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Compact groups (CGs) of galaxies are extreme environments for morphological transformations and the cessation of star formation. Our objective is to understand the dynamics of CGs and how their surrounding environment impacts galaxy properties. We selected a sample of 340 CGs in the Stripe 82 region, totaling 1083 galaxies, and a control sample of 2281 field galaxies. We find that at least 27\% of our sample of CGs are part of major structures, i.e. non-isolated CGs. We find a bimodality in the effective radius ($R_e$)-S\'ersic index ($n$) plane for all transition galaxies (those with $(u-r) > 2.3$ and $n<2.5$) in CGs. Additionally, transition galaxies in isolated CGs populate more densely the $R_e-n$ plane for $n < 1.75$. In contrast, transition galaxies in non-isolated CGs have smoothly increasing $n$ values, suggesting these galaxies have already suffered morphological transformation, and primarily contribute to the distribution of more compact galaxies in the $R_e-n$ plane for all transition galaxies in CGs. We also find significant differences in the specific star-formation rate (sSFR) distribution between the late-type galaxies (LTGs) ($(u-r)<2.3$ and $n< 2.5$) in non-isolated CGs and the same type of galaxies in the control sample, suggesting that the evolution of LTGs differs in non-isolated CGs. Early-type galaxies ($(u-r)>2.3$ and $n>2.5$) and transition galaxies in non-isolated CGs have lower sSFR values and a higher fraction of quenched galaxies, compared to those in isolated CGs. Based on our results, we propose an evolutionary scenario where the major structures in which the CGs are embedded accelerate the morphological transformations of their members. Our findings highlight the importance of considering the larger structures in which CGs may be located, when analysing the properties of their galaxy, as this can significantly affect the evolution of CGs and their galaxies., Comment: Submitted to A&A, 13 pages, 9 figures

The Fornax galaxy cluster is the richest nearby (D ~ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of oportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow- and broad-bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV ~ 1.4 x 1.4 deg$^2$) observed in five SDSS-like ugriz broad-bands and seven narrow-bands covering specific spectroscopic features like [OII], CaII H+K, H$\delta$, G-band, Mg b triplet, H$\alpha$, and the CaII triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our dataset provides the community with catalogues containing homogeneous 12-band photometry for ~ 3 x 10$^6$ resolved and unresolved objects within a region extending over ~ 208 deg$^2$ (~ 5 Rvir in RA) around Fornax' central galaxy, NGC 1399. We further explore the EAGLE and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M$\star \geq 10^8$ M$\odot$. The S+FP dataset we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented., Comment: 25 pages, 30 figures, accepted for publication in MNRAS

In this paper we present CALSAGOS: Clustering ALgorithmS Applied to Galaxies in Overdense Systems which is a PYTHON package developed to select cluster members and to search, find, and identify substructures. CALSAGOS is based on clustering algorithms and was developed to be used in spectroscopic and photometric samples. To test the performance of CALSAGOS we use the S-PLUS's mock catalogues and we found an error of 1\% - 6\% on member selection depending on the function that is used. Besides, CALSAGOS has a $F_1$-score of 0.8, a precision of 85\% and a completeness of 100\% in the identification of substructures in the outer regions of galaxy clusters ($r > r_{200}$). The $F_1$-score, precision and completeness of CALSAGOS fall to 0.5, 75\% and 40\% when we consider all substructure identifications (inner and outer) due to the function that searches, finds, and identifies the substructures works in 2D and cannot resolve the substructures projected over others., Comment: 13 pages, 6 figures