Context. We present the full data set of the VIsible Multi-Object Spectrograph (VIMOS) spectroscopic campaign of the ESO/GOODS program in the Chandra Deep Field South (CDFS), which complements the FORS2 ESO/GOODS spectroscopic campaign. Aims. The ESO/GOODS spectroscopic programs are aimed at reaching signal-to-noise ratios adequate to measure redshifts for galaxies with AB magnitudes in the range ∼24−25 in the B and R band using VIMOS, and in the z band using FORS2. Methods. The GOODS/VIMOS spectroscopic campaign is structured in two separate surveys using two different VIMOS grisms. The VIMOS Low Resolution Blue (LR-Blue) and Medium Resolution (MR) orange grisms have been used to cover different redshift ranges. The LR-Blue campaign is aimed at observing galaxies mainly at 1.8 < z < 3.5, while the MR campaign mainly aims at galaxies at z < 1 and Lyman Break Galaxies (LBGs) at z > 3.5. Results. The full GOODS/VIMOS spectroscopic campaign consists of 20 VIMOS masks. This release adds 8 new masks to the previous release (12 masks, Popesso et al. 2009, A&A, 494, 443). In total we obtained 5052 spectra, 3634 from the 10 LR-Blue masks and 1418 from the 10 MR masks. A significant fraction of the extracted spectra comes from serendipitously observed sources: ∼21% in the LR-Blue and ∼16% in the MR masks. We obtained 2242 redshifts in the LR-Blue campaign and 976 in the MR campaign for a total success rate of 62% and 69% respectively, which increases to 66% and 73% if only primary targets are considered. The typical redshift uncertainty is estimated to be σ z 0.00084 (∼255 km s −1 ) for the LR-Blue grism and σ z 0.00040 (∼120 km s −1 ) for the MR grism. By complementing our VIMOS spectroscopic catalog with all existing spectroscopic redshifts publicly available in the CDFS, we compiled a redshift master catalog with 7332 entries, which we used to investigate large scale structures out to z 3.7. We produced stacked spectra of LBGs in a few bins of equivalent width (EW) of the Ly-α and found evidence for a lack of bright LBGs with high EW of the Ly-α. Finally, we obtained new redshifts for 12 X-ray sources of the CDFS and extended-CDFS. Conclusions. After the completion of the two complementary ESO/GOODS spectroscopic campaigns with VIMOS and FORS2 at VLT, the number of spectroscopic redshifts in CDFS/GOODS field increased dramatically, in particular at z > ∼ 2. These data provide the redshift information indispensable to achieve the scientific goals of GOODS, such as tracing the evolution of galaxy masses, morphologies, clustering, and star formation.

We present an analysis of star formation and quenching in the SDSS-IV MaNGA-DR15, utilising over 5 million spaxels from ∼3500 local galaxies. We estimate star formation rate surface densities (Σ SFR ) via dust corrected Hα flux where possible, and via an empirical relationship between specific star formation rate (sSFR) and the strength of the 4000Å break (D4000) in all other cases. We train a multi-layered artificial neural network (ANN) and a random forest (RF) to classify spaxels into 'star forming' and 'quenched' categories given various individual (and groups of) parameters. We find that global parameters (pertaining to the galaxy as a whole) perform collectively the best at predicting when spaxels will be quenched, and are substantially superior to local/ spatially resolved and environmental parameters. Central velocity dispersion is the best single parameter for predicting quenching in central galaxies. We interpret this observational fact as a probable consequence of the total integrated energy from AGN feedback being traced by the mass of the black hole, which is well known to correlate strongly with central velocity dispersion. Additionally, we train both an ANN and RF to estimate Σ SFR values directly via regression in star forming regions. Local/ spatially resolved parameters are collectively the most predictive at estimating Σ SFR in these analyses, with stellar mass surface density at the spaxel location (Σ * ) being by far the best single parameter. Thus, quenching is fundamentally a global process but star formation is governed locally by processes within each spaxel.

We investigate how star formation quenching proceeds within central and satellite galaxies using spatially resolved spectroscopy from the SDSS-IV MaNGA DR15. We adopt a complete sample of star formation rate surface densities (ΣSFR), derived in Bluck et al. (2020), to compute the distance at which each spaxel resides from the resolved star forming main sequence (ΣSFR − Σ* relation): ΔΣSFR. We study galaxy radial profiles in ΔΣSFR, and luminosity weighted stellar age (AgeL), split by a variety of intrinsic and environmental parameters. Via several statistical analyses, we establish that the quenching of central galaxies is governed by intrinsic parameters, with central velocity dispersion (σc) being the most important single parameter. High mass satellites quench in a very similar manner to centrals. Conversely, low mass satellite quenching is governed primarily by environmental parameters, with local galaxy over-density (δ5) being the most important single parameter. Utilising the empirical MBH - σc relation, we estimate that quenching via AGN feedback must occur at MBH ≥ 106.5 − 7.5M⊙, and is marked by steeply rising ΔΣSFR radial profiles in the green valley, indicating ‘inside-out’ quenching. On the other hand, environmental quenching occurs at over-densities of 10 - 30 times the average galaxy density at z∼0.1, and is marked by steeply declining ΔΣSFR profiles, indicating ‘outside-in’ quenching. Finally, through an analysis of stellar metallicities, we conclude that both intrinsic and environmental quenching must incorporate significant starvation of gas supply.

We present a novel technique for ranking the relative importance of galaxy properties in the process of quenching star formation. Specifically, we develop an artificial neural network (ANN) approach for pattern recognition and apply it to a population of over 400,000 central galaxies taken from the Sloan Digital Sky Survey Data Release 7. We utilise a variety of physical galaxy properties for training the pattern recognition algorithm to recognise star forming and passive systems, for a 'training set' of ∼100,000 galaxies. We then apply the ANN model to a 'verification set' of ∼100,000 different galaxies, randomly chosen from the remaining sample. The success rate of each parameter singly, and in conjunction with other parameters, is taken as an indication of how important the parameters are to the process(es) of central galaxy quenching. We find that central velocity dispersion, bulge mass and B/T are excellent predictors of the passive state of the system, indicating that properties related to the central mass of the galaxy are most closely linked to the cessation of star formation. Larger scale galaxy properties (total or disk stellar masses), or those linked to environment (halo masses or δ 5 ) perform significantly less well. Our results are plausibly explained by AGN feedback driving the quenching of central galaxies, although we discuss other possibilities as well.