Advanced Laser Interferometer Gravitational Wave Observatory (LIGO) and the Event Horizon Telescope (EHT). From an observational perspective, although all massive galaxies are thought to harbor nuclear SMBHs, the observability is dependent on the accretion activity. The activity of accreting SMBHs, or Active Galactic Nuclei (AGN), is expected to evolve with time and is likely a function of the ability to efficiently channel gas inflow to the galactic center. Many black hole feeding mechanisms exist, such as gravitational instabilities in galaxies that are barred or nucleated, gas dynamic processes involving multiple black holes, and major galaxy interactions. To further complicate the matter, it is possible that more than one mechanism plays a role at any given time. However, analyzing which SMBHs are active, and why, is vital to understanding various feedback processes and how the growth of a SMBH and its host galaxy are tied. In this dissertation, I present various analyses that are all focused on studying the activity of SMBHs in various environments. Specifically, I have studied a population of AGN in nucleated galaxies to analyze how nuclear star clusters affect SMBH activity (Chapter 2), and a binary AGN candidate (two SMBHs that are gravitationally bound; Chapter 3) that did not appear to be undergoing any major merger. However, the majority of my dissertation focuses on detecting and analyzing AGN pairs, (``dual AGN", if the SMBHs are not yet gravitationally bound). Despite the importance of dual AGN to wide-ranging astrophysical fields such as galaxy formation and gravitational waves, the rate of dual AGN has yet to be accurately measured. Yet, the rate of dual AGN can inform us of the role galaxy mergers play in triggering AGN, timescales for post-merger SMBHs to sink to the center of the potential well, as well as merger-related feedback physics. Dual AGN that are widely separated relative to the instrument PSF and have near unity flux ratios are easy to identify, however dual AGN with small separations and/or flux ratios can only be distinguished from a single AGN with advanced statistical analysis. As a result, very few dual AGN have been confirmed. Thus, I've developed a tool called BAYMAX (Bayesian Analysis of Multiple AGN in X-rays), that quantitatively evaluates whether a given source in a Chandra observation is composed of a single or multiple point sources, using a Bayesian framework. With BAYMAX, I am methodically expanding the known population of multiple AGN systems (Chapters 5 and 6), while learning more about their preferential environments via multi-wavelength (Optical, IR, and X-ray) analyses.
dc.language.isoen_US
dc.subjectX-ray Astronomy
dc.subjectSupermassive Black Hole
dc.subjectGalaxy Mergers
dc.subjectActive Galactic Nuclei
dc.titleDiscovering the Missing Population of AGN Pairs with Chandra
dc.typeThesis
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineAstronomy and Astrophysics
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberGultekin, Kayhan
dc.contributor.committeememberMcKay, Timothy A
dc.contributor.committeememberComerford, Julia M
dc.contributor.committeememberGallo, Elena
dc.contributor.committeememberHodges-Kluck, Edmund
dc.contributor.committeememberMiller, Jon Matthew
dc.subject.hlbsecondlevelAstronomy
dc.subject.hlbsecondlevelPhysics
dc.subject.hlbsecondlevelStatistics and Numeric Data
dc.subject.hlbtoplevelScience
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/163194/1/foord_1.pdfen_US
dc.identifier.orcid0000-0002-1616-1701
dc.identifier.name-orcidFoord, Adi; 0000-0002-1616-1701en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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