Investigating the influence of radio-faint active galactic nuclei on the infrared-radio correlation of massive galaxies
Astronomy & Astrophysics EDP Sciences 706 (2026) A111-A111
Abstract:
Context. It is well known that star-forming galaxies (SFGs) exhibit a tight correlation between their radio and infrared emissions, commonly referred to as the infrared-radio correlation (IRRC). Recent empirical studies have reported a dependence of the IRRC on the galaxy stellar mass, in which more massive galaxies tend to show lower infrared-to-radio ratios ( q IR ) with respect to less massive galaxies. One possible, yet unexplored, explanation is a residual contamination of the radio emission from active galactic nuclei (AGNs), not captured through “radio-excess” diagnostics. Aims. To investigate this hypothesis, we aim to statistically quantify the contribution of AGN emission to the radio luminosities of SFGs located within the scatter of the IRRC. Methods. Our Very Large Baseline Array (VLBA) AGN-sCAN program has targeted 500 galaxies that follow the q IR distribution of the IRRC, i.e., with no prior evidence for radio-excess AGN emission based on low-resolution (∼arcsec) VLA radio imaging. Our VLBA 1.4 GHz observations reach a 5 σ sensitivity limit of 25 μJy/beam, corresponding to a radio-brightness temperature of T b ∼ 10 5 K. This classification serves as a robust AGN diagnostic, regardless of the host galaxy’s star formation rate. Results. We detect four VLBA sources in the deepest regions, which are also the faintest VLBI-detected AGNs in SFGs to date. The effective AGN detection rate is 9%, when considering a control sample matched in mass and sensitivity, which is in good agreement with the extrapolation of previous radio AGN number counts. Despite the non-negligible AGN flux contamination (∼30%) in our individual VLBA detections, we find that the peak of the q IR distribution is completely unaffected by this correction. Although we cannot rule out a high incidence of radio-silent AGNs at (sub)μJy levels among the VLBA non-detections, we derive a conservative upper limit of < 0.1 dex of their cumulative impact on the q IR distribution. We conclude that residual AGN contamination from non-radio-excess AGNs is unlikely to be the primary driver of the M ★ – dependent IRRC.WISDOM Project – XXVII. Giant molecular clouds of the lenticular galaxy NGC 1387: similarities with spiral galaxy clouds
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2026) stag221
Abstract:
Abstract Molecular gas is crucial to understanding star formation and galaxy evolution, but the giant molecular clouds (GMCs) of early-type galaxies (ETGs) have rarely been studied. Here we present analyses of the spatially resolved GMCs of the lenticular galaxy NGC 1387, exploiting high spatial resolution (0″.15 or 14 pc) 12CO(2-1) line observations from the Atacama Large Millimeter/submillimeter Array. We identify 1285 individual GMCs and measure the fundamental properties (radius, velocity dispersion and molecular gas mass) of each with a modified version of the CPROPStoo package. Unusually for an ETG, the GMCs of NGC 1387 follow scaling relations very similar to those of the Milky Way disc and Local Group galaxy clouds, and most are virialised. GMCs with large masses and radii and/or small galactocentric distances have their angular momenta aligned with the large-scale galactic rotation, while other GMCs do not. These results show that ETGs have more diversified GMC properties than previously thought. We discuss potential reasons for such diversity, and viewing-angle dependency is a plausible candidate.A normalizing flow approach for the inference of star cluster properties from unresolved broadband photometry
Astronomy & Astrophysics EDP Sciences 706 (2026) a201
Abstract:
Context . Estimating properties of star clusters from unresolved broadband photometry is a challenging problem that is classically tackled using spectral energy distribution (SED) fitting methods that are based on simple stellar population models. However, grid-based methods suffer from computational limitations. Because of their exponential scaling, they can become intractable when the number of inference parameters grows. In addition, nuisance parameters in the model can make the computation of the likelihood function intractable. These limitations can be overcome by modern generative deep learning methods that offer flexible and powerful tools for modeling high-dimensional posterior distributions and fast inference from learned data. Aims . We present a normalizing flow approach for the inference of cluster age, mass, and reddening parameters from Hubble Space Telescope broadband photometry. In particular, we explore our network’s behavior when dealing with an inference problem that has been analyzed in previous works. Methods . We used the SED modeling code CIGALE to create a dataset of synthetic photometric observations for 5 × 10 6 mock star clusters. Subsequently, this dataset was used to train a coupling-based flow in the form of a conditional invertible neural network to predict posterior probability distributions for cluster age, mass, and reddening from photometric observations. Results . We predicted cluster parameters for the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) Data Release 3 catalog. To evaluate the capabilities of the network, we compared our results to the publicly available PHANGS estimates and found that the estimates agree reasonably well. Conclusions . We demonstrate that normalizing flow methods can be a viable tool for the inference of cluster parameters, and argue that this approach is especially useful when nuisance parameters make the computation of the likelihood intractable and in scenarios that require efficient density estimation.Duration and properties of the embedded phase of star formation in 37 nearby galaxies from PHANGS-JWST
Astronomy & Astrophysics EDP Sciences 706 (2026) a186
Abstract:
Light reprocessed by dust grains emitting in the infrared enables the study of the physics at play in dusty embedded regions, where ultraviolet and optical wavelengths are attenuated. Infrared telescopes such as JWST have made it possible to study the earliest feedback phases, when stars are shielded by cocoons of gas and dust. Comprehending this phase is crucial for unravelling the effects of feedback from young stars that leads to their emergence and the dispersal of their host molecular clouds. Here we show that the transition from the embedded to the exposed phase of star formation is short (< 4 Myr) and sometimes almost absent (< 1 Myr) across a sample of 37 nearby star-forming galaxies covering a wide range of morphologies, from massive barred spirals to irregular dwarfs. The short duration of the dust-clearing timescales suggests a predominant role of pre-supernova feedback mechanisms in revealing newborn stars, confirming previous results on smaller samples and allowing, for the first time, a statistical analysis of their dependencies. We find that the timescales associated with mid-infrared emission at 21 μm, tracing a dust-embedded feedback phase, are controlled by a complex interplay between giant molecular cloud properties (masses and velocity dispersions) and galaxy morphology. We report relatively longer durations of the embedded phase of star formation in barred spiral galaxies, while this phase is significantly reduced in low-mass irregular dwarf galaxies. We discuss tentative trends with gas-phase metallicity, which may favor faster cloud dispersal at low metallicities.When relics were made: vigorous stellar rotation and low dark matter content in the massive ultra-compact galaxy GS-9209 at z=4.66
Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2026) stag210