The S-PLUS Fornax Project (S+FP): An extragalactic catalog covering $\sim$ 5 virial radii around NGC 1399 with galaxy properties

TL;DR

The paper introduces the S-PLUS Fornax Project (S+FP), a wide-field extragalactic catalog covering ~208 deg^2 around NGC 1399 to ~5 $R_{vir}$ in RA and ~3 $R_{vir}$ in Dec, built from 12-band S-PLUS photometry with UV and IR supplements. It develops supervised learning pipelines to remove spurious detections and to perform star/galaxy separation, delivering a clean catalog of 119,580 galaxies with derived photometric redshifts $z_{phot}$ (NMAD ~ $2.1\times10^{-2}$) and physical properties (stellar mass, SFR, $D4000_{N}$) via ML trained on SDSS data, plus 350 new Fornax-member candidates using a lower redshift limit $z_{lim}\sim0.03$. The catalog also identifies 181 ELG candidates, 158 eROSITA clusters, and assesses completeness via mock light-cones, yielding ~72% completeness for $g\le19.5$ and $0.01\le z_{spec}\le1.0$, demonstrating robust tracing of large-scale structure in the Fornax region. These results enable detailed environmental and structure studies and set up a framework for extending the analysis to the Eridanus-Fornax-Doradus filament. The dataset, with 493 catalog columns, provides a rich resource for cosmology and galaxy evolution investigations in a key nearby region.

Abstract

Observational extragalactic catalogs over wide sky areas are essential for uncovering the large-scale structure of the Universe. They allow, among others, cosmological studies and density analyses that impose strong constraints on models of galaxy formation and evolution. By taking advantage of the wide field images and the 12 optical bands of the Southern Photometric Local Universe Survey (S-PLUS), we aim at providing a catalog of galaxies located, in projection, towards the Fornax galaxy cluster, within $\sim$ 5 virial radii in right ascension (R.A.) and $\sim$ 3 virial radius in declination (Dec) around NGC,1399, the dominant galaxy of the cluster. Such a catalog will allow unprecedented large-scale structure studies in that sky region. Supervised deep learning algorithms have been developed, utilizing neural networks complemented with dimensionality reduction techniques, to classify and separate spurious objects, stars and galaxies in a photometric catalog previously built for the S-PLUS Fornax Project (S+FP). That catalog was built using a combination of SExtractor configurations optimized for galaxy detection and characterization. A catalog of 119,580 galaxies was obtained in the direction of the Fornax cluster containing photometric information in the 12 optical bands of S-PLUS complemented with GALEX (UV), VHS-VISTA (NIR) and AllWISE (MIR) data. We estimate photometric redshifts (σ_ NMAD $\sim$ 0.0219) with a lower limit of z_ lim $\sim$ 0.03. Stellar masses, star formation rates (SFRs) and D4000_N index estimates were obtained through a machine learning approach, by matching S-PLUS photometric data to SDSS spectroscopic data. The completeness of the catalog (72%) was calculated by comparing with mock catalogs ...

Figures (18)

• Figure 1: Definition of two categories of spurious objects: those detected close to the spikes of saturated star and those accumulated at the edges of the images.
• Figure 2: Confusion matrix for the separation of spurious and non-spurious objects for the test sample (20$\%$). On the vertical axis we show the true source labels and on the horizontal axis, the predicted labels. N represents the number of sources per label.
• Figure 3: Confusion matrix of the PCA model, the one with the highest accuracy and F1-score. N represents the number of sources per label and the quantities shown correspond to the test sample (20$\%$) of the training sample.
• Figure 4: From left to right, the panels show the evolution of the spatial distribution of objects, from the catalog by Haack2024(left panel) to the final S+FP extragalactic catalog (right panel) (see text for details).
• Figure 5: Histogram of g-band AUTO magnitudes and the choice of photometric depth at 19.5 mag. The distributions correspond to three S/N thresholds (S/N > 3, blue; S/N > 10, red; and S/N > 20, green).