Seyfert and Quasars
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.
Above is the optical image of the quasar 3C273 located at 2.5 billion light-years. At the bottom is the optical image of the Seyfert galaxy NGC 7674 located at 400 million light-years. Images Credits:ESA/Hubble & NASA
The Clumpy dusty torus model
Schematic representation of the clumpy dusty torus model.
The dust in the torus absorbs the optical/UV emission emitted in the accretion disk and re-emit it in the IR between 1 and 1000 um, peaking at mid-IR around 20-30 um. Therefore, IR wavelengths offers an ideal spectral range to study the properties of the dusty torus. I used the mid-IR camera CanariCam (CC) installed on the 10.4m Gran Telescopio CANARIAS (GTC) to observe (image and spectroscopy) at N-band ( 7 - 14 m) a sample of 20 nearby (z<0.1) Quasi Stellar Objects (QSOs). The goal was to characterize the physical (e.g., optical depth) and geometrical (e.g., orientation) properties of the putative dusty torus, assuming the dusty CLUMPY torus model of Nenkova et al. (2002, 2008a,b). The CLUMPY torus model of Nenkova et al. (2002, 2008a, 2008b) assumes a toroidal distribution of clumpy dust. According to this model, the classification of an AGN in type 1 or 2 is not a matter of the torus’s orientation but of the probability that a photon emitted in the central engine can escape through the LOS without being absorbed by a cloud.
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.
Assuming the dusty torus model of Nenkova et al. (2008) we found that the dusty torus in QSOs is intrinsically different from the torus in Seyfert
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.
The infrared spectral energy distribution of QSOs is better modeled by the Disk+Wind model proposed by Hoenig et al. (2017).
Summary of my research on the nuclear dust in QSOs
A talk that summaries my work on the nuclear dust in QSOs in 10 minutes!
ESO_IR_MP.pdf