Counting the Unseen
Black Hole Demographics in Low-Mass Galaxies: Improving Tidal Disruption Event Rate Estimations
Measuring massive black hole (MBH) demographics in low-mass galaxies provides a promising route toward constraining the different theoretical seeding mechanisms for MBHs. The advent of the Rubin Observatory (LSST) will allow tidal disruption events (TDEs) to be used in measuring MBH demographics. This measurement requires accurate TDE rate predictions. The current, widely used TDE rate estimates of Stone & Metzger (2016) do not account for stellar density components resulting from the presence of nuclear star clusters (NSCs). Due to the prevalence of NSCs in galaxies with masses between 10^8 and 10^10 M⊙ paired with the large enhancement in TDE rates caused by the presence of NSCs (Pfister et al. 2020), the rates of TDEs in these galaxies are determined by the density profiles of their NSCs. In this work, we are constructing the largest currently available set of high-resolution 3-D stellar density profiles of galaxies with NSCs. We are using these stellar density profiles to develop accurate relations between the stellar mass/type of galaxies and their central density profiles. We then combine these relations with realistic model galaxy distributions to create new loss-cone models and improve TDE rate estimates. With these estimates, we will predict the galaxy demographics of TDE hosts for ZTF and Rubin with a wide range MBH demographic scenarios.
Spatially Resolving the Star Formation Histories of Three Nearby Nuclear Star Clusters
The formation of nuclear star clusters (NSCs) remains an open question. In this work, we use spatially-resolved HST/STIS spectroscopic observations of three nearby NSCs (hosted by NGC 5102, NGC 5206, and NGC 205) to constrain their formation histories by exploring radial variations of the stellar populations within each cluster. Utilizing full-spectrum fitting, we find substantial age and metallicity gradients within the central 0.″9 (16 pc) of the NSC in NGC 5102 where populations near the center are young/metal-rich (age ~400 Myr and [M/H] ~ -0.4) and become older/metal-poor at larger radii (mean age ~1 Gyr and mean [M/H] ~ -1.6 in the radial range [0.″3, 0.″9]). This behavior suggests that the young/metal-rich population at the center was formed from a period of in situ formation, while the older/metal-poor populations were likely formed by inspiraled globular clusters. The two broad populations observed in the NGC 5102 NSC (young/metal-rich and old/metal-poor) appear to be linked to the transition between the two morphological components of the NSC derived from the surface-brightness profile in Nguyen et al. (2018). The radial ranges explored in NGC 5206 and NGC 205 were much smaller due to poor data quality; in NGC 5206 we find a similar metallicity gradient to NGC 5102 (but with much lower significance), while the data for NGC 205 is too poor to reach any conclusions. Overall, this data highlights the links between the morphological and stellar population complexity of NSCs and their formation mechanisms.
Optimizing Computations of Numerical Disk Models Constrained by H-alpha Emission Spectra
Classical Be stars are defined as rapidly rotating main-sequence high mass stars that form an outwardly diffusing, gaseous disk, which gives rise to emission in one, or more hydrogen Balmer lines. Variability associated with the emission from the disks of these stars has been observed on timescales ranging from less than a day to decades. Though rapid rotation is believed to contribute, the primary mechanism responsible for the growth, maintenance, and eventual dissipation of these disks remains unknown. Trends in Hydrogen-α (Hα) emission features such as equivalent width (EW) have been attributed to certain stages of disk variability. Numerical disk models capable of producing synthetic Hα emission profiles can be used with observational data to reveal time-dependent variations in the density and temperature structure of the circumstellar disks. This research addresses the primary challenge in determining the closest match between a model line profile and an observed spectrum. Because each synthetic spectrum is essentially a function of up to 6 free input parameters for the radiative transfer codes bedisk and beray, the task of finding the best matching synthetic spectrum reduces to a 6-dimensional nonlinear model fitting problem. The standard brute force approach to this problem is unrealistic as the computation time required to generate a fine grid of model spectra would surpass 550 years when conducting computations simultaneously on 1000 CPU cores. An optimization pipeline utilizing the Levenberg-Marquardt optimization algorithm has been developed in Interactive Data Language (IDL) to reduce computation time when searching for a synthetic spectrum that is in agreement with an observed spectrum. Although versions of this algorithm already exist in IDL, a custom version was needed to handle challenges specific to this research, such as bound and discrete model parameters. This pipeline will allow for rapid model fitting when studying variations in physical disk parameters through observed trends in Hα emission.