Galaxy formation and evolution

Abstract:

We use the full-disk Very Large Telescope/MUSE mosaic of NGC 253 to identify 2492 H ii regions and study their resolved structure. With an average physical resolution of 17 pc, this is one of the largest samples of highly resolved spectrally mapped extragalactic H ii regions. Regions of all luminosities exhibit a characteristic emission profile described by a double Gaussian with a marginally resolved or unresolved core with radius < 10 pc surrounded by a more extended halo of emission with radius = 20–30 pc. Approximately 80% of the emission of a region originates from the halo component. As a result of this compact structure, the luminosity–radius relations for core and effective radii of H ii regions depend sensitively on the adopted methodology. Only the isophotal radius yields a robust relationship in NGC 253, but this measurement has an ambiguous physical meaning. We invert the measured emission profiles to infer density profiles and find central densities of ne ≈ 10–100 cm−3. In the brightest regions, these agree well with densities inferred from the [S ii] λλ6716, 6730 doublet. The central density of H ii regions correlates well with the surface brightness within the effective radius. We show that this same scaling relation applies to the recent MUSE + Hubble Space Telescope catalog for 19 nearby galaxies. We also discuss potential limitations, including completeness, impacts of background subtraction and spatial resolution, and the generality of our results when applied to other galaxies.

Abstract:

Current spatially resolved kinematic measurements of supermassive black hole (SMBH) masses are largely confined to the local Universe (distances ≲ 100 Mpc). We investigate the potential of the Extremely Large Telescope’s (ELT) first-light instruments, MICADO and HARMONI, to extend these dynamical measurements to galaxies at redshift 1 ≲ z ≲ 2. We select a sample of five bright, massive, quiescent galaxies at these redshifts, adopting their Sérsic profiles, from HST photometry, as their intrinsic surface brightness distributions. Based on these intrinsic models, we generate mock MICADO images using SimCADO and mock HARMONI integral-field spectroscopic data cubes using hsim. The HARMONI simulations utilize input stellar kinematics derived from Jeans Anisotropic Models (JAM). We then process these mock observations: the simulated MICADO images are fitted with Multi-Gaussian Expansion (MGE) to derive stellar mass models, and stellar kinematics are extracted from mock HARMONI cubes with pPXF. Finally, these derived stellar mass models and kinematics are used to constrain JAM dynamical models within a Bayesian framework. Our analysis demonstrates that SMBH masses can be recovered with an accuracy of ∼10 %. We find that MICADO can provide detailed stellar mass models with ∼1 hour of on-source exposure. HARMONI requires longer minimum integrations for reliable stellar kinematic measurements of SMBHs. The required on-source time scales with apparent brightness, ranging from 5–7.5 hours for galaxies at z ≈ 1 (F814W, 20–20.5 mag) to 5 hours for galaxies at 1 < z ≲ 2 (F160W, 20.8 mag). These findings highlight the ELT’s capability to push the frontier of SMBH mass measurements to z ≈ 2, enabling crucial tests of SMBH-galaxy co-evolution at the top end of the galaxies mass function.

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 . 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.