Efficient Long-range Active Galactic Nuclei (AGNs) Feedback Affects the Low-redshift Lyα Forest

Author:

Tillman Megan TaylorORCID,Burkhart BlakesleyORCID,Tonnesen StephanieORCID,Bird SimeonORCID,Bryan Greg L.ORCID,Anglés-Alcázar DanielORCID,Davé RomeelORCID,Genel ShyORCID

Abstract

Abstract Active galactic nuclei (AGNs) feedback models are generally calibrated to reproduce galaxy observables such as the stellar mass function and the bimodality in galaxy colors. We use variations of the AGN feedback implementations in the IllustrisTNG (TNG) and Simba cosmological hydrodynamic simulations to show that the low-redshift Lyα forest can provide constraints on the impact of AGN feedback. We show that TNG overpredicts the number density of absorbers at column densities N HI < 1014 cm−2 compared to data from the Cosmic Origins Spectrograph (in agreement with previous work), and we demonstrate explicitly that its kinetic feedback mode, which is primarily responsible for galaxy quenching, has a negligible impact on the column density distribution (CDD) of absorbers. In contrast, we show that the fiducial Simba model, which includes AGN jet feedback, is the preferred fit to the observed CDD of the z = 0.1 Lyα forest across 5 orders of magnitude in column density. We show that the Simba results with jets produce a quantitatively better fit to the observational data than the Simba results without jets, even when the ultraviolet background is left as a free parameter. AGN jets in Simba are high speed, collimated, weakly interacting with the interstellar medium (via brief hydrodynamic decoupling), and heated to the halo virial temperature. Collectively these properties result in stronger long-range impacts on the intergalactic medium when compared to TNG’s kinetic feedback mode, which drives isotropic winds with lower velocities at the galactic radius. Our results suggest that the low-redshift Lyα forest provides plausible evidence for long-range AGN jet feedback.

Funder

National Aeronautics and Space Administration

National Science Foundation

Chandra X-ray Observatory

Simons Foundation

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

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1. FLAME: Fitting Lyα absorption lines using machine learning;Astronomy & Astrophysics;2024-08

2. The effect of AGN feedback on the Lyman-α forest signature of galaxy protoclusters at z∼ 2.3;Monthly Notices of the Royal Astronomical Society;2024-07-27

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