Large Sample Of Galaxies Research Articles

A Novel Method for Estimating the Ambient Medium Density Around Distant Radio Sources from Their Observed Radio Spectra

Abstract The dynamical evolution and radiative properties of luminous radio galaxies and quasars of the FR II type, are well understood. As a result, through the use of detailed modeling of the observed radio emission of such sources, one can estimate various physical parameters of the systems, including the density of the ambient medium into which the radio structure evolves. This, however, requires rather comprehensive observational information, i.e., sampling the broadband radio continua of the targets at several frequencies, and imaging their radio structures with high resolution. Such observations are, on the other hand, not always available, especially for high-redshift objects. Here, we analyze the best-fit values of the source physical parameters, derived from extensive modeling of the largest currently available sample of FR II radio sources, for which good-quality multiwavelength radio flux measurements could be collected. In the analyzed data set, we notice a significant and nonobvious correlation between the spectral index of the nonthermal radio emission continuum, and density of the ambient medium. We derive the corresponding correlation parameters, and quantify the intrinsic scatter by means of Bayesian analysis. We propose that the discovered correlation could be used as a cosmological tool to estimate the density of ambient medium for large samples of distant radio galaxies. Our method does not require any detailed modeling of individual sources, and relies on limited observational information, namely, the slope of the radio continuum between the rest-frame frequencies 0.4 and 5 GHz, possibly combined with the total linear size of the radio structure.

Lenses In VoicE (LIVE): searching for strong gravitational lenses in the VOICE@VST survey using convolutional neural networks

ABSTRACT We present a sample of 16 likely strong gravitational lenses identified in the VST Optical Imaging of the CDFS and ES1 fields (VOICE survey) using convolutional neural networks (CNNs). We train two different CNNs on composite images produced by superimposing simulated gravitational arcs on real Luminous Red Galaxies observed in VOICE. Specifically, the first CNN is trained on single-band images and more easily identifies systems with large Einstein radii, while the second one, trained on composite RGB images, is more accurate in retrieving systems with smaller Einstein radii. We apply both networks to real data from the VOICE survey, taking advantage of the high limiting magnitude (26.1 in the r band) and low PSF FWHM (0.8 arcsec in the r band) of this deep survey. We analyse ∼21 200 images with magr < 21.5, identifying 257 lens candidates. To retrieve a high-confidence sample and to assess the accuracy of our technique, nine of the authors perform a visual inspection. Roughly 75 per cent of the systems are classified as likely lenses by at least one of the authors. Finally, we assemble the LIVE sample (Lenses In VoicE) composed by the 16 systems passing the chosen grading threshold. Three of these candidates show likely lensing features when observed by the Hubble Space Telescope. This work represents a further confirmation of the ability of CNNs to inspect large samples of galaxies searching for gravitational lenses. These algorithms will be crucial to exploit the full scientific potential of forthcoming surveys with the Euclid satellite and the Vera Rubin Observatory.

A composite likelihood approach for inference under photometric redshift uncertainty

ABSTRACTObtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

Hyper Suprime-Cam Subaru Strategic Program: A Mass-dependent Slope of the Galaxy Size−Mass Relation at z < 1

