We present observations collected in the CFHTLS-VIPERS region in the ultraviolet with the GALEX satellite (far- and near-ultraviolet channels) and in the near-infrared with the CFHT/WIRCam camera (K_s band) over an area of 22 and 27 deg^2, respectively. The depth of the photometry was optimised to measure the physical properties (e.g., star formation rate, stellar masses) of all the galaxies in the VIPERS spectroscopic survey. The large volume explored by VIPERS will enable a unique investigation of the relationship between the galaxy properties and their environment (density field and cosmic web) at high redshift (0.5 ≤ z ≤ 1.2). In this paper, we present the observations, the data reductions, and the build-up of the multi-colour catalogues. The CFHTLS-T0007 (gri-χ^2) images are used as reference to detect and measure the Ks-band photometry, while the T0007 u^∗-selected sources are used as priors to perform the GALEX photometry based on a dedicated software (EMphot). Our final sample reaches NUV_(AB) ~ 25 (at 5σ) and KAB ~ 22 (at 3σ). The large spectroscopic sample (~51 000 spectroscopic redshifts) allows us to highlight the robustness of our star/galaxy separation and the reliability of our photometric redshifts with a typical accuracy of σ_z ≤ 0.04 and a fraction of catastrophic failures η ≤ 2% down to i ~ 23. We present various tests on the K_s-band completeness and photometric redshift accuracy by comparing our results with existing overlapping deep photometric catalogues. Finally, we discuss the BzK sample of passive and active galaxies at high redshift and the evolution of galaxy morphology in the (NUV−r) vs. (r−K_s) diagram at low redshift (z ≤ 0.25) based on the high image quality of the CFHTLS.
We investigate the evolution of the galaxy stellar mass function (SMF) and stellar mass density from redshift z=0.2 to z=1.5 of a $K_{AB}$<22-selected sample with highly reliable photometric redshifts and over an unprecedentedly large area. Our study is based on NIR observations carried out with WIRCam at CFHT over the footprint of the VIPERS spectroscopic survey and benefits from the high quality optical photometry from the CFHTLS and UV observations with the GALEX satellite. The accuracy of our photometric redshifts is $\sigma_z$ < 0.03 and 0.05 for the bright ($i_{AB}$<22.5) and faint ($i_{AB}$>22.5) samples, respectively. The SMF is measured with ~760,000 galaxies down to $K_s$=22 and over an effective area of ~22.4 deg$^2$, the latter of which drastically reduces the statistical uncertainties (i.e. Poissonian error & cosmic variance). We point out the importance of a careful control of the photometric calibration, whose impact becomes quickly dominant when statistical uncertainties are reduced, which will be a major issue for future generation of cosmological surveys with, e.g. EUCLID or LSST. By exploring the rest-frame (NUV-r) vs (r-$K_s$) color-color diagram separating star-forming and quiescent galaxies, (1) we find that the density of very massive log($M_*/ M_{\odot}$) > 11.5 galaxies is largely dominated by quiescent galaxies and increases by a factor 2 from z~1 to z~0.2, which allows for additional mass assembly via dry mergers, (2) we confirm a scenario where star formation activity is impeded above a stellar mass log($M^*_{SF} / M_{\odot}$) = 10.64$\pm$0.01, a value that is found to be very stable at 0.2 < z < 1.5, (3) we discuss the existence of a main quenching channel that is followed by massive star-forming galaxies, and finally (4) we characterise another quenching mechanism required to explain the clear excess of low-mass quiescent galaxies observed at low redshift.
We use the full VIPERS redshift survey in combination with SDSS-DR7 to explore the relationships between star-formation history (using d4000), stellar mass and galaxy structure, and how these relationships have evolved since z~1. We trace the extents and evolutions of both the blue cloud and red sequence, by fitting double Gaussians to the d4000 distribution of galaxies in narrow stellar mass bins, for four redshift intervals over 010^11 M_sun, d4000<1.55) drops sharply by a factor five between z~0.8 and z~0.5. These galaxies are becoming quiescent at a rate that largely matches the increase in the numbers of massive passive galaxies seen over this period. We examine the size-mass relation of blue cloud galaxies, finding that its high-mass boundary runs along lines of constant M*/r_e or equivalently inferred velocity dispersion. Larger galaxies can continue to form stars to higher stellar masses than smaller galaxies. As blue cloud galaxies approach this high-mass limit, they start to be quenched, their d4000 values increasing to push them towards the green valley. In parallel, their structures change, showing higher Sersic indices and central stellar mass densities. For these galaxies, bulge growth is necessary for them to reach the high-mass limit of the blue cloud and be quenched by internal mechanisms. The blue cloud galaxies that are being quenched at z~0.8 lie along the same size-mass relation as present day quiescent galaxies, and seem the likely progenitors of today's S0s.
