Quasars and Seyfert are two different types of AGNs. For example, quasars are more luminous than Seyferts. The term quasar or QSO is the abbreviation for “quasi-stellar object”, since these objects look like a star in the optical wavelengths.

The Clumpy dusty torus model

Spectral energy distribution fitting

We use near-infrared unresolved emission (orange point and green-arrow) and mid-infrared starburst-subtracted spectrum (in black) to model the dusty torus (image above right). The purple points are the extrapolations of the starburst-subtracted spectrum, which are in agreement with the predictions. The model has six free parameters; the angular width, the radial extend, the number of clouds distributed along the equator, the index of the radial distribution (large values indicate a stepper distribution), the optical depth, and the viewing angle (orientation of the torus respect to the observer). We used a Bayesian statistical approach to constrain these parameters, which takes advantage of prior information on the parameters. In cases where we didn't have prior information on the parameters assumed a uniform distribution. In the image, above-left is the constrained global posterior distributions for each parameter. These distributions were combined by implementing a bootstrapping technique, allowing resampling of the individual posterior distributions.

We compared the global posterior distribution of QSOs with the ones obtained for Seyfert galaxies by Ichikawa et al. (2015). From a statistical comparison based on the KS- and Mann-Whitney- tests, we concluded that the dusty torus of quasars is intrinsically different from the dusty torus in Seyfert. Indeed, a recent study (Martinez-Paredes et al., 2021) suggests that the geometry that better describes the infrared data of QSOs includes a hot dust component. However, a deeper study on the dust composition is necessary to better understand the properties of the dust. The coming Mid -Infrared Instrument and near-Infrared Camera on the James Webb Space Telescope will offer better-infrared data that will allow a depth study on dust properties.