Abstract We present the galaxy size−mass (R e –M *) distributions using a stellar mass complete sample of ∼1.5 million galaxies, covering ∼100 deg2, with log ( M * / M ⊙ ) > 10.2 ( 9.2 ) over the redshift range 0.2 < z < 1.0 (z < 0.6) from the second public data release of the Hyper Suprime-Cam Subaru Strategic Program. We confirm that, at fixed redshift and stellar mass over the range of log ( M * / M ⊙ ) < 11 , star-forming galaxies are on average larger than quiescent galaxies. The large sample of galaxies with accurate size measurements, thanks to the excellent imaging quality, also enables us to demonstrate that the R e –M * relations of both populations have a form of a broken power law, with a clear change of slopes at a pivot stellar mass M p . For quiescent galaxies, below an (evolving) pivot mass of log ( M p / M ⊙ ) = 10.2 – 10.6 , the relation follows R e ∝ M ∗ 0.1 ; above M p the relation is steeper and follows R e ∝ M * 0.6 – 0.7 . For star-forming galaxies, below log ( M p / M ⊙ ) ∼ 10.7 the relation follows R e ∝ M * 0.2 ; above M p the relation evolves with redshift and follows R e ∝ M * 0.3 – 0.6 . The shallow power-law slope for quiescent galaxies below M p indicates that large low-mass quiescent galaxies have sizes similar to those of their counterpart star-forming galaxies. We take this as evidence that large low-mass quiescent galaxies have been recently quenched (presumably through environment-specific processes) without significant structural transformation. Interestingly, the pivot stellar mass of the R e –M * relations for both populations also coincides with the mass at which half of the galaxy population is quiescent, implying that the pivot mass represents the transition of galaxy growth from being dominated by in situ star formation to being dominated by (dry) mergers.

A multimission catalogue of ultraluminous X-ray source candidates

ABSTRACT We present a new, multimission catalogue of ultraluminous X-ray source (ULX) candidates, based on recent data releases from each of the XMM–Newton, Swift, and Chandra observatories (the 4XMM-DR10, 2SXPS, and CSC2 catalogues, respectively). This has been compiled by cross-correlating each of these X-ray archives with a large sample of galaxies primarily drawn from the HyperLEDA archive. Significant efforts have been made to clean the sample of known non-ULX contaminants (e.g. foreground stars, background active galactic nuclei, supernovae), and also to identify ULX candidates that are common to the different X-ray catalogues utilized, allowing us to produce a combined ‘master’ list of unique sources. Our sample contains 1843 ULX candidates associated with 951 different host galaxies, making it the largest ULX catalogue compiled to date. Of these, 689 sources are catalogued as ULX candidates for the first time. Our primary motivation is to identify new sources of interest for detailed follow-up studies, and within our catalogue we have already found one new extreme ULX candidate that has high S/N data in the archive: NGC 3044 ULX1. This source has a peak luminosity of LX,peak ∼ 1040 erg s−1, and the XMM–Newton spectrum of the source while at this peak flux is very similar to other, better-studied extreme ULXs that are now understood to be local examples of super-Eddington accretion. This likely indicates that NGC 3044 ULX1 is another source accreting at super-Eddington rates. We expect that this catalogue will be a valuable resource for planning future observations of ULXs – both with our current and future X-ray facilities – to further improve our understanding of this enigmatic population.

X-Ray Constraints on the Hot Gas Content of Early-type Galaxies in Virgo

Abstract We present a systematic study of the diffuse hot gas around early-type galaxies (ETGs) residing in the Virgo cluster, based on archival Chandra observations. Our representative sample consists of 79 galaxies with low-to-intermediate stellar masses (M * ≈ 109−11 M ⊙), a mass range that has not been extensively explored with X-ray observations thus far. We detect diffuse X-ray emission in only eight galaxies and find that in five cases a substantial fraction of the detected emission can be unambiguously attributed to truly diffuse hot gas, based on their spatial distribution and spectral properties. For the individually nondetected galaxies, we constrain their average X-ray emission by performing a stacking analysis, finding a specific X-ray luminosity of L X / M * ∼ 10 28 erg s − 1 M ⊙ − 1 , which is consistent with unresolved stellar populations. The apparent paucity of truly diffuse hot gas in these low- and intermediate-mass ETGs may be the result of efficient ram pressure stripping by the hot intracluster medium. However, we also find no significant diffuse hot gas in a comparison sample of 57 field ETGs of similar stellar masses, for which archival Chandra observations with similar sensitivity are available. This points to the alternative possibility that galactic winds evacuate the hot gas from the inner region of low- and intermediate-mass ETGs, regardless of the galactic environment. Nevertheless, we do find strong morphological evidence for ongoing ram pressure stripping in two galaxies (NGC 4417 and NGC 4459). A better understanding of the roles of ram pressure stripping and galactic winds in regulating the hot gas content of ETGs invites sensitive X-ray observations for a large galaxy sample.

