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Radio-AGN activity across the galaxy population: dependence on stellar mass, star-formation rate, and redshift

T0 review · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Using LOFAR deep fields, the incidence of radio-loud AGN depends on both stellar mass and star-formation rate: quiescent-host LERGs follow a redshift-invariant steep mass relation, and lower-mass star-forming galaxies show up to 10 times higher LERG incidence.

desk verdict The quiescent-LERG and massive-galaxy results look solid, but the headline factor-of-10 enhancement of LERG activity in low-mass star-forming galaxies is not yet established because the radio-excess selection does not model contamination by star-forming galaxies. read the letter →

arxiv 2411.08104 v1 pith:PUHWNB2Z submitted 2024-11-12 astro-ph.GA astro-ph.HE

R. Kondapally , P. N. Best , K. J. Duncan , H. J. A. Röttgering , D. J. B. Smith , I. Prandoni , M. J. Hardcastle , T. Holc
show 11 more authors
A. L. Patrick M. I. Arnaudova B. Mingo R. K. Cochrane S. Das P. Haskell M. Magliocchetti K. Ma{l}ek G. K. Miley C. Tasse W. L. Williams
This is my paper · ORCID
classification astro-ph.GAastro-ph.HE
keywords galaxiesacrosslergsactivitygalaxydependencehergslerg
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Some galaxies host active galactic nuclei (AGN): supermassive black holes that swallow matter and sometimes shoot out powerful radio jets. These radio-loud AGN come in two flavours. Low-excitation radio galaxies (LERGs) are thought to be powered by hot gas falling onto the black hole at low rates. High-excitation radio galaxies (HERGs) are powered by colder gas at higher rates. This paper uses the deep LOFAR radio survey to ask: in which galaxies do these AGN switch on, and does that change with cosmic time?

The authors measured the fraction of galaxies hosting a LERG or HERG as a function of stellar mass, star-formation rate, and redshift, using about 540,000 galaxies and about 3,900 AGN above a fixed radio luminosity. The key results: in quiescent (non-star-forming) galaxies, the LERG fraction rises steeply with stellar mass and this relation does not change between redshift 0.3 and 1.5. In massive galaxies (above about 10^11 solar masses), the LERG fraction is about the same whether the galaxy is star-forming or quiescent. At lower masses, star-forming galaxies are up to 10 times more likely to host a LERG than quiescent galaxies, and this gap grows with redshift. HERGs, by contrast, are mostly found in star-forming galaxies at all redshifts.

These patterns are interpreted as evidence for two fuelling paths: hot halo gas powers LERGs in massive and quiescent galaxies, while cold gas provides an additional trigger in lower-mass star-forming galaxies. The authors are careful about uncertainties: the radio-excess selection used to find AGN is incomplete in strongly star-forming galaxies, and they apply Monte Carlo corrections. They also validate their LERG/HERG classification with stacked optical spectra and X-ray data.

Extended reading notes

Core claim

The load-bearing assertion is from the abstract: 'At lower masses, however, LERG activity is significantly more enhanced (by a factor of up to 10) in star-forming galaxies compared to quiescent galaxies,' combined with the claim that LERG activity in quiescent galaxies shows a steep stellar mass dependence 'with the same normalisation across the past ~10 Gyr.' If true, radio-loud AGN are fuelled by hot gas in massive/quiescent systems and by an additional cold-gas mechanism in lower-mass star-forming systems.

Load-bearing premise

The Monte Carlo completeness corrections for the radio-excess AGN selection (Sec. 2.3, Appendix A) assume a 0.3 dex Gaussian scatter in the radio luminosity-SFR relation and weight the simulated sample by the LERG luminosity functions of Kondapally et al. (2022) and Best et al. (2014), the authors' own prior fits. The claimed factor-of-10 enhancement of LERG activity in star-forming galaxies at low stellar mass comes from SFR bins where these corrections are largest (SFR > 10 Msun/yr). If the true scatter is larger, or the luminosity functions are not representative, the enhancement could be a selection artifact.

