Kavli Affiliate: John D. Silverman
| First 5 Authors: Wenke Ren, Hengxiao Guo, Yue Shen, John D. Silverman, Colin J. Burke
| Summary:
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 which improves the precision and
effectiveness of the decomposition process. Specifically, we have reduced the
degeneracy and over-fitting in AGN-host decomposition, particularly for those
with low signal-to-noise ratios (SNR), where traditional methods tend to fail.
By applying our method to 76,565 SDSS Data Release 16 quasars with $z<0.8$, we
achieve a success rate of $approx$ 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 ($M_{rm BH}$). Furthermore, we obtained stellar
velocity dispersion ($sigma_*$) measurements for 4,137 quasars. The slope of
the $M_{rm BH}-sigma_*$ 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.
| Search Query: ArXiv Query: search_query=au:”John D. Silverman”&id_list=&start=0&max_results=3