Highlights from the VIMOS VLT Deep Survey Olivier Le Fèvre, LAM, Marseille On behalf of the VVDS team An unbiased survey of the Universe 0<z<5 using VIMOS / VLT 15000 redshifts to I AB =24 35000 redshifts to I AB =22.5 Accurate description of the galaxy population z<2 Luminosity Function, Luminosity Density Correlation Function Mass Function Specific high redshift populations Red early type galaxies up to z=1.8 Galaxies with 2.5<z<5 QSOs 1
VIMOS -VLT-UT3 A highly efficient redshift machine in operations since 2002 2
VIMOS -VLT-UT3 VVDS: Wide: ~450 spectra Deep: ~550 spectra 3
Design of a deep redshift survey Maintain the ability to make a proper census of galaxies Relate sub-populations to the global population <z>=0.76 VVDS: I-band magnitude selection Simple bias f(λ) No selection against stellar-like objects Imaging survey 16 deg² in BVRI, one mag. deeper than spectra 30x30 arcmin² down to K AB =22.5 3 fields now observed by CFHTLS- Megacam, Ugriz Multi-wavelength survey Deep VLA Spitzer-SWIRE GALEX XMM-LSS Selecting galaxies to survey The high redshift zoo LBG BzK EROs LRGs DRGs Blue/red rest frame Magnitude Mag+color Mag+photoz But only one galaxy population with a continuum of properties 4
VVDS current observations status Field I AB <22.5 I AB <24 I AB <24.75 0226-04 ~14000 1000 Fall 2006 1000+03 ~5000 1400+05 ~10000 +5000 Spring 06 2217+00 ~15000 CDFS ~1500 Public Total ~35000 ~15500 ~1000 Goal >100000 redshifts 0<z<5+ R~230, 5500-9300Å Magnitude selected: I band DEEP: 17.5 I AB 24, 1.2 deg² WIDE: 17.5 I AB 22.5, 10deg² 5 fields,, total ~11 deg² 0230-04 1000+03 (now the HST-COSMOS field) 1400+05 2217+00 CDFS 5
VVDS today: 15000 redshifts I AB 24 in 0.5deg² ~35000 redshifts I AB 22.5 in 8deg² 0.7deg 2 of 4 VVDS fields VVDS-F02h: First Epoch data 17.5 I AB 24 0.7 0.7 deg² 9600 redshifts <z>=0.76 High-z tail up to z=5 VVDS-F22h: 4deg² 17.5 I AB 22.5 15000 redshifts <z>=0.6, up to z=1.5 2 deg 6
Magnitude selection: VVDS-Deep Deep I AB 24 <z>=0.76 Sample all redshifts 0<z<5: consistent measurement of evolution from one sample / selection function A lot of galaxies z~1, tail to z=5 Brighter, bluer galaxies as redshift increases 7
Cone diagram,, 4deg²,, I AB 22.5 <z>=0.76 The largest deep area surveyed by a spectroscopic survey Real data, not a simulation! Garilli et al., in prep. Structures going across the survey transverse size >50 h-1 Mpc 8
Evolution of clustering since z~2 Measure correlation length From projected ξ(rp,π) Global: Le Fèvre et al., 2005, A&A, 439, 877 Per type: Meneux et al., 2006, astro-ph/ See L. Guzzo s talk 9
Evolution of clustering since z~2 Measure correlation length From projected ξ(rp,π) Global: Le Fèvre et al., 2005, A&A, 439, 877 Per type: Meneux et al., 2006, astro-ph/ See L. Guzzo s talk 10
Evolution of the galaxy dark matter bias since z~1.5 Use the PDF of galaxy densities to derive the galaxy dark matter bias The bias is strongly evolving Marinoni et al., 2005, A&A, 442, 801 11
Evolution of the galaxy Luminosity Function per types since z~1.2 Spectral types (SED fit to photometry) Zucca et al. astroph/0506393 Since z~1: 2-3x increase with z for early types 5-10x decrease in latest types Early type vs. latest types LF (2 of 4 types) 12
Influence of environment: the Build-up up of the Colour-density relation fraction RED: (U-V) 1.40 BLUE: (U-V) 0.65 0.25 z 0.6 0.6 z 0.9 0.9 z 1.2 1.2 z 1.5 Spectro-z: compute galaxy density field z=0.7 δ : local galaxy density z=0.8 M B -20.0 Inversion of the colour-density relation at z>0.9 Blue massive star forming galaxies are in higher density regions at z~1.2-1.5 Cucciati et al., 2006, astro-ph/0603202 13
Influence of environment on L.F. LEFT: B-band LF for under dense (blue) and overdense (red) environment, for 4 different redshift bins. RIGHT: 68% (thick lines) and 90% (thin lines) error contours for M* and α RESULTS: - slope is systematically steeper in under-dense environments - no significant difference in M* between over- and under-dense environment Ilbert et al., 2006, 14 astro-ph/0602
