AGN-driven galactic outflows: comparing models to observations

TL;DR

This study compares models of AGN-driven galactic outflows with observations, finding that radiation pressure feedback can explain the observed outflow properties and scaling relations, supporting its role alongside wind models.

Contribution

It provides the first quantitative comparison of radiation pressure-driven models with observational data, demonstrating their ability to reproduce outflow dynamics and energetics.

Findings

Radiation pressure models match observed outflow energetics.

Scaling relations of outflows align with AGN luminosity.

Sources with ultra-fast and molecular outflows occupy a specific region in the $N_ ext{H} - \\lambda$ plane.

Abstract

The actual mechanism(s) powering galactic outflows in active galactic nuclei (AGN) is still a matter of debate. At least two physical models have been considered in the literature: wind shocks and radiation pressure on dust. Here we provide a first quantitative comparison of the AGN radiative feedback scenario with observations of galactic outflows. We directly compare our radiation pressure-driven shell models with the observational data from the most recent compilation of molecular outflows on galactic scales. We show that the observed dynamics and energetics of galactic outflows can be reproduced by AGN radiative feedback, with the inclusion of radiation trapping and/or luminosity evolution. The predicted scalings of the outflow energetics with AGN luminosity can also quantitatively account for the observational scaling relations. Furthermore, sources with both ultra-fast and molecular outflow detections are found to be located in the `forbidden' region of the $N_\mathrm{H} - \lambda$ plane. Overall, an encouraging agreement is obtained over a wide range of AGN and host galaxy parameters. We discuss our results in the context of recent observational findings and numerical simulations. In conclusion, AGN radiative feedback is a promising mechanism for driving galactic outflows that should be considered, alongside wind feedback, in the interpretation of future observational data.