We measure the evolution of the galaxy stellar mass function from z=1.3 to z=0.5 using the first 53,608 redshifts of the ongoing VIMOS Public Extragalactic Survey (VIPERS). We estimate the galaxy stellar mass function at several epochs discussing in detail the amount of cosmic variance affecting our estimate. We find that Poisson noise and cosmic variance of the galaxy mass function in the VIPERS survey are comparable with the statistical uncertainties of large surveys in the local universe. VIPERS data allow us to determine with unprecedented accuracy the high-mass tail of the galaxy stellar mass function, which includes a significant number of galaxies that are usually too rare to detect with any of the past spectroscopic surveys. At the epochs sampled by VIPERS, massive galaxies had already assembled most of their stellar mass. We apply a photometric classification in the (U-V) rest-frame colour to compute the mass function of blue and red galaxies, finding evidence for the evolution of their contribution to the total number density budget: the transition mass above which red galaxies dominate is found to be about 10^10.4 M_sun at z=0.55 and evolves proportionally to (1+z)^3. We are able to trace separately the evolution of the number density of blue and red galaxies with masses above 10^11.4 M_sun, in a mass range barely studied in previous work. We find that for such large masses, red galaxies show a milder evolution with redshift, when compared to objects at lower masses. At the same time, we detect a population of similarly massive blue galaxies, which are no longer detectable below z=0.7. These results show the improved statistical power of VIPERS data, and give initial promising indications of mass-dependent quenching of galaxies at z~1. [Abridged]
Various galaxy classification schemes have been developed so far to constrain the main physical processes regulating evolution of different galaxy types. In the era of a deluge of astrophysical information and recent progress in machine learning, a new approach to galaxy classification becomes imperative.
We employ a Fisher Expectation-Maximization unsupervised algorithm working in a parameter space of 12 rest-frame magnitudes and spectroscopic redshift. The model (DBk) and the number of classes (12) were established based on the joint analysis of standard statistical criteria and confirmed by the analysis of the galaxy distribution with respect to a number of classes and their properties. This new approach allows us to classify galaxies based just on their redshifts and UV-NIR spectral energy distributions.
The FEM unsupervised algorithm has automatically distinguished 12 classes: 11 classes of VIPERS galaxies and an additional class of broad-line AGNs. After a first broad division into blue, green and red categories we obtained a further sub-division into three red, three green, and five blue galaxy classes. The FEM classes follow the galaxy sequence from the earliest to the latest types that is reflected in their colours (which are constructed from rest-frame magnitudes used in classification procedure) but also their morphological, physical, and spectroscopic properties (not included in the classification scheme). We demonstrate that the members of each class share similar physical and spectral properties. In particular, we are able to find three different classes of red passive galaxy populations. Thus, we demonstrate the potential of an unsupervised approach to galaxy classification and we retrieve the complexity of galaxy populations at z~0.7, a task that usual simpler colour-based approaches cannot fulfil.
Aims. We analyse the properties of the host galaxies of a [NeV]-selected sample to investigate whether and how they are affected by the AGN. Methods. We have selected a sample of galaxies at 0.62 < z < 1.2 from the VIMOS Public Extragalactic Redshift Survey (VIPERS) and divided it in blue cloud galaxies, red passive galaxies and green valley galaxies using the NUV r K diagram. Within each category, galaxies with AGN activity were identified based on the detection of the high-ionisation [NeV] λ 3426 emission line. For each galaxy we derived several properties (stellar age and mass, the ( r − K ) colour, the [OII] luminosity) and compared them between active and inactive galaxies matched in stellar mass and redshift. Results . We find statistically significant differences in the properties between active and inactive galaxies. These differences imply that the AGN is more often found in galaxies with younger stellar populations and more recent star-forming activity than their parent samples. Interestingly, the AGN identified through the [NeV] λ 3426 emission line is not commonly found by traditional AGN-selection techniques based on shallow X-ray data, mid-IR colours, and classical line diagnostic diagrams, and might thus reveal a specific evolutionary phase. The spectral analysis reveals a sub-set of AGN within the blue cloud that has spectral signatures implying a sudden suppression of star formation activity similar to post-starburst galaxies. Conclusion . Using the rich dataset of the large VIPERS sample we identify a novel class of active post-starburst galaxies that would be missed by traditional selection techniques. These galaxies belong to the blue cloud, but their star-formation activity has been recently suppressed, possibly by the AGN identified through the presence of the [NeV] λ 3426 emission line in their spectra. Our results support the idea that AGN feedback may be responsible for halting star-formation in active blue galaxies and for their transition into the red sequence, at least in the 0.6–1.2 redshift range and for stellar masses greater than 5 × 10 10 ℳ ⊙ . Our results are based on a complete spectroscopic sample and limited by the [NeV] observability, and the AGN can be variable and with a relatively short duty cycle. Considering this, AGN feedback that makes blue galaxies quickly transition to the red sequence may be even more common than previously believed.
