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C. López Sanjuan

Publications and source records attributed to C. López Sanjuan.

2 recordsLinked to original sources

J-PLUS: The planetary nebula population of M 33

In this pilot study, we investigate the PN population in M~33, a nearby spiral galaxy ($\simeq 840$~kpc), using data from the DR3 of the Javalambre-Photometric Local Universe Survey (J-PLUS), a 12-band photometric dataset extensively used to identify H$α$ line emitters. From the 143 known PNe of M~33, the photometry of only 13 are present in the J-PLUS catalog, as available on the J-PLUS portal. With the aim of recovering a larger fraction of the M~33 PN population, the software SExtractor is adopted to extract the sources in the J-PLUS images and obtain the photometric data for the PNe known in the literature, performing PSF photometry when possible. With this procedure the photometry of 98 PNe was obtained using H$α$ image as detection image, including the 13 already present in the J-PLUS catalog. Using diagnostic color-color diagrams (DCCDs) based on criteria developed for Milky Way halo PNe, we identified 16 sources with PN-like colors. Cross-match with existing catalogs revealed that most of these candidates are H II regions, though one source remains unidentified. Additionally, analyzing their full width at half maximum, most of them would not be PN candidates. This highlights the method's ability to select emission-line objects but also underscores the challenge of distinguishing PNe from contaminants using photometry alone. The J-PLUS colors of 98 known PNe were analyzed, together with literature information on their radial velocities, resulting in the identification of one possible halo PN. This is the first paper which aims at detecting extragalactic PNe in multi-band surveys such as J-PLUS, the Southern Local Universe Survey (S-PLUS) and the Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS), paving the way for similar studies in these surveys for other nearby galaxies, which lack catalogs of known PNe.

astro-ph.GA↗

J-PAS: A Neural Network Approach to Single Stellar Population Characterization

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 revolutionize galaxy evolution studies by observing $\sim$10$^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 combine 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 is trained on synthetic J-PAS photometry from different SSP librares (E-MILES, Charlot & Bruzual, XSL), to enhance the robustness of our predictions against individual SSP model variations and limitations. To create mock samples with varying observed magnitudes we add artificial noise in the form of random Gaussian variations within typical observational uncertainties in each band. Our results indicate that the NN can accurately estimate stellar parameters for SSP models without evident degeneracies, surpassing a bayesian SED-fitting method on the same test set. We obtain median bias, scatter and 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 \sim$17 mag for age, metallicity and dust attenuation, respectively. The accuracy of the predictions is highly dependent on the signal-to-noise (S/N) ratio of the photometry, achieving robust predictions up to $i$ $\sim$ 20 mag.

astro-ph.GA↗