Normal, dust-obscured galaxies in the epoch of reionization.

Over the past decades, rest-frame ultraviolet (UV) observations have provided large samples of UV luminous galaxies at redshift (z) greater than 6 (refs. 1-3), during the so-called epoch of reionization. While a few of these UV-identified galaxies revealed substantial dust reservoirs4-7, very heavily dust-obscured sources at these early times have remained elusive. They are limited to a rare population of extreme starburst galaxies8-12 and companions of rare quasars13,14. These studies conclude that the contribution of dust-obscured galaxies to the cosmic star formation rate density at z > 6 is sub-dominant. Recent ALMA and Spitzer observations have identified a more abundant, less extreme population of obscured galaxies at z = 3-6 (refs. 15,16). However, this population has not been confirmed in the reionization epoch so far. Here, we report the discovery of two dust-obscured star-forming galaxies at z = 6.6813 ± 0.0005 and z = 7.3521 ± 0.0005. These objects are not detected in existing rest-frame UV data and were discovered onlythrough their far-infrared [C II] lines and dust continuum emission as companions to typical UV-luminous galaxies at the same redshift. The two galaxies exhibit lower infrared luminosities and star-formation rates than extreme starbursts, in line with typical star-forming galaxies at z ≈ 7. This population of heavily dust-obscured galaxies appears to contribute 10-25% to the z > 6 cosmic star formation rate density.

Frequency and nature of central molecular outflows in nearby star-forming disk galaxies

Central molecular outflows in spiral galaxies are assumed to modulate their host galaxy’s star formation rate (SFR) by removing gas from the inner region of the galaxy. Outflows consisting of different gas phases appear to be a common feature in local galaxies, yet, little is known about the frequency of molecular outflows in main sequence galaxies in the nearby universe. We develop a rigorous set of selection criteria, which allow the reliable identification of outflows in large samples of galaxies. Our criteria make use of central spectra, position-velocity diagrams and velocity-integrated intensity maps (line-wing maps). We use this method on high-angular resolution CO (2–1) observations from the PHANGS-ALMA survey, which provides observations of the molecular gas for a homogeneous sample of 90 nearby main sequence galaxies at a resolution of ∼100 pc. We find correlations between the assigned outflow confidence and stellar mass or global SFR. We determine the frequency of central molecular outflows to be 25 ± 2% considering all outflow candidates, or 20 ± 2% for secure outflows only. Our resulting outflow candidate sample of 16−20 galaxies shows an overall enhanced fraction of active galactic nuclei (AGN) (50%) and bars (89%) compared to the full sample (galaxies with AGN: 24%, with bar: 61%). We extend the trend between mass outflow rates and SFR known for high outflow rates down to lower values (log10Ṁout[M⊙yr−1] < 0). Mass loading factors are of order unity, indicating that these outflows are not efficient in quenching the SFR in main sequence galaxies.

Galaxy Evolution Probe

The Galaxy Evolution Probe (GEP) is a concept for a mid- and far-infrared space observatory to measure key properties of large samples of galaxies with large and unbiased surveys. GEP will attempt to achieve zodiacal light and Galactic dust emission photon background-limited observations by utilizing a 6 Kelvin, 2.0 meter primary mirror and sensitive arrays of kinetic inductance detectors. It will have two instrument modules: a 10 - 400 micron hyperspectral imager with spectral resolution R = 8 (GEP-I) and a 24 - 193 micron, R = 200 grating spectrometer (GEP-S). GEP-I surveys will identify star-forming galaxies via their thermal dust emission and simultaneously measure redshifts using polycyclic aromatic hydrocarbon emission lines. Galaxy luminosities derived from star formation and nuclear supermassive black hole accretion will be measured for each source, enabling the cosmic star formation history to be measured to much greater precision than previously possible. Using optically thin far-infrared fine-structure lines, surveys with GEP-S will measure the growth of metallicity in the hearts of galaxies over cosmic time and extraplanar gas will be mapped in spiral galaxies in the local universe to investigate feedback processes. The science case and mission architecture designed to meet the science requirements are described, and the kinetic inductance detector and readout electronics state of the art and needed developments are described. This paper supersedes the GEP concept study report cited in it by providing new content, including: a summary of recent mid-infrared KID development, a discussion of microlens array fabrication for mid-infrared KIDs, and additional context for galaxy surveys. The reader interested in more technical details may want to consult the concept study report.