Aims. Using the VIMOS Public Extragalactic Redshift Survey (VIPERS) we aim to jointly estimate the key parameters that describe the galaxy density field and its spatial correlations in redshift space. Methods. We use the Bayesian formalism to jointly reconstruct the redshift-space galaxy density field, power spectrum, galaxy bias and galaxy luminosity function given the observations and survey selection function. The high-dimensional posterior distribution is explored using the Wiener filter within a Gibbs sampler. We validate the analysis using simulated catalogues and apply it to VIPERS data taking into consideration the inhomogeneous selection function. Results. We present joint constraints on the anisotropic power spectrum as well as the bias and number density of red and blue galaxy classes in luminosity and redshift bins as well as the measurement covariances of these quantities. We find that the inferred galaxy bias and number density parameters are strongly correlated although these are only weakly correlated with the galaxy power spectrum. The power spectrum and redshift-space distortion parameters are in agreement with previous VIPERS results with the value of the growth rate $f\sigma_8 = 0.38$ with 18% uncertainty at redshift 0.7.
Aims. Various galaxy classification schemes have been developed so far to constrain the main physical processes regulating evolution of different galaxy types. In the era of a deluge of astrophysical information and recent progress in machine learning, a new approach to galaxy classification has become imperative. Methods. In this paper, we employ a Fisher Expectation-Maximization (FEM) unsupervised algorithm working in a parameter space of 12 rest-frame magnitudes and spectroscopic redshift. The model (DBk) and the number of classes (12) were established based on the joint analysis of standard statistical criteria and confirmed by the analysis of the galaxy distribution with respect to a number of classes and their properties. This new approach allows us to classify galaxies based on only their redshifts and ultraviolet to near-infrared (UV–NIR) spectral energy distributions. Results. The FEM unsupervised algorithm has automatically distinguished 12 classes: 11 classes of VIPERS galaxies and an additional class of broad-line active galactic nuclei (AGNs). After a first broad division into blue, green, and red categories, we obtained a further sub-division into: three red, three green, and five blue galaxy classes. The FEM classes follow the galaxy sequence from the earliest to the latest types, which is reflected in their colours (which are constructed from rest-frame magnitudes used in the classification procedure) but also their morphological, physical, and spectroscopic properties (not included in the classification scheme). We demonstrate that the members of each class share similar physical and spectral properties. In particular, we are able to find three different classes of red passive galaxy populations. Thus, we demonstrate the potential of an unsupervised approach to galaxy classification and we retrieve the complexity of galaxy populations at z ∼ 0.7, a task that usual, simpler, colour-based approaches cannot fulfil.
Identifying spurious reduction artefacts in galaxy spectra is a challenge for large surveys. We present an algorithm for identifying and repairing residual spurious features in sky-subtracted galaxy spectra with application to the VIPERS survey. The algorithm uses principal component analysis (PCA) applied to the galaxy spectra in the observed frame to identify sky line residuals imprinted at characteristic wavelengths. We further model the galaxy spectra in the rest-frame using PCA to estimate the most probable continuum in the corrupted spectral regions, which are then repaired. We apply the method to 90,000 spectra from the VIPERS survey and compare the results with a subset where careful editing was performed by hand. We find that the automatic technique does an extremely good job in reproducing the time-consuming manual cleaning and does it in a uniform and objective manner across a large data sample. The mask data products produced in this work are released together with the VIPERS second public data release (PDR-2).
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