Detailed Characterization of H_beta emission line profile in low z SDSS quasars
S. Zamfir (1), J. W. Sulentic (1,2), P. Marziani (3), D. Dultzin (4), ((1) Univ. of Alabama, Tuscaloosa, USA; (2) Instituto de Astrofisica de, Andalucia, Granada, Spain; (3) INAF-Osservatorio Astronomico di Padova,, Italy; (4) Instituto de Astronomia, UNAM, Mexico City, Mexico)

TL;DR
This study characterizes the H_beta emission line profiles in low-redshift SDSS quasars, revealing two main populations with distinct spectral and physical properties, and suggests refinements to quasar classification within the 4DE1 parameter space.
Contribution
It provides a detailed analysis of H_beta line profiles in low-z quasars, supporting the two-population framework and proposing new spectral diagnostics for quasar classification.
Findings
Population A quasars have Lorentzian H_beta profiles.
Population B quasars show double Gaussian H_beta profiles.
Distinct black hole mass and Eddington ratio distributions for the two populations.
Abstract
We explore the properties of the H_beta emission line profile in a large, homogeneous and bright sample of N~470 low redshift quasars extracted from Sloan Digital Sky Survey (DR5). We approach the investigation from two complementary directions: composite/median spectra and a set of line diagnostic measures (asymmetry index, centroid shift and kurtosis) in individual quasars. The project is developed and presented in the framework of the so-called 4D Eigenvector 1 (4DE1) Parameter Space, with a focus on its optical dimensions, FWHM(H_beta) and the relative strength of optical FeII (R_FeII=W(FeII4434-4684)/W(H_beta)). We reenforce the conclusion that not all quasars are alike and spectroscopically they do not distribute randomly about an average typical optical spectrum. Our results give further support to the concept of two populations A and B (narrower and broader than 4000 km/s…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