Improving the reliability of photometric redshift with machine learning

ABSTRACT In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of galaxies are needed. Correct estimation of the various photo-z algorithms’ performance requires attention to both the performance metrics and the data used for the estimation. In this work, we use the supervised machine learning algorithm MLPQNA (Multi-Layer Perceptron with Quasi-Newton Algorithm) to calculate photometric redshifts for the galaxies in the COSMOS2015 catalogue and the unsupervised Self-Organizing Maps (SOM) to determine the reliability of the resulting estimates. We find that for zspec < 1.2, MLPQNA photo-z predictions are on the same level of quality as spectral energy distribution fitting photo-z. We show that the SOM successfully detects unreliable zspec that cause biases in the estimation of the photo-z algorithms’ performance. Additionally, we use SOM to select the objects with reliable photo-z predictions. Our cleaning procedures allow us to extract the subset of objects for which the quality of the final photo-z catalogues is improved by a factor of 2, compared to the overall statistics.

Do galaxies die? Different views from simulations and observations in the local Universe

ABSTRACT For years, the extragalactic community has divided galaxies in two distinct populations. One of them, featuring blue colours, is actively forming stars, while the other is made up of ‘red-and-dead’ objects with negligible star formation. Yet, are these galaxies really dead? Here, we would like to highlight that, as previously reported by several independent groups, state-of-the-art cosmological numerical simulations (EAGLE, IllustrisTNG, MAGNETICUM, and SIMBA) predict the existence of a large number of quenched galaxies that have not formed any star over the last few Gyr. In contrast, observational measurements of large galaxy samples in the nearby Universe (GAMA, SDSS) suggest that even the most passive systems still form stars at some residual level close to sSFR ∼ 10−12 yr−1. Unfortunately, extremely low star formation poses a challenge for both approaches. We conclude that, at present, the fraction of truly dead galaxies is still an important open question that must be addressed in order to understand galaxy formation and evolution.

Predicting bulge to total luminosity ratio of galaxies using deep learning

ABSTRACT We present a deep learning model to predict the r-band bulge-to-total luminosity ratio (B/T) of nearby galaxies using their multiband JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample of galaxies with reliable decomposition into the bulge and disc components. The existing approaches to estimate the B/T ratio use galaxy light-profile modelling to find the best fit. This method is computationally expensive, prohibitively so for large samples of galaxies, and requires a significant amount of human intervention. Machine learning models have the potential to overcome these shortcomings. In our CNN model, for a test set of 20 000 galaxies, 85.7 per cent of the predicted B/T values have absolute error (AE) less than 0.1. We see further improvement to 87.5 per cent if, while testing, we only consider brighter galaxies (with r-band apparent magnitude <17) with no bright neighbours. Our model estimates the B/T ratio for the 20 000 test galaxies in less than a minute. This is a significant improvement in inference time from the conventional fitting pipelines, which manage around 2–3 estimates per minute. Thus, the proposed machine learning approach could potentially save a tremendous amount of time, effort, and computational resources while predicting B/T reliably, particularly in the era of next-generation sky surveys such as the Legacy Survey of Space and Time (LSST) and the Euclid sky survey which will produce extremely large samples of galaxies.