Observed Star Formation Rate Results from VVDS redshifts in GALEX fields Availability of VVDS redshifts allowed prompt identification of Galex sources 1000 redshifts of a GALEX sample @1500Å First UV, luminosity density at λobserved=1500a Tresse et al., 2002 Schiminovich et al., 2005 Lilly et al., 1996 (1+z) 2.5 Schiminovitch, llbert, et al., 2005, ApJ, 619, L47 15
Assembly of mass: K-band mass function to z=2 Small evolution of the bright end of the K-band LF: the most massive galaxies were already in place by z~1.5-2 Strong evolution of the low mass population, increasing numbers and slope Pozzetti et al., 2006, In prep. See G. Zamorani s talk, L. Pozzetti s poster 16
Downsizing High mass galaxies experience 10x stronger star formation at z~1 Converging evidence for downsizing from: - Strongly clustered red galaxies - Evolution of colordensity relation VVDS, in prep. 17
Ages of reddest galaxies up to z=1.8 Select the reddest ~100 galaxies (among ~8000) with U-I>2.8 Because of large 0.5deg² coverage in VVDS-Deep, VVDS has the ability to pick-up rare red objects (as many as in GDDS, but brighter) Combine spectra Measure ages from latest BC03 models Place limits on the age of formation. 18
Ages of reddest galaxies up to z=1.8 Select the reddest ~100 galaxies (among ~8000) with U-I>2.8 Because of large 0.5deg² coverage in VVDS-Deep, VVDS has the ability to pick-up rare red objects (as many as in GDDS, but brighter) Combine spectra Measure ages from latest BC03 models Place limits on the age of formation. z=1.4-1.8 19
Ages of reddest galaxies up to z=1.8 Ages of reddest galaxies from SED fitting and Bruzual Charlot models: age of last burst (Lamareille et al., in prep.) Early single burst is a good representation of star formation history for these galaxies Ages consistently point to a redshift for the peak of star formation at z=3-5 20
Making a proper census of z~1.4-5 galaxies VVDS: 970 galaxies with 1.4 z 5 The largest purely magnitude-selected sample in the high redshift universe An unbiased census of the star-forming galaxy population at high-z 21
Selecting galaxies at z~3: LBG <z>=0.76 z=3.2 2.9 z=3.2 3.0 2.9 2.8 2.7 2.7 LBG selection z~3: relies on hypothesis made on the stellar population(s), dust, no AGN Courtesy S. Charlot 22
High redshift galaxies 2.5<z<5 A significant fraction of high-z galaxies cannot be selected via a Lyman-break technique VVDS galaxies: «all in one» combining various populations seen so far? LBGs+BzK+DRGs+ Le Fèvre et al., Nature, 437, 519 23
LF / LD of galaxies with 3<z<4 I-band selected VVDS z=[3,4] Luminosity function shows M* at least 0.7 mag. brighter than LBG selected sample LBG Steidel z=3 Steidel z=4 Sawicki z=3 Sawicki z=4 LD (VVDS) / LD (LBG) =2.8 (α=1.4, M 1700 <-21) Paltani et al., in prep. For integrated LD down to M 1700 =-17, significant uncertainty remains Continue complete census: 24 upcoming I AB =24.75 survey
Faint QSOs at high z Magnitude selection: a more complete census of type II AGN compared to color selection 2Qz-like selection 25
VVDS+Spitzer Spitzer-SWIRESWIRE ~3200 Spitzer-IRAC and MIPS sources with VVDS redshifts Work in progress 26
Conclusions Magnitude selected VVDS: a complete census of galaxies and AGN. Evolution of galaxies is strongly depending on environment (spectroscopic redshifts required) z~1 2: an important time in the life of galaxies. Downsizing at play More bright galaxies at z~3-4 than previously thought Continue complete census at high-z Complete UV and near-ir selected samples with spectroscopic redshifts are necessary for a full picture on evolution 27 See also talks by Guzzo, Zamorani, poster by Pozzetti, etc.
VVDS survey team Laboratoire d Astrophysique (Marseille) : Adami, Arnouts, de la Torre, Ilbert (IfA-Hawaii), Le Brun, Le Fèvre, Marinoni, Mazure, Paltani (Genève), Pollo, Tresse OABo, IRA (INAF Bologna): Bardelli, Bolzonella, Bondi, Bongiorno, Cappi, Marano, Pozzetti, Scaramella (Rome), Vettolani, Zamorani, Zanichelli, Zucca, et al. IAP (Paris): Charlot, McCracken, Mellier IASF (INAF Milan): Bottini, Franzetti, Garilli, Maccagni,, Meneux (LAM), Scodeggio, Vergani, et al. OABr (INAF Milan): Cucciati, Guzzo, Iovino OAC (INAF Naples): Busarello, Merluzzi, Radovich, Ripepi OMP (Toulouse): Contini, Gavignaud (Postdam), Lamareille, Mathez, Pello, Picat 28