The Blast Wave Model for AGN Feedback: Effects on AGN Obscuration
N. Menci (1), F. Fiore (1), S. Puccetti (1,2), A. Cavaliere (3)((1), INAF, Osservatorio Astronomico di Roma; (2) ASI SDC; (3) Dip. Fisica, Universita' Roma Tor Vergata)

TL;DR
This paper presents a physical model for AGN feedback using blast waves, predicting how galactic absorption affects AGN obscuration and its evolution with redshift and luminosity, aligning with some observed trends.
Contribution
The study introduces a semi-analytic model incorporating blast wave feedback to explain AGN obscuration and its dependence on luminosity and redshift, matching several observational patterns.
Findings
The model reproduces the observed AGN 'downsizing' behavior for z<2.
It predicts a higher abundance of Compton-thick AGNs at z>2.
The absorbed fraction decreases with luminosity at z<1 and increases with redshift up to z~2.
Abstract
We compute the effect of the galactic absorption on AGN emission in a cosmological context by including a physical model for AGN feeding and feedback in a semi-analytic model of galaxy formation. This is based on galaxy interactions as triggers for AGN accretion, and on expanding blast waves as a mechanism to propagate outwards the AGN energy injected into the interstellar medium at the center of galaxies. We first test our model against the observed number density of AGNs with different intrinsic luminosity as a function of redshift. The model yields a ''downsizing'' behavior in close agreement with the observed one for z<2. At higher redshifts, the model predicts an overall abundance of AGNs (including Compton-thick sources) larger than the observed Compton-thin sources by a factor around 2 for z>2 and L_X < 10^{44} erg/s. Thus, we expect that at such luminosities and redshifts about…
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.
