Bibcode
Esparza-Arredondo, D.; González-Martín, O.; Dultzin, D.; Ramos Almeida, C.; García-Lorenzo, B.; Alonso-Herrero, A.; García-Bernete, I.; Masegosa, J.
Bibliographical reference
Astronomy and Astrophysics
Advertised on:
6
2025
Journal
Citations
0
Refereed citations
0
Description
Context. Over ten mid-infrared (mid-IR) and X-ray models are currently attempting to describe the nuclear obscuring material of active galactic nuclei (AGNs), but many questions remain unresolved. Aims. This study aims to determine the physical parameters of the obscuring material in nearby AGNs and explore their relationship with nuclear activity. Methods. We selected 24 nearby Seyfert AGNs with X-ray luminosities ranging from 1041 to 1044 erg/s‑1, using NuSTAR and Spitzer spectra. Our team fit the spectra using a simultaneous fitting technique. Then, we compared the resulting parameters with AGN properties, such as the bolometric luminosity, accretion rate, and black hole mass. Results. Our analysis shows that dust and gas share a similar structure in most AGNs. Approximately 70% of the sample favor a combination of the X-ray UXClumpy torus model with the Clumpy and Two-Phases torus models at IR wavelengths. We found that linking the half-opening angle and torus angular width parameters from X-ray and mid-IR models helps to constrain other parameters and break degeneracies. The study reveals that Sy1 galaxies are characterized by low covering factors, half-opening angles, and column densities but high Eddington rates. In contrast, Sy2 galaxies display higher covering factors and column densities, with a broader range of half-opening angles. We also observed that the distribution of obscuring material is closer to the nucleus in intermediate-luminosity sources, while it is more extended in more luminous AGNs. Conclusions. Our findings reinforce the connection between the properties of gas-dust material within 10 pc and AGN activity. Applying this methodology to a larger sample and incorporating data from facilities such as JWST and XRISM will be crucial in further refining these results.