The clustering of galaxies in the DESI imaging legacy surveys DR8: I. The luminosity and color dependent intrinsic clustering

In a recent study, we developed a method that models the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). Using this method, we simultaneously obtained both the intrinsic clustering strength and the photometric redshift errors by fitting the projected 2PCF with two integration depths along the line-of-sight. Herein, we apply this method to the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 8 (LS DR8), which is the largest galaxy sample currently available. We separate the galaxies into 20 samples in eight redshift bins, from z = 0.1 to z = 1.0, and several z-band absolute magnitude bins, with Mz ≤ −20. These galaxies are further divided into red and blue subsamples according to their M r 0.5 - M z 0.5 colors. We measure the projected 2PCFs for all these galaxy subsamples and fit them using our photometric redshift 2PCF model. We find that the photometric redshift errors are smaller in the red subsamples than in the overall population. In contrast, some systematic photometric redshift errors exist in the blue subsamples, such that some of the subsamples show a significantly enhanced 2PCF on large scales. Therefore, separately focusing only on the red subsamples and on all the subsamples, we find that the biases of the galaxies in these subsamples exhibit clear color, redshift, and luminosity dependencies; the brighter red galaxies at higher redshift are more biased than their bluer and low-redshift counterparts. Apart from the best-fit set of parameters, σz and b, from this state-of-the-art photometric redshift survey, we obtain high-precision intrinsic clustering measurements for these 40 red- and all-galaxy subsamples. These measurements, on large and small scales, hold important information regarding cosmology and galaxy formation that will be used in our subsequent probes in this series.

A tight angular-momentum plane for disc galaxies

The relations between the specific angular momenta (j) and masses (M) of galaxies are often used as a benchmark in analytic models and hydrodynamical simulations as they are considered to be amongst the most fundamental scaling relations. Using accurate measurements of the stellar (j*), gas (jgas), and baryonic (jbar) specific angular momenta for a large sample of disc galaxies, we report the discovery of tight correlations between j, M, and the cold gas fraction of the interstellar medium (fgas). At fixed fgas, galaxies follow parallel power laws in 2D (j, M) spaces, with gas-rich galaxies having a larger j* and jbar (but a lower jgas) than gas-poor ones. The slopes of the relations have a value around 0.7. These new relations are amongst the tightest known scaling laws for galaxies. In particular, the baryonic relation (jbar − Mbar − fgas), arguably the most fundamental of the three, is followed not only by typical discs but also by galaxies with extreme properties, such as size and gas content, and by galaxies previously claimed to be outliers of the standard 2D j − M relations. The stellar relation (j* − M* − fgas) may be connected to the known j* − M*-bulge fraction relation; however, we argue that the jbar − Mbar − fgas relation can originate from the radial variation in the star formation efficiency in galaxies, although it is not explained by current disc instability models.

Unveiling an Automated Modeling Method for S0 Galaxies

Abstract The objective of this study is to unveil an optimum and precise automated method to model S0 galaxies. Preliminary results of the study confirm that GALFIT—a two-dimensional image decomposition program—with a Sérsic profile can be used to model S0 galaxies. Since the input parameters affect the accuracy of the model, different combinations of parameters were tested to obtain the best-fit model. An automated GALFIT fitting process was developed using Python and Astropy module to increase the efficiency of the process. A sample of S0 galaxy images observed at the Kitt Peak National Observatory was used to test the precision of the implemented method. The accuracy of the created models was tested both visually and statistically. The new method will allow us to model a large sample of S0 galaxies accurately and determine their structure and properties.