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Assumptions & free parameters 7 free parameters · 6 assumptions · 0 invented entities

The central claims rest on a chain of empirical calibrations inherited from prior work (radio-excess ridgeline, SED classification thresholds, main-sequence relation, BH mass and jet power scalings, completeness simulation scatter) rather than on new theoretical postulates. No new physical entities are introduced. The most consequential inherited ingredient is the completeness correction at high SFR, which directly supports the factor-of-10 enhancement claim.

free parameters (7)
  • Radio-excess ridgeline intercept and slope = 22.24, 1.08 (Best et al. 2023)
    Used to define the expected radio luminosity from star formation; sources 0.7 dex above this line are classified as radio-excess AGN. The central sample definition depends on this calibration.
  • Radio-excess threshold = 0.7 dex (about 3 sigma)
    Chosen in Best et al. 2023; sets the boundary between AGN and star-forming galaxies.
  • Main-sequence coefficients and bin offsets = SFR_MS coefficients (0.84, -0.026, -6.51, 0.11); offsets -1.3 and -0.4
    Speagle et al. 2014 relation with chosen offsets defines quiescent, intermediate, and star-forming galaxy bins.
  • Completeness simulation scatter = 0.3 dex
    Assumed Gaussian scatter in the radio luminosity-SFR relation for the Monte Carlo completeness corrections; drives the size of the high-SFR corrections.
  • Black hole mass scaling = MBH = 0.0014 M*
    Haring and Rix 2004 relation used to convert stellar mass to black hole mass for Eddington-scaled accretion rates.
  • Jet mechanical luminosity scaling = Lkin = 7e36 f_cav (L1.4/1e25)^0.68 W
    Cavagnolo et al. 2010 cavity scaling used to add jet power to Eddington rates.
  • SED classification thresholds = fAGN,16 > 0.06 (CIGALE), >0.1 in Boötes
    Thresholds from Best et al. 2023 that separate radiative-mode AGN (HERGs) from LERGs; small changes would move sources between populations.
assumptions (6)
  • domain assumption Flat LCDM cosmology with Omega_M=0.3, Omega_Lambda=0.7, H0=70
    Stated in Sec. 1; used for luminosity distances and volumes.
  • domain assumption Radio spectral index alpha = -0.7 (S_nu ~ nu^alpha)
    Assumed for k-corrections and converting 150 MHz to 1.4 GHz; uncertainty in alpha directly shifts luminosities and the effective luminosity limit.
  • domain assumption The radio-excess criterion identifies the radio-loud AGN population
    Sec. 2.2; all LERGs/HERGs are selected as sources more than 0.7 dex above the radio-SFR relation, with completeness corrections applied.
  • domain assumption SED-based LERG/HERG classification traces radiatively inefficient/efficient accretion
    Sec. 2.2 and Appendix B; validated on stacks, but source-by-source classification can be wrong in star-forming hosts.
  • domain assumption IRAC 3.6um-selected parent sample represents the underlying galaxy population
    Sec. 2.4; assumes F3.6>10 uJy with Duncan et al. mass completeness limits yields an unbiased denominator for fractions.
  • ad hoc to paper The Speagle et al. main sequence is the correct reference for defining quiescent/intermediate/star-forming
    Sec. 4; the offsets (-1.3, -0.4) are chosen by the authors to split the population; other definitions could change the enhancement factors.

