Paula Coelho

Aims. We aim at deriving stellar atmospheric parameters based on the photometric data from the Javalambre Photometric Local Universe Survey (J-PLUS) in addition to near-infrared photometry from the Two Micron All-Sky Survey (2MASS). Methods. Our method consists of a semi-supervised machine learning approach based on the k-means method combined with a modified K-nearest neighbors algorithm. This method compares the observed photometry to a set of reference data to estimate the stellar effective temperature ( T _eff ), surface gravity (log g ), and metallicity ([Fe/H]) of stars from J-PLUS Data Release 3 (DR3). For that, a set of 105 colors was constructed using extinction-corrected photometric data from J-PLUS DR3 and 2MASS. The reference dataset used was composed by the MESA Isochrones & Stellar Tracks (MIST) models, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), and the Apache Point Observatory Galactic Evolution Experiment (APOGEE) surveys. Results. We estimate T _eff , log g , and [Fe/H], for approximately 5.6 million stars from J-PLUS DR3, along with their errors. Our results were in agreement with the spectroscopic estimates of LAMOST and APOGEE. We also applied a dimension reduction method, seeking greater efficiency by reducing the computation time and minimizing the information needed to calculate the stellar parameters, resulting in a subset of 11 colors. From this approach, stellar parameters were obtained for approximately six million stars, increasing the number of studied objects. The results obtained were of the same order, despite having slightly higher uncertainties compared to those obtained with 105 colors. Conclusions. Our results demonstrate the potential of using a method built from machine learning algorithms that does not require prior training. Additionally, we show that the proposed method allows the estimation of reliable atmospheric parameters even when the available photometry did not fulfill all the photometric quality criteria. As part of our method, we define a neighborhood parameter, which assesses the reliability of our estimates and indicates that objects with smaller neighborhood values have lower uncertainties.

Stellar populations in the central regions of disc galaxies provide key constraints on their formation and secular evolution. We investigate the properties of young stellar populations in the centres of nearby barred galaxies from the TIMER survey, using four stellar population models, two based on empirical stellar libraries (MILES and X-Shooter) and two on theoretical libraries (Starburst99 and HR-pyPopStar), complemented by independent gas-phase metallicities from emission-line diagnostics. The inferred stellar metallicities depend strongly on the adopted model. Measured as the 5th–95th percentile spread across the three galaxies analysed in detail, the empirical libraries recover variations of 1.11 and 0.98 dex, whereas the theoretical ones return 0.40 and 0.49 dex; the gas in the same regions spans 0.49 dex. Gas metallicities are indeed lower in the central star-forming regions, but the amplitude of that depression (about 0.3 dex in NGC 1097) exceeds what bar-driven inflow of disc gas can account for, given typical abundance gradients in literature. The age–metallicity relations consistently reveal two distinct components; an older population consistent with a self-enrichment scenario, and a younger population formed from gas inflows with a different chemical enrichment history. The empirical libraries produce a monotonic decline of metallicities from old to young populations, which would require a sustained inflow of metal-poor gas outpacing its own enrichment. The theoretical libraries instead recover a young component whose metallicity departs from the older populations only at the most recent ages and by a few tenths of a dex, compatible with a single dilution episode. Our results demonstrate that model choice critically affects inferred metallicities, with models based on empirical stellar libraries recovering age–metallicity relations that demand physical conditions the gas measurements cannot sustain.

There is vast evidence from observations of multiple stellar populations (MPs) in globular clusters (GCs). To explore the issue theoretically, this work considers two subsolar metallicities, two ages, and two initial abundance patterns: a first population of standard α -enhanced metal mixture stars and a second stellar population displaying C-N and Na-O anticorrelations chemical abundance patterns, along with an enhanced helium fraction. Analysing the predictions for these extreme compositions, we provide insights into the observability of not-resolved MPs into individual stars of GCs. We use colours and spectrophotometric indices measurable with modern facilities (e.g. Euclid , LSST, DES, JWST).

This talk presents a systematic review of stellar spectral libraries (SSLs) and their evolution in astronomical research, with a focus on their role in stellar population studies. Through a literature search covering publications from 1899 to 2024, we trace the development of SSLs from early photographic surveys to modern high-resolution digital collections. We examine the current state-of-the-art in both observational and synthetic libraries, discussing their relative strengths and impacts on the field. The review highlights how technological advances expand the capabilities of libraries, and it discusses future perspectives with upcoming facilities and the challenges of managing increasingly large datasets.

Spectroscopic and photometric studies have encountered evidence of multiple populations of stars in Galactic Globular Clusters. Anti-correlated C-N and O-Na abundance patterns in subsequent generations of cluster stars present new challenges to the fields of stellar nucleosynthesis and cluster evolution. In order to study extragalactic clusters, we modeled the integrated light of stellar populations with these typical abundances patterns and identified spectral indices that are sensitive to the light element anti-correlations. We are currently expanding the previous work to cover a larger wavelength range, using the low metallicity stars of the X-shooter Stellar Library for validation. Preliminary results confirm that cool low-gravity stars are the most difficult to model and indicate a decreasing quality-of-fit towards lower metallicities. This trend might be related to recent literature reports of mismatches between spectroscopic and photometric determinations of atmospheric parameters of low-Z giants.