LoTSS jellyfish galaxies

Context. The cluster environment has a strong impact on galaxy star formation, as seen by the fact that clusters host proportionally more red, passive galaxies relative to the field. Ram pressure stripping may drive this environmental quenching by directly stripping cold gas from galactic disks. In some cases, ram pressure stripping gives rise to ‘jellyfish galaxies’, observed with clear ‘tentacles’ of stripped gas extending beyond the optical extent of the galaxy. Aims. In this paper we present a large sample of jellyfish galaxies in low redshift clusters (z < 0.05), identified through 120−168 MHz radio continuum from the LOFAR Two-metre Sky Survey (LoTSS). Methods. From a parent sample of 29 X-ray-detected SDSS galaxy clusters and their spectroscopic members, we visually identify 95 star-forming, LoTSS jellyfish galaxies with 144 MHz radio tails. Star formation rates (SFRs) and stellar masses are obtained for all galaxies from SED fits. For each jellyfish galaxy we determine the tail orientation with respect to the cluster centre and quantify the prominence of the radio tails with the 144 MHz shape asymmetry. Results. After carefully accounting for redshift-dependent selection effects, we find that the frequency of jellyfish galaxies is relatively constant from cluster to cluster. LoTSS jellyfish galaxies are preferentially found at small clustercentric radius and large velocity offsets within their host clusters and have radio tails that are oriented away from the cluster centre. These galaxies also show enhanced star formation, relative to both ‘normal’ cluster galaxies and isolated field galaxies, but generally fall within the scatter of the L144 MHz − SFR relation. Conclusions. The properties of the LoTSS jellyfish galaxies identified in this work are fully consistent with expectations from ram pressure stripping. This large sample of jellyfish galaxies will be valuable for further constraining ram pressure stripping and star formation quenching in nearby galaxy clusters. We show that LOFAR is a powerful instrument for identifying ram pressure stripped galaxies across extremely wide fields. Moving forward, we will push the search for jellyfish galaxies beyond this initial cluster sample, including a comprehensive survey of the galaxy group regime.

Less and more IGM-transmitted galaxies from z ∼ 2.7 to z ∼ 6 from VANDELS and VUDS

Aims. Our aim is to analyze the variance of the intergalactic medium (IGM) transmission by studying this parameter in the rest-frame UV spectra of a large sample of high-redshift galaxies. Methods. We made use of the VIMOS Ultra Deep Survey and the VANDELS public survey to gain insight into the far UV spectrum of 2.7 < z < 6 galaxies. Using the SPARTAN fitting software, we estimated the IGM toward individual galaxies and then divided them into two sub-samples characterized by a transmission above or below the theoretical prescription. We created average spectra of combined VUDS and VANDELS data for each set of galaxies in seven redshift bins. Results. The resulting spectra clearly exhibit the variance of the IGM transmission that can be seen directly from high-redshift galaxy observations. Computing the optical depth based on the IGM transmission, we find an excellent agreement with results for quasi-stellar objects. In addition, our measurements appear to suggest that there is a large dispersion of redshift where a complete Gunn-Peterson Trough occurs, depending on the line of sight.

The shape and scatter of the galaxy main sequence for massive galaxies at cosmic noon

ABSTRACT We present the main sequence for all galaxies and star-forming galaxies for a sample of 28 469 massive (M⋆ ≥ 1011 M⊙) galaxies at cosmic noon (1.5 < z < 3.0), uniformly selected from a 17.5 deg2 area (0.33 Gpc3 comoving volume at these redshifts). Our large sample allows for a novel approach to investigating the galaxy main sequence that has not been accessible to previous studies. We measure the main sequence in small mass bins in the SFR–M⋆ plane without assuming a functional form for the main sequence. With a large sample of galaxies in each mass bin, we isolate star-forming galaxies by locating the transition between the star-forming and green valley populations in the SFR–M⋆ plane. This approach eliminates the need for arbitrarily defined fixed cutoffs when isolating the star-forming galaxy population, which often biases measurements of the scatter around the star-forming galaxy main sequence. We find that the main sequence for all galaxies becomes increasingly flat towards present day at the high-mass end, while the star-forming galaxy main sequence does not. We attribute this difference to the increasing fraction of the collective green valley and quiescent galaxy population from z = 3.0 to z = 1.5. Additionally, we measure the total scatter around the star-forming galaxy main sequence and find that it is ∼0.5–1.0 dex with little evolution as a function of mass or redshift. We discuss the implications that these results have for pinpointing the physical processes driving massive galaxy evolution.

