Galaxy formation and evolution

Abstract:

Spatially resolved stellar kinematics has become a key ingredient in time-delay cosmography to break the mass-sheet degeneracy in the mass profile and in turn provide a precise constraint on the Hubble constant and other cosmological parameters. In this paper, we present the first measurements of 2D resolved stellar kinematics for the lens galaxy in the quadruply lensed quasar system łensname using integral field spectroscopy from JWST's Near-Infrared Spectrograph (NIRSpec), marking the first such measurement conducted with JWST. In extracting robust kinematic measurements from this first-of-its-kind dataset, we have made methodological improvements both in the data reduction and kinematic extraction. In our kinematic extraction procedure, we performed joint modeling of the lens galaxy, the quasar, and its host galaxy's contributions in the spectra to deblend the lens galaxy component and robustly constrain its stellar kinematics. Our improved methodological frameworks are released as software pipelines for future use: squirrel , for extracting stellar kinematics, and , for JWST-NIRSpec data reduction. We incorporated additional artifact cleaning beyond the standard JWST pipeline. We compared our measured stellar kinematics from the JWST NIRSpec with previously obtained ground-based measurements from the Keck Cosmic Web Imager integral field unit and find that the two datasets are statistically consistent at a ∼1.1σ confidence level. Our measured kinematics will be used in a future study to improve the precision of the Hubble constant measurement. RegalJumper

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.

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.

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.