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Pith. "Pith review of Radio-AGN activity across the galaxy population: dependence on stellar mass, star-formation rate, and redshift." pith.science (2026). https://pith.science/paper/PUHWNB2Z

@misc{pith2026241108104,
  author       = {Pith},
  title        = {Pith review of: Radio-AGN activity across the galaxy population: dependence on stellar mass, star-formation rate, and redshift},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/PUHWNB2Z}},
  note         = {Machine review of arXiv:2411.08104}
}
abstract

We characterise the co-evolution of radio-loud AGN and their galaxies by mapping the dependence of radio-loud AGN activity on stellar mass and star-formation rate (SFR) across cosmic time (out to $z \sim 1.5$). Deep LOFAR radio observations are combined with large galaxy samples to study the incidence of radio-loud AGN across the galaxy population; the AGN are further split into low-excitation radio galaxies (LERGs) and high-excitation radio galaxies (HERGs). We find that LERG activity occurs over a wide range of SFRs, whereas HERGs are typically found in galaxies with ongoing star formation. The LERGs are then split based on their SFRs relative to the main sequence, across redshift. Within quiescent galaxies, LERG activity shows a steep stellar mass dependence with the same normalisation across the past $\sim$ 10 Gyr; this indicates that hot gas fuels LERGs in quiescent galaxies across cosmic time. In massive galaxies ($\log_{10}(M/\rm{M_{\odot}}) \gtrsim 11$), the incidence of LERGs is roughly constant across the galaxy population, suggesting that LERGs in massive galaxies may be fuelled by hot gas regardless of the star-formation activity. At lower masses, however, LERG activity is significantly more enhanced (by a factor of up to 10) in star-forming galaxies compared to quiescent galaxies; this suggests that an additional fuelling mechanism, likely associated with cold gas, may fuel the LERGs in galaxies with higher SFRs. We find that HERGs typically accrete above 1 per cent of the Eddington-scaled accretion rate, and the LERGs typically accrete below this level.

Figures

Figures reproduced from arXiv: 2411.08104 by the authors.

Figure 1
Figure 1. The fraction of all galaxies that host a LERG (left) or a HERG (right) as a function of stellar mass across 0.3 < z ≤ 1.5 for a radio luminosity limit of L150MHz ≥ 1024 WHz−1 . The numbers of LERGs and HERGs satisfying the radio luminosity limit over this redshift range are also listed in each panel. The solid and dotted lines show the fractions obtained with and without the radio-luminosity – SFR completeness corre… view at source ↗
Figure 2
Figure 2. The fraction of galaxies that host a LERG (lower left) or a HERG (lower right) with L150MHz ≥ 1024 WHz−1 as a function of sSFR across 0.3 < z ≤ 1.5. To reduce any mass selection effects, we calculate the fractions for a constant stellar mass range of 10.8 < log10(M⋆/M⊙) ≤ 11.5 (see text) across the redshift bins. The solid and dotted lines show the results with and without the radio luminosity – SFR completeness cor… view at source ↗
Figure 3
Figure 3. The location of LERGs on the SFR-M⋆ plane in five redshift bins across 0.3 < z ≤ 1.5. The LERG sample has been split into the subset that are hosted by quiescent (red), intermediate (green), and star-forming (blue) galaxies, defined based on the evolving main-sequence (see Sec. 4). The diagonal dashed lines show the division lines used to select the three populations. The shaded contours show the distribution of the… view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: Fraction of quiescent (left), intermediate (middle), and star-forming (right) galaxies hosting a LERG with L150MHz ≥ 1024 WHz−1 as a function of their stellar mass across 0.3 < z ≤ 1.5. The host galaxy types for the LERGs are identified based on the offset from the evo…
Figure 5
Figure 5. Figure 5: The incidence of LERGs with L150MHz ≥ 1024 WHz−1 across redshift, with panels showing increasing stellar mass bins from left to right. In each panel, the incidences of LERGs are calculated within different galaxy types: quiescent (red), intermediate (green), and star-f…
Figure 6
Figure 6. Figure 6: The cumulative distribution of the Eddington-scaled accretion rates for the LERGs within different galaxy populations, and for the HERGs. The top panel shows the Eddington-scaled accretion rates derived by combining the bolometric radiative AGN luminosity estimated fro…

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    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.stat...

Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.