XCOLD GASS and xGASS: Radial metallicity gradients and global properties on the star-forming main sequence

Context. The xGASS and xCOLD GASS surveys have measured the atomic (H I) and molecular gas (H2) content of a large and representative sample of nearby galaxies (redshift range of 0.01 < z < 0.05). Methods. We present optical longslit spectra for a subset of the xGASS and xCOLD GASS galaxies to investigate the correlation between radial metallicity profiles and cold gas content. In addition to previous data, this paper presents new optical spectra for 27 galaxies in the stellar mass range of 9.0 ≤ log M⋆ [M⊙] ≤10.0. Methods. The longslit spectra were taken along the major axis of the galaxies, allowing us to obtain radial profiles of the gas-phase oxygen abundance (12 + log(O/H)). The slope of a linear fit to these radial profiles is defined as the metallicity gradient. We investigated correlations between these gradients and global galaxy properties, such as star formation activity and gas content. In addition, we examined the correlation of local metallicity measurements and the global H I mass fraction. Results. We obtained two main results: (i) the local metallicity is correlated with the global H I mass fraction, which is in good agreement with previous results. A simple toy model suggests that this correlation points towards a ‘local gas regulator model’; (ii) the primary driver of metallicity gradients appears to be stellar mass surface density (as a proxy for morphology). Conclusions. This work comprises one of the few systematic observational studies of the influence of the cold gas on the chemical evolution of star-forming galaxies, as considered via metallicity gradients and local measurements of the gas-phase oxygen abundance. Our results suggest that local density and local H I mass fraction are drivers of chemical evolution and the gas-phase metallicity.

The miniJPAS survey

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start imaging thousands of square degrees of the northern sky with its unique set of 56 filters (spectral resolution of R ∼ 60). Before the arrival of the final instrument, we observed 1 deg2 on the AEGIS field with an interim camera with all the J-PAS filters. Taking advantage of these data, dubbed miniJPAS, we aim at proving the scientific potential of the J-PAS to derive the stellar population properties of galaxies via fitting codes for spectral energy distributions (SEDs), with the ultimate goal of performing galaxy evolution studies across cosmic time. One parametric (BaySeAGal) and three non-parametric (MUFFIT, AlStar, and TGASPEX) SED-fitting codes are used to constrain the stellar mass, age, metallicity, extinction, and rest-frame and dust-corrected (u − r) colours of a complete flux-limited sample (rSDSS ≤ 22.5 AB) of miniJPAS galaxies that extends up to z = 1. We generally find consistent results on the galaxy properties derived from the different codes, independently of the galaxy spectral type or redshift; this is remarkable considering that 25% of the J-spectra have signal-to-noise ratios (S/N) ∼3. For galaxies with S/N ≥ 10, we estimate that the J-PAS photometric system will allow us to derive the stellar population properties of rest-frame (u − r) colour, stellar mass, extinction, and mass-weighted age with a precision of 0.04 ± 0.02 mag, 0.07 ± 0.03 dex, 0.2 ± 0.09 mag, and 0.16 ± 0.07 dex, respectively. This precision is equivalent to that obtained with spectroscopic surveys of similar S/N. By using the dust-corrected (u − r) colour–mass diagram, a powerful proxy for characterizing galaxy populations, we find: (i) that the fraction of red and blue galaxies evolves with cosmic time, with red galaxies being ∼38% and ∼18% of the whole population at z = 0.1 and z = 0.5, respectively, and (ii) consistent results between codes for the average intrinsic (u − r) colour, stellar mass, age, and stellar metallicity of blue and red galaxies and their evolution up to z = 1. At all redshifts, the more massive galaxies belong to the red sequence, and these galaxies are typically older and more metal-rich than their counterparts in the blue cloud. Our results confirm that with J-PAS data we will be able to analyse large samples of galaxies up to z ∼ 1, with galaxy stellar masses above log(M⋆/M⊙)∼8.9, 9.5, and 9.9 at z = 0.3, 0.5, and 0.7, respectively. The star formation history of a complete sub-sample of galaxies selected at z ∼ 0.1 with log(M⋆/M⊙) > 8.3 constrains the cosmic evolution of the star formation rate density up to z ∼ 3, in good agreement with results from cosmological surveys.