College - Author 1

College of Science and Mathematics

Department - Author 1

Physics Department

Degree Name - Author 1

BS in Physics



Primary Advisor

Vardha Bennert, College of Science and Math, Physics Department


Supermassive Black Holes (SMBHs) can be found in the center of almost every galaxy, and in some cases, can form Active Galactic Nuclei (AGNs). AGNs are some of the brightest objects in our observable Universe and are distinguished from quiescent galaxies by accretion onto the central SMBH, which forms a disk where the luminosity is produced. Reverberation mapping (RM) of broad-line AGNs determines the mass of the SMBH by resolving the gravitational sphere of influence of the BH ``in time". In this study, GALFIT is used to fit 2D analytic functions to existing Hubble Space Telescope (HST) images for 23 RM AGNs. The goal is to extract morphological information of the host galaxies, such as spheroid luminosity and size, as well as disk and bar luminosity (if present). Ultimately, when combined with the SMBH mass determined from RM, all 23 RM AGNs will be placed on the BH mass - host-galaxy scaling relations to study dependencies on host galaxy morphology.

Out of 23 galaxies, eight are best fit by a PSF and Sersic component only. The other 15 are spiral galaxies and found to be best fit with additional components, where ten are modeled with PSF, bulge, and disk components, and the other five are modeled with an additional bar component. For the 15 spiral host galaxies, the best fit is compared to a single-sersic model to study the difference in derived parameters. The comparison confirms that a single-sersic component best matches the disk of a multi-sersic model, confirming the procedure taken to model spiral host galaxies.

In building up scaling relations, researchers often encounter high-redshift objects or low resolution data of host galaxies, where components such as a disk cannot be resolved. The frequent strategy for these objects is to fit them with a single-sersic model. By comparing the different modeling approaches, this thesis provides recipes to adjust derived values (such as magnitude, radius, and Sersic index), quantifying uncertainties due to single-sersic fits.