Date of Graduation


Document Type


Degree Type



Eberly College of Arts and Sciences


Physics and Astronomy

Committee Chair

Sarah Burke-Spolaor

Committee Co-Chair

Maura McLaughlin

Committee Member

Maura McLaughlin

Committee Member

Kathryn Williamson

Committee Member

Jenny Greene


Supermassive black hole binaries (SMBHBs) can lurk, often unseen, in the centers of post-merger galaxies, and pulsar timing arrays (PTAs) are rapidly approaching the sensitivities required to detect nanohertz gravitational waves (GWs) from these giant pairs. Independently, numerous electromagnetic surveys are seeking evidence of these dynamic duos’ effects on their host galaxies by searching for periodicities in time-domain observations. Combining these two methods to use multi-messenger techniques allows us to learn more about these binaries than using one messenger alone. In this thesis, we have created Bayesian methods to search for SMBHBs using electromagnetic observations of quasars and through GW emission in PTA data.

By using electromagnetic observations to identify an SMBHB candidate, we gain numerous pieces of information that also define the source's GW emission, including the location of and distance to the SMBHB's host galaxy and the orbital period of the SMBHB. In our study, we developed the first multi-messenger techniques used by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav), and applied them to a well-known supermassive black hole binary candidate, 3C 66B. We placed the lowest chirp mass limit to date on an SMBHB within 3C 66B of M

Next, we analyzed the capabilities of Bayesian methods to search for electromagnetic signatures of these binaries in simulated time-domain data sets from next-generation surveys. We developed a Bayesian model selection technique to identify periodicities induced into a quasar light curve by the orbital motion of an SMBHB from within intrinsic red noise. We discovered that future surveys, such as the Legacy Survey of Space and Time (LSST), will identify more robust SMBHB candidates than current surveys, such as the Catalina Real-time Transient Survey (CRTS).

Finally, we present the results of searches for bright continuous GWs (CWs) from individual SMBHBs in NANOGrav's 12.5-year data set. A red noise process, which could be the first signs of an emerging stochastic GW background (GWB), was previously detected for the first time in this data set. In our work, we searched for CWs alongside this common noise process for the first time in real PTA data, and developed necessary data-handling techniques which will be critical for the detection of a CW, which may come soon after the potentially imminent detection of the GWB.