Easylife: the data reduction and survey handling system for VIPERS

We present Easylife, the software environment developed within the framework of the VIPERS project for automatic data reduction and survey handling. Easylife is a comprehensive system to automatically reduce spectroscopic data, to monitor the survey advancement at all stages, to distribute data within the collaboration and to release data to the whole community. It is based on the OPTICON founded project FASE, and inherits the FASE capabilities of modularity and scalability. After describing the software architecture, the main reduction and quality control features and the main services made available, we show its performance in terms of reliability of results. We also show how it can be ported to other projects having different characteristics.Comment: pre-print, 17 pages, 4 figures, accepted for publication in Publications of the Astronomical Society of the Pacifi

Visualization, Exploration and Data Analysis of Complex Astrophysical Data

In this paper we show how advanced visualization tools can help the researcher in investigating and extracting information from data. The focus is on VisIVO, a novel open source graphics application, which blends high performance multidimensional visualization techniques and up-to-date technologies to cooperate with other applications and to access remote, distributed data archives. VisIVO supports the standards defined by the International Virtual Observatory Alliance in order to make it interoperable with VO data repositories. The paper describes the basic technical details and features of the software and it dedicates a large section to show how VisIVO can be used in several scientific cases.Comment: 32 pages, 15 figures, accepted by PAS

EZ: A Tool for Automatic Redshift Measurement

We present EZ (Easy redshift), a tool we have developed within the VVDS project to help in redshift measurement from otpical spectra. EZ has been designed with large spectroscopic surveys in mind, and in its development particular care has been given to the reliability of the results obtained in an automatic and unsupervised mode. Nevertheless, the possibility of running it interactively has been preserved, and a graphical user interface for results inspection has been designed. EZ has been successfully used within the VVDS project, as well as the zCosmos one. In this paper we describe its architecture and the algorithms used, and evaluate its performances both on simulated and real data. EZ is an open source program, freely downloadable from http://cosmos.iasf-milano.inaf.it/pandora.Comment: accepted for publication in Publications of the Astronomical Society of the Pacifi

The VIMOS Ultra Deep Survey. Luminosity and stellar mass dependence of galaxy clustering at z~3

We present the study of the dependence of galaxy clustering on luminosity and stellar mass in the redshift range 2$<$z$<$3.5 using 3236 galaxies with robust spectroscopic redshifts from the VIMOS Ultra Deep Survey (VUDS). We measure the two-point real-space correlation function $w_p(r_p)$ for four volume-limited stellar mass and four luminosity, M$_{UV}$ absolute magnitude selected, sub-samples. We find that the scale dependent clustering amplitude $r_0$ significantly increases with increasing luminosity and stellar mass indicating a strong galaxy clustering dependence on these properties. This corresponds to a strong relative bias between these two sub-samples of $\Delta$b/b$^*$=0.43. Fitting a 5-parameter HOD model we find that the most luminous and massive galaxies occupy the most massive dark matter haloes with $\langle$M$_h$$\rangle$ = 10$^{12.30}$ h$^{-1}$ M$_{\odot}$. Similar to the trends observed at lower redshift, the minimum halo mass M$_{min}$ depends on the luminosity and stellar mass of galaxies and grows from M$_{min}$ =10$^{9.73}$ h$^{-1}$M$_{\odot}$ to M$_{min}$=10$^{11.58}$ h$^{-1}$M$_{\odot}$ from the faintest to the brightest among our galaxy sample, respectively. We find the difference between these halo masses to be much more pronounced than is observed for local galaxies of similar properties. Moreover, at z~3, we observe that the masses at which a halo hosts, on average, one satellite and one central galaxy is M$_1$$\approx$4M$_{min}$ over all luminosity ranges, significantly lower than observed at z~0 indicating that the halo satellite occupation increases with redshift. The luminosity and stellar mass dependence is also reflected in the measurements of the large scale galaxy bias, which we model as b$_{g,HOD}$($>$L)=1.92+25.36(L/L$^*$)$^{7.01}$. We conclude our study with measurements of the stellar-to-halo mass ratio (SHMR).Comment: 20 pages, 11 figures, A&A in press, v2. revised discussion in sec. 5.5, changed Fig. 4 and Fig. 11, added reference

Automated reliability assessment for spectroscopic redshift measurements

We present a new approach to automate the spectroscopic redshift reliability assessment based on machine learning (ML) and characteristics of the redshift probability density function (PDF). We propose to rephrase the spectroscopic redshift estimation into a Bayesian framework, in order to incorporate all sources of information and uncertainties related to the redshift estimation process, and produce a redshift posterior PDF that will be the starting-point for ML algorithms to provide an automated assessment of a redshift reliability. As a use case, public data from the VIMOS VLT Deep Survey is exploited to present and test this new methodology. We first tried to reproduce the existing reliability flags using supervised classification to describe different types of redshift PDFs, but due to the subjective definition of these flags, soon opted for a new homogeneous partitioning of the data into distinct clusters via unsupervised classification. After assessing the accuracy of the new clusters via resubstitution and test predictions, unlabelled data from preliminary mock simulations for the Euclid space mission are projected into this mapping to predict their redshift reliability labels.Comment: Submitted on 02 June 2017 (v1). Revised on 08 September 2017 (v2). Latest version 28 September 2017 (this version v3

The VIMOS-VLT Deep Survey: Dependence of galaxy clustering on stellar mass

We have investigated the dependence of galaxy clustering on their stellar mass at z~1, using the data from the VIMOS-VLT Deep Survey (VVDS). We have measured the projected two-point correlation function of galaxies, wp(rp) for a set of stellar mass selected samples at an effective redshift =0.85. We have control and quantify all effects on galaxy clustering due to the incompleteness of our low mass samples. We find that more massive galaxies are more clustered. When compared to similar results at z~0.1 in the SDSS, we observed no evolution of the projected correlation function for massive galaxies. These objects present a stronger linear bias at z~1 with respect to low mass galaxies. As expected, massive objects at high redshift are found in the highest pics of the dark matter density field.Comment: 4 pages, 2 figures, 43rd Rencontres de Moriond - March 15-22, 2008 - La Thuile (Val d'Aosta, Italy