Simple Stellar Population Modeling of Quasar Host Galaxies with Diffusion K-Means Test Results

Type Conference Paper
Names Gregory Mosby, E. A. Moravec, C. A. Tremonti, M. J. Wolf
Proceedings Title Bulletin of the American Astronomical Society
Conference Name AAS Meeting #221, #339.41
Volume 221
Date January 1, 2013
Library Catalog
Abstract In the last decade, the correlation of the masses of supermassive black holes (SMBHs) and their host galaxy stellar spheroid velocity dispersions (the M-sigma relation) was greeted as clear evidence for the co-evolution of host galaxies and their SMBHs. However, studies in the last five years have posited that this relation could arise from central-limit properties of hierarchical formation alone. To address the question of whether and how often the SMBHs evolve with their host galaxies, it is necessary to look at galaxies whose SMBHs are actively growing—quasars—and determine the host galaxy properties. The central nuclei of quasar host galaxies complicate this type of study because their high luminosity tends to wash out their host galaxies. But, by using 3-D spectroscopy with the integral field unit (IFU) Sparsepak on the WIYN telescope, we have shown that the quasar light can be mostly isolated to one fiber in order to obtain the spectra of the quasar and the host galaxy concurrently. We can then model simultaneously the scattered quasar light and the stellar populations in the host galaxy fiber using a new simple stellar population (SSP) modeling method called diffusion k-means (DFK). The objectives of the research presented in this poster are to model synthetic quasar host galaxies using a DFK basis and a more traditional basis, compare the accuracy of both modeling methods, and test the affects of various prescriptions for masking the quasar lines in the host galaxy fiber. We present results from our SSP modeling and Markov Chain Monte Carlo (MCMC) results for DFK and traditional modeling schemes using synthetic data. By determining and then using the more robust stellar population modeling method, we can more confidently study quasar host galaxies to answer remaining questions in galaxy evolution. This work was partially supported by a National Science Foundation Graduate Fellowship (NSF Grant DGE-0718123) and through the NSF's REU program (NSF Award AST-1004881).
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