The GLEAM 4-Jy (G4Jy) Sample: V. Broadband spectral analysis

Sarah V. White; Siegfried A. Gawenda; Giulia Macario; Samuel P. Hansen; Ross J. Turner; Thomas M. O. Franzen; Joseph R. Callingham; Randall Wayth; Kshitij Thorat

arXiv · 2610.27171

The GLEAM 4-Jy (G4Jy) Sample: V. Broadband spectral analysis

Sarah V. White·Siegfried A. Gawenda·Giulia Macario·Samuel P. Hansen·Ross J. Turner·Thomas M. O. Franzen·Joseph R. Callingham·Randall Wayth·Kshitij Thorat

View original source ↗Read source document ↗Export metadata ↓

Abstract

The G4Jy Sample consists of 1,863 of the brightest sources in the southern sky, as selected at 151 MHz using the GaLactic and Extragalactic All-sky MWA (GLEAM) survey. We supplement existing, low-frequency radio data by completing visual inspection of radio images from the Rapid ASKAP Continuum Survey (RACS) at 887.5, 1367.5 and 1655.5 MHz. Doing so on a source-by-source basis allows us to assess the quality of the association of the radio emission, which we indicate via a flag system. Having multiple radio flux-densities allows us to construct broadband radio spectral energy distributions (SEDs), and these extend up to 20 GHz for sources that also have data from the Australia Telescope Compact Array (ATCA). We fit polynomial functions to these SEDs, and determine the distribution of sources that are best-fit by absorption models, these accounting for 11 per cent of the sample. The SEDs are further modelled using the Radio AGN in Semi-analytic Environments (RAiSE) framework, for three assumed density-profiles (set by typical halo masses of 10^12.5, 10^13.5, and 10^14.5 Msol). The derived source ages show the expected distribution in the radio-power--size (P--D) diagram, whilst derived jet powers show non-linear behaviour. The latter is believed to be the result of higher densities, associated with higher magnetic fields, restricting the expansion of the radio jets/lobes.

Explore related subjects

astro-ph.GA

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Sarah V. White, Siegfried A. Gawenda, Giulia Macario, Samuel P. Hansen, Ross J. Turner, Thomas M. O. Franzen, Joseph R. Callingham, Randall Wayth, Kshitij Thorat. 2026-10-19. The GLEAM 4-Jy (G4Jy) Sample: V. Broadband spectral analysis. https://arxiv.org/abs/2610.27171

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Environmental dependence of galaxy properties in the southern GAMA regions

Using data from the Galaxy and Mass Assembly (GAMA) survey, we investigate how galaxy properties correlate with the local environment, focusing on the two southern regions of the survey (G02 and G23) that have not previously been examined in this context. We employ two-point and marked correlation functions to quantify the environmental dependence of galaxy color, stellar mass, luminosity across the $u$, $g$, $r$, $J$, and $K$ bands, as well as star formation rate (SFR) and specific star formation rate (sSFR). We also assess the impact of redshift incompleteness and cosmic variance on these clustering measurements. Our results show that $u-r$ and $g-r$ colors are most strongly correlated with local overdensity, followed by stellar mass. The sSFR exhibits a clear inverse relationship with density of the environment, consistent with the trend observed for $u$-band luminosity, which traces young stellar populations. In contrast, galaxies brighter in the $g$, $J$, and $K$ bands preferentially inhabit denser regions. By comparing our measurements from the southern regions with those from the equatorial regions of GAMA, we find that cosmic variance does not significantly influence our conclusions. However, redshift incompleteness affects the clustering measurements, as revealed through comparisons of subsets within the G02 region. The measured correlations provide key constraints for models of galaxy assembly across mass and environment, while the environmental trends in color and near-infrared luminosity offer a means to trace stellar mass growth and quenching with redshift.

astro-ph.GA↗

arXiv2026

Dark matter density profiles of the Milky Way satellite population: reconciling simulations and observations

The cusp-core problem remains a key challenge for the $Λ$CDM model. Historically, comparing inner dark matter halo slopes ($d\logρ/d\log r$) from simulations and observations has suffered from a methodological mismatch: evaluating slopes at different radii creates apparent tensions due to inconsistent definitions rather than genuine physical differences. We rigorously compare dark matter density profiles of Milky Way (MW) dwarf satellites inferred from dynamical modelling against CDM hydrodynamical simulations. Using the NIHAO and FIRE-2 suites ($M_{\star} \sim 10^3$-$10^{11}\,\rm M_\odot$), we confront simulated profiles with dynamical inferences of 16 MW satellites across four methods, strictly within their reliability limits. Crucially, we evaluate simulated slopes at observationally accessible radii, directly comparing profiles at matched stellar mass. Both observed and simulated galaxies exhibit a mass-dependent core-formation trend: inner slopes rise from cuspy values ($\approx -1.5$) at $M_{\star} \sim 10^5\,\rm M_\odot$ to core-like values ($\approx 0$ to $-0.4$) at $M_{\star} \sim 10^8\,\rm M_\odot$. Efficient core formation begins at $M_{\star} \gtrsim 10^6\,\rm M_\odot$ for centrals, where satellites display increased scatter consistent with tidal disruption. Simulated profiles agree with observations within $\lesssim 1σ$ for most systems, outperforming a NFW profile. Furthermore, differing observational models present scatter for a given system comparable to the simulation-to-observation offset. Evaluating dark matter density slopes at fixed physical radii significantly improves agreement between hydrodynamical simulations and dynamical models, revealing no clear tension when comparing profiles at fixed stellar mass, but Willman\,1 remains an unresolved outlier.

astro-ph.GA↗

arXiv2026

Tighter Dark Matter Constraints from the Projected Mass Method: A Neural Network Enhanced Method for Galaxy Groups and Clusters

Measuring the total mass of the Milky Way and nearby galaxy groups is difficult because classical dynamical estimators rely on assumptions about satellite orbital geometry that are rarely satisfied in practice, and because only a handful of satellite galaxies are typically available as kinematic tracers. We present a new framework that corrects the well-known Projected Mass Estimator (PME) using a residual neural network trained on thousands of simulated galaxy groups from the IllustrisTNG cosmological simulation. Separate networks are trained for each satellite sample size, from as few as 5 satellites up to 50, so that the correction automatically accounts for the statistical noise that dominates when only a small number of tracers is available. In tests on simulated halos, the classical PME systematically overestimates halo masses by factors of $M_{\rm proj}/M_{\rm true} = 1.30^{+0.72}_{-0.62}$ (using the 2D distance) and $1.46^{+0.97}_{-0.72}$ (using the 3D distance), with RMSE of 0.29 and 0.32 dex respectively. The neural-network correction reduces this to $M_{\rm proj}/M_{\rm true} = 1.02^{+0.30}_{-0.26}$ with an RMSE of 0.13 dex. Applied to the Milky Way, the method yields a total mass of $M_{\rm MW} = 1.144^{+0.399}_{-0.296}\times10^{12}\,M_\odot$, with estimates based on the brightest 5-10 satellites favoring a somewhat lower range of $(0.8-0.95)\times10^{12}\,M_\odot$. The modified PME gives a tighter constraint on the virial masses and the inferred dark matter content of galaxy groups and clusters.

astro-ph.GA↗