Using VLT/MUSE data, we study the ionised-gas kinematics in a mass- and volume-limited (M* ≥ 1010M⊙, D ≤ 20 Mpc) sample of 21 nearby galaxies to identify signatures of extended shocks within their inner kiloparsec, which appear as coherent velocity jumps in kinematic maps. By removing angular momentum, shocks in gas cause inflows, which can trigger nuclear star formation and fuel AGN activity. To identify the signatures of extended shocks, we examine residual velocity fields after subtracting a modelled rotating disc, and we study velocity difference between various gas tracers. Combining our kinematic analysis with BPT ionisation diagnostic maps and dust morphology, we find that 12 of 21 galaxies (~57 % show extended shock signatures with velocity jumps consistent with models of bar-driven shocks. This is likely a lower limit, as three additional galaxies (~14 %) exhibit shocks along bars, potentially reaching the nucleus but obscured by AGN outflows. We trace shock signatures inwards close to the resolution limit, which suggests that shocks may be the prevailing mechanism of inflow in the central kpc of galaxies. The only two unbarred galaxies in our sample are also the only systems with unperturbed kinematics and no shocks, strongly linking the perturbed gas dynamics in centres of galaxies to the presence of bars. All galaxies with inner bars show LINER- or Seyfert-like nuclear emission, whereas galaxies without inner bars exhibit all emission types, indicating that regardless of gas supply, inner bars suppress star formation in galactic nuclei.

We present SpectralUnmix , an R package for regularized non-negative matrix factorization (NMF), implemented in torch with optional GPU acceleration. The package estimates low-rank non-negative representations through proximal-gradient updates and allows smoothness regularization along the spectral axis. As a compact demonstration, we apply the method to a subset of stellar spectra and compare the recovered NMF components with principal-component directions and representative stellar spectra. The package is released under the MIT license at https://rafaelsdesouza.github.io/SpectralUnmix/ ; a copy has been deposited to Zenodo (R. S. de Souza 2026).

J-PAS (Javalambre Physics of the Accelerating Universe Astrophysical Survey) will present a groundbreaking photometric survey covering 8500 deg ² of the visible sky from Javalambre, capturing data in 56 narrow-band filters. This survey promises to revolutionise galaxy evolution studies by observing ∼10 ⁸ galaxies with low spectral resolution. A crucial aspect of this analysis involves predicting stellar population parameters from the observed galaxy photometry. In this study, we combined the exquisite J-PAS photometry with state-of-the-art single stellar population (SSP) libraries to accurately predict stellar age, metallicity, and dust attenuation with a neural network (NN) model. The NN was trained on synthetic J-PAS photometry from different SSP libraries (E-MILES, Charlot & Bruzual, and XSL) to enhance the robustness of our predictions against individual SSP model variations and limitations. To create mock samples with varying observed magnitudes, we added artificial noise in the form of random Gaussian variations within typical observational uncertainties in each band. Our results indicate that the NN was able to accurately estimate stellar parameters for SSP models without any evident degeneracies, surpassing a Bayesian SED-fitting method on the same test set. We obtained the median bias, scatter, and the percentage of outliers: μ = (0.01 dex, 0.00 dex, 0.00 mag), σ _NMAD = (0.23 dex, 0.29 dex, 0.04 mag), f _o = (17%, 24%, 1%) at i ∼ 17 mag for the age, metallicity and dust attenuation, respectively. The accuracy of the predictions is highly dependent on the signal-to-noise ratio (S/N) of the photometry, achieving robust predictions up to i ∼ 20 mag.

Context . Photometric surveys require precise point spread function (PSF) characterization, as the PSF varies across filters and plays a crucial role in achieving accurate photometry, particularly in low surface brightness (LSB) studies. Such studies include the analysis of faint and extended structures like galaxy halos, tidal features, diffuse circumgalactic emission, and intracluster light. However, the small PSF models produced by default data-reduction pipelines are optimized mainly for compact or barely resolved sources, which makes it challenging to analyze regions near bright stars, often rendering those areas unusable. Aims . We aim to demonstrate the feasibility of subtracting the extended PSF from each J-PLUS DR3 exposure prior to sky subtraction, an approach that has not yet been explored in wide surveys, and enable a comprehensive analysis of its behavior across detector position and time. Methods . To build an extended non-parametric PSF, we selected three different ranges of stars to create the central, middle, and outer regions in exposures within ~2.5 hours of the target. These components were then combined to generate a final PSF for each exposure and filter, spanning 15 mag arcsec ⁻² in surface brightness and 4 arcmin in radius in the broad bands. Results . In narrowband filters, the J-PLUS PSF exhibits two rings, whereas in broadband filters, only one ring is observed. Additionally, the position of the ring shifts with the filter wavelength in the following manner: as the filters become redder, the ring radius increases. We find that the precision of sky subtraction can be greatly improved with a PSF-subracted image, and out to a radius of 4 arcmin, there is no significant variation in the extended PSF observed as a function of time or position in the field of view. The radial profile of NGC 4212 (which is close to a star) is also studied before and after PSF subtraction as a demonstration of the effect. We developed a novel method to determine the central coordinates of saturated stars, and we classified stars without using Gaia magnitudes. Additionally, mirror reflections were automatically detected and masked. Furthermore, in combining different stars and various components of the PSF, we avoided the use of a fixed radius by introducing a new method that does not depend on radial measurements. Conclusions . Accurate characterization of the extended PSF and its subtraction improves sky subtraction, increases the effective area of the survey by about 10%, and enables the study of extended large LSB features in wide area surveys such as J-PLUS. Our pipeline is published as free software (GNU GPLv3), and it can be customized to suit other surveys such as J-PAS, where its impact will be even greater due to its depth. This paper is fully reproducible and produced from Commit 21523b8 .