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| VVDS survey | |
|---|---|
| Name | VIMOS VLT Deep Survey |
| Acronym | VVDS |
| Established | 2002 |
| Telescopes | VLT (Unit Telescope 2), CFHT |
| Instruments | VIMOS, CFHTLS |
| Principal investigators | Olivier Le Fèvre, Frédéric Hammer, Luca Pozzetti |
| Wavelength | Optical |
| Area | ~16 deg² (deep, wide fields) |
| Redshift range | z ≈ 0–5 |
| Data release | Several public releases (DR1–DR5) |
VVDS survey
The VIMOS VLT Deep Survey (VVDS) is a major extragalactic redshift survey conducted with the Very Large Telescope and related facilities, designed to map the three-dimensional distribution of galaxies from the local Universe to redshift z~5. The project was led by a European consortium including teams associated with the Centre National de la Recherche Scientifique, Institut d'Astrophysique de Paris, Osservatorio Astronomico di Bologna, and collaborators from the European Southern Observatory, Max Planck Society, and the National Center for Scientific Research. VVDS combined deep spectroscopic campaigns with ancillary imaging from surveys such as Canada–France–Hawaii Telescope Legacy Survey and targeted fields overlapping with the COSMOS, GOODS-North, and CFHTLS Deep areas.
VVDS was conceived to trace galaxy evolution, large-scale structure, and the build-up of stellar mass across cosmic time using spectroscopic redshifts obtained with the VIMOS spectrograph on the Very Large Telescope. Its goals complemented contemporaneous projects like the Sloan Digital Sky Survey, DEEP2 Redshift Survey, zCOSMOS, and 2dF Galaxy Redshift Survey by pushing to fainter magnitudes and higher redshifts in carefully chosen deep and wide fields. The survey design leveraged imaging and multiwavelength support from facilities such as the Spitzer Space Telescope, XMM-Newton, Hubble Space Telescope, and the Subaru Telescope to connect spectroscopic information with photometry, morphology, and environment.
VVDS implemented a tiered strategy of "Wide", "Deep", and "Ultra-Deep" components to balance cosmic volume and depth, targeting magnitude-limited samples selected from CFHT imaging catalogs. The Wide component sampled large areas to characterize cosmic variance and clustering, while the Deep and Ultra-Deep components probed faint populations and high-redshift galaxies, enabling comparisons with the Hubble Deep Field and GOODS programs. Target selection avoided color preselection biases used by surveys like Lyman-break studies, opting instead for pure I-band magnitude limits to provide a representative census of galaxy types analogous to methodologies in 2dFGRS and SDSS. The survey incorporated careful sampling rates, slit-mask strategies, and repeated observations to quantify incompleteness, echoing practices developed for DEEP2 and zCOSMOS.
The primary spectroscopic instrument was VIMOS mounted on the VLT Unit Telescope 2, employing low- and medium-resolution grisms to measure redshifts from prominent lines such as [OII], Hβ, [OIII], and Lyα across optical wavelengths used by instruments like FORS2 and DEIMOS. Observations were scheduled to exploit southern fields accessible from Cerro Paranal and coordinated with northern imaging from CFHT and complementary spectroscopy at facilities like the Keck Observatory. Calibration used standard stars and procedures aligned with pipelines from the European Southern Observatory, with observing strategies informed by prior surveys such as VVDS predecessor projects and lessons from the Las Campanas Redshift Survey and WINGS.
Raw spectra underwent reduction pipelines tailored to VIMOS, performing bias subtraction, flat-fielding, wavelength calibration, sky subtraction, and one-dimensional extraction, using software developed by teams affiliated with CNRS, INAF, and the Observatoire de Paris. Redshift determination combined automated cross-correlation techniques and human validation to assign quality flags comparable to those used in SDSS and DEEP2. Public data releases provided catalogs of spectroscopic redshifts, photometry cross-matched with GALEX, Spitzer, UKIDSS, and morphological parameters from HST imaging where available. Products included luminosity functions, stellar mass estimates calibrated against population synthesis models from groups linked to Bruzual & Charlot and PEGASE, and value-added catalogs facilitating comparisons with model outputs from cosmological simulations like Millennium Simulation and semi-analytic models produced by teams at Max Planck Institute for Astrophysics.
VVDS delivered precise measurements of the evolution of the galaxy luminosity function, showing differential evolution for blue and red populations similar to trends established by DEEP2 and COMBO-17. It quantified the growth of stellar mass and star formation rate density from z~1 to the present, providing constraints complementary to results from COSMOS and Herschel studies. VVDS measurements of galaxy clustering and bias evolution constrained structure growth and tested models from the Lambda-CDM framework and predictions of the Millennium Simulation. High-redshift spectroscopic identifications contributed to discoveries of star-forming and passive galaxies at z>2, connecting to populations studied in Lyman-break Galaxy and Submillimeter Galaxy research. The survey also produced environmental studies of galaxy properties in groups and filaments that interfaced with work from the GAMA survey and the 2MASS database.
VVDS established a benchmark spectroscopic dataset that advanced understanding of galaxy assembly, environment-driven evolution, and large-scale structure, influencing subsequent surveys such as VIPERS, Euclid, DESI, and LSST preparatory work. Its methodology informed instrument designs and survey strategies at observatories including ESO, CFHT, and Keck, while its public releases enabled cross-survey syntheses with multiwavelength programs like GALEX, Herschel Space Observatory, and Chandra X-ray Observatory. The legacy of VVDS persists in constraints on galaxy formation models, calibration of photometric redshifts used in weak lensing studies with HST and future missions, and in training datasets for machine-learning applications developed at institutions such as CEA Saclay and INAF.
Category:Extragalactic astronomy surveys