Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates

Abstract We examine the demographics of radio-emitting active galactic nuclei (AGN) in the local Universe as a function of host galaxy properties, most notably both stellar mass ( M ⋆ ) and star formation rate (SFR). Radio AGN activity is theoretically implicated in helping reduce the SFR of galaxies, and therefore it is natural to investigate the relationship between these two galaxy properties. We use the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) optical IFU catalog in conjunction with the NVSS and Faint Images of the Radio Sky at Twenty radio catalogs. MaNGA's high precision determinations of SFR allow us to impose a clean cut to reliably identify radio AGN from star formers. Using this sample of AGN, the well-measured stellar velocity dispersions from MaNGA, and the black hole M – σ relationship, we examine the Eddington ratio distribution (ERD) and its dependence on M ⋆ and SFR. We find that the ERD depends strongly on M ⋆ , with more massive galaxies having larger Eddington ratios ( λ ). Interpreting our model fit to the data leads to a completeness-corrected estimate of F AGN ( λ &gt; 0.001), the fraction of galaxies with radio AGN with λ &gt; 0.001. At <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mfenced close=")" open="("> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⋆</mml:mo> </mml:mrow> </mml:msub> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:mrow> </mml:mfenced> <mml:mo>∼</mml:mo> <mml:mn>11</mml:mn> </mml:math> , we estimate F AGN = 0.02. The AGN fraction increases rapidly with M ⋆ , and at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mfenced close=")" open="("> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⋆</mml:mo> </mml:mrow> </mml:msub> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:mrow> </mml:mfenced> <mml:mo>∼</mml:mo> <mml:mn>12</mml:mn> </mml:math> , we estimate F AGN ∼ 0.24. We do not find any dependence on SFR, specific star formation rate, or velocity dispersion when controlling for stellar mass. We conclude that galaxy SFRs appear to be unrelated to the presence or absence of a radio AGN, which may be useful in constraining theoretical models of AGN feedback.

Authors

Publication Details

Journal
The Astrophysical Journal
Published
2024-12-01
DOI
https://doi.org/10.3847/1538-4357/ad8ac7
Citations
5
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
1.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates

Michael R. Blanton, Arjun Suresh
5 citations
The Astrophysical Journal
Galaxies: Formation, Evolution, Phenomena
1.66
article

Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates

Michael R. Blanton, Arjun Suresh
article en
5 citations

Abstract

Abstract We examine the demographics of radio-emitting active galactic nuclei (AGN) in the local Universe as a function of host galaxy properties, most notably both stellar mass ( M ⋆ ) and star formation rate (SFR). Radio AGN activity is theoretically implicated in helping reduce the SFR of galaxies, and therefore it is natural to investigate the relationship between these two galaxy properties. We use the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) optical IFU catalog in conjunction with the NVSS and Faint Images of the Radio Sky at Twenty radio catalogs. MaNGA's high precision determinations of SFR allow us to impose a clean cut to reliably identify radio AGN from star formers. Using this sample of AGN, the well-measured stellar velocity dispersions from MaNGA, and the black hole M – σ relationship, we examine the Eddington ratio distribution (ERD) and its dependence on M ⋆ and SFR. We find that the ERD depends strongly on M ⋆ , with more massive galaxies having larger Eddington ratios ( λ ). Interpreting our model fit to the data leads to a completeness-corrected estimate of F AGN ( λ &gt; 0.001), the fraction of galaxies with radio AGN with λ &gt; 0.001. At <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mfenced close=")" open="("> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⋆</mml:mo> </mml:mrow> </mml:msub> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:mrow> </mml:mfenced> <mml:mo>∼</mml:mo> <mml:mn>11</mml:mn> </mml:math> , we estimate F AGN = 0.02. The AGN fraction increases rapidly with M ⋆ , and at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>log</mml:mi> <mml:mfenced close=")" open="("> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⋆</mml:mo> </mml:mrow> </mml:msub> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:mrow> </mml:mfenced> <mml:mo>∼</mml:mo> <mml:mn>12</mml:mn> </mml:math> , we estimate F AGN ∼ 0.24. We do not find any dependence on SFR, specific star formation rate, or velocity dispersion when controlling for stellar mass. We conclude that galaxy SFRs appear to be unrelated to the presence or absence of a radio AGN, which may be useful in constraining theoretical models of AGN feedback.

The Astrophysical JournalVol. 977(2)
Openalex Percentile: Top 16%
Galaxies: Formation, Evolution, Phenomena
1.66
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.