The viewing angle in AGN SED models, a data-driven analysis

TL;DR

This study evaluates the role of viewing angle in classifying Seyfert galaxies using SED modeling, finding it less effective than luminosity-based parameters and proposing X-CIGLE for AGN classification.

Contribution

The paper introduces a data-driven analysis of viewing angles in AGN SED models across a large sample, highlighting their limited discriminative power for Seyfert classification.

Findings

Viewing angle is better constrained in Type-1 AGNs.

Viewing angle does not significantly affect key physical parameters.

Luminosity-based measures can distinguish AGN types at low redshift.

Abstract

The validity of the unified active galactic nuclei (AGN) model has been challenged in the last decade, especially when different types of AGNs are considered to only differ in the viewing angle to the torus. We aim to assess the importance of the viewing angle in classifying different types of Seyfert galaxies in spectral energy distribution (SED) modelling. We retrieve photometric data from publicly available astronomical databases: CDS and NED, to model SEDs with X-CIGALE in a sample of 13 173 Seyfert galaxies located at redshift range from $z=0$ to $z=3.5$, with a median redshift of $z\approx0.2$. We assess whether the estimated viewing angle from the SED models reflects different Seyfert classifications. Two AGN models with either a smooth or clumpy torus structure are adopted in this paper. We find that the viewing angle in Type-1 AGNs is better constrained than in Type-2 AGNs. Limiting the viewing angles representing these two types of AGNs do not affect the physical parameter estimates such as star-formation rate (SFR) or AGN fractional contribution ($f_{\rm{AGN}}$). In addition, the viewing angle is not the most discriminating physical parameter to differentiate Seyfert types. We suggest that the observed and intrinsic AGN disc luminosity can: i) be used in $z<0.5$ studies to distinguish between Type-1 and Type-2 AGNs, and ii) explain the probable evolutionary path between these AGN types. Finally, we propose the use of X-CIGALE for AGN galaxy classification tasks. All data from the 13 173 SED fits are available at https://doi.org/10.5281/zenodo.5221764