Prior-informed Active Galactic Nucleus Host Spectral Decomposition Using PyQSOFit

Abstract

We introduce an improved method for decomposing the emission of active galactic nuclei (AGN) and their host galaxies using templates from principal component analysis (PCA). This approach integrates prior information from PCA with a penalized pixel fitting mechanism that improves the precision and effectiveness of the decomposition process. Specifically, we have reduced the degeneracy and overfitting in AGN host decomposition, particularly for those with low signal-to-noise ratios (SNRs), where traditional methods tend to fail. By applying our method to 76,565 Sloan Digital Sky Survey Data Release 16 quasars with z < 0.8, we achieve a success rate of ≈94%, thus establishing the largest host-decomposed spectral catalog of quasars to date. Our fitting results consider the impact of the host galaxy on the overestimation of the AGN luminosity and black hole mass ( M _BH ). Furthermore, we obtained stellar velocity dispersion ( σ _⋆ ) measurements for 4137 quasars. The slope of the M _BH − σ _⋆ relation in this subsample is generally consistent with previous quasar studies beyond the local Universe. Our method provides a robust and efficient approach to disentangle the AGN and host galaxy components across a wide range of SNRs and redshifts.

Keywords

• AGN host galaxies
• Astronomy data analysis
• Active galactic nuclei
• Quasars