A New Framework for Active Galactic Nucleus Accretion and Jet Feedback in Numerical Simulations

Abstract Accurate modeling of active galactic nucleus (AGN) feedback, especially due to relativistic jets, is crucial for understanding the cool-core problem in galaxy clusters. We present a new subgrid method to model accretion onto and feedback from AGN in hydrodynamical simulations of galaxy clusters. Instead of applying the traditional Bondi formalism, we use a sink particle algorithm in which the accretion flux is measured directly through a control surface. A weighting kernel is used to reset the gas properties within the accretion radius at the end of each time step. We implement feedback in the form of bipolar jets whose properties are tied to the accretion rate. The method is tested with a spherically symmetric Bondi gas flow problem and a Bondi–Hoyle–Lyttleton wind problem, with and without jet feedback. We discuss the reliability of this model by comparing our jet simulations with those in the literature, and we examine the dependence of test results on parameters such as the resolution and size of the jet injection region. We find that the sink particle model can account for the α factor in accretion measurement, and the accretion radius must be resolved with at least two zones to produce realistic black hole accretion. We also show how underresolving the AGN feedback region in simulations can impact the feedback energy deposited and the jet dynamics. The code described here is the framework for a feedback model, described in a companion paper, that will use accretion disk modeling to more self-consistently determine the feedback efficiency.

Authors

Publication Details

Journal
The Astrophysical Journal Supplement Series
Published
2025-04-01
DOI
https://doi.org/10.3847/1538-4365/adb963
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A New Framework for Active Galactic Nucleus Accretion and Jet Feedback in Numerical Simulations

P. M. Ricker, Ying-He Celeste 映荷 Lü 吕
1 links
The Astrophysical Journal Supplement Series
Galaxies: Formation, Evolution, Phenomena
article

A New Framework for Active Galactic Nucleus Accretion and Jet Feedback in Numerical Simulations

P. M. Ricker, Ying-He Celeste 映荷 Lü 吕
article en

Abstract

Abstract Accurate modeling of active galactic nucleus (AGN) feedback, especially due to relativistic jets, is crucial for understanding the cool-core problem in galaxy clusters. We present a new subgrid method to model accretion onto and feedback from AGN in hydrodynamical simulations of galaxy clusters. Instead of applying the traditional Bondi formalism, we use a sink particle algorithm in which the accretion flux is measured directly through a control surface. A weighting kernel is used to reset the gas properties within the accretion radius at the end of each time step. We implement feedback in the form of bipolar jets whose properties are tied to the accretion rate. The method is tested with a spherically symmetric Bondi gas flow problem and a Bondi–Hoyle–Lyttleton wind problem, with and without jet feedback. We discuss the reliability of this model by comparing our jet simulations with those in the literature, and we examine the dependence of test results on parameters such as the resolution and size of the jet injection region. We find that the sink particle model can account for the α factor in accretion measurement, and the accretion radius must be resolved with at least two zones to produce realistic black hole accretion. We also show how underresolving the AGN feedback region in simulations can impact the feedback energy deposited and the jet dynamics. The code described here is the framework for a feedback model, described in a companion paper, that will use accretion disk modeling to more self-consistently determine the feedback efficiency.

The Astrophysical Journal Supplement SeriesVol. 277(2)
Openalex Percentile: Top 95%
Galaxies: Formation, Evolution, Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.