New Results from the DEEP2 Galaxy Redshift Survey Jeffrey Newman Lawrence Berkeley National Laboratory And The DEEP2 Team

The DEEP2 Collaboration U.C. Berkeley M. Davis (PI) A. Coil M. Cooper B. Gerke R. Yan C. Conroy LBNL J. Newman U. Hawaii N. Kaiser U.C. Santa Cruz S. Faber (Co-PI) D. Koo P. Guhathakurta D. Phillips C. Willmer B. Weiner R. Schiavon K. Noeske A. Metevier L. Lin N. Konidaris G. Graves JPL P. Eisenhardt Princeton D. Finkbeiner U. Pitt. A. Connolly K survey (Caltech) K. Bundy C. Conselice R. Ellis The DEEP2 Galaxy Redshift Survey, which uses the DEIMOS spectrograph on the Keck II telescope, is studying both galaxy properties and large-scale structure at z=1.

DEEP2 Update DEEP2 was designed to have comparable size and density to previous generation local redshift surveys and is ~50 times larger than previous surveys at z~ fields totalling 3 square degrees Most targets at 0.7<z<1.4 (median 0.94) Each field 0.5 o x <2 o =20x60x1000 Mpc/h 3 >50,000 R~5000 spectra to R AB =24.1, typically covering Å;~40,000 redshifts net >400 one hour exposures with the DEIMOS spectrograph, requiring 80 Keck nights DEEP2 began observations Summer 2002, and is now >80% complete. 3 of 4 fields will soon be done.

Update on observations of the Extended Groth Strip (EGS) Spitzer MIPS, IRAC DEEP2 spectra and Caltech / JPL K s imaging HST/ACS V,I (Cycle 13) Background: 2 x 2 deg from POSS DEEP2/CFHT B,R,I GALEX NUV+FUV Chandra & XMM: Past coverage New Award (1.4Ms) Plus VLA (6 & 21 cm), SCUBA, etc….

Do the fundamental constants of Nature change over time? DEEP2 data can be used to answer questions not considered when the survey was designed. For instance, we are now testing for evolution in the Fine Structure Constant, . Time evolution of  is predicted by some dark energy scenarios and theories with large extra dimensions. There have been recent claims of significant evolution based on QSO absorption-line systems. Most methods of testing for evolution in  are likely dominated by unknown systematics (e.g. different groups get significantly different results).

Previous measurements [OIII] emission lines provide lower nominal accuracies than absorption line/many-multiplet or natural reactor methods, but the physics is much simpler. It is this type of measurement which we can perform with DEEP2.

 and [OIII] The [OIII] 4959/5007 doublet lines both are emitted from the same state and are optically thin; they therefore have line profiles proportional to each other (regardless of isotopal ratios, etc). To <~1%,             for these lines, as the splitting arises from fine structure directly.

Measuring  with DEEP2 The DEEP2 sample is unique in using galaxies, rather than QSOs/AGN, to measure [OIII] wavelengths. Advantages of DEEP2 for this work include: High spectral resolution compared to SDSS sample (0.3 Å/pix). Tight control of wavelength solution. Systematics are <0.001Å differential between the two [OIII] lines. Larger sample than SDSS DR1 QSOs (~ galaxies), allowing empirical tests of errors. Higher typical redshift (median z=0.72 vs 0.37). Main disadvantage is lower S/N for each individual object - beat everything down by sqrt(N).

Tying down the wavelength solution The wavelength scale for DEEP2 spectra is set using KrArNeXe arc lamps, with conventional techniques. -Typically ~20 lines are used on each half of the detector, with RMS ~0.005Å about each fit. However, the wavelength scale at the time of calibration may not match that at time of observation (e.g. due to change in focus due to thermal expansion). Temperature changes can be systematic! To correct for this, we fit for wavelength differences between each slit’s sky spectrum and a high resolution sky spectrum from Fulbright & Osterbrock (1996).

Tying down the wavelength solution, II Cross-correlation gives a robust measurement of the local shift between the observed & template sky spectra. We fit this to quadratic order…

Tying down the wavelength solution, III Then fit for the variation of the coefficients of the quadratic over each DEIMOS mask as a function of X & Y. There are >100 slits per mask, with RMS about the fits of ~ Å (dwarfed by centroid errors).

Looking for changes from z=0 Simplest thing: combine all data with z>0.6 into one bin, and measure.

Results - checking for an offset Results are very consistent with no evolution in  from z=0. We can perturb many of the ways we do things (e.g. use H  for redshifts instead of the full spectrum, or change the wavelength calibration of template sky spectrum) and this remains true.

Results - exploring d  /dt

Null hypothesis (no evolution from z=0) has very good  2 (p ~ 80%). Adding 1 or 2 parameters only improves  2 marginally.

Using redshifts from H  …

Vs. previous measurements Nominal precision still does not approach QSO absorption- line measurements. However, method is much more simple (and robust?).

Conclusions Our results are consistent with no evolution in the fine structure constant from z~0 to z~0.7. Large surveys can make possible many kinds of scientific discoveries, and go far beyond whatever topics and fields are thought to be interesting when the survey is designed. Future baryonic oscillation surveys may be able to do very well at constraining evolution in , if they have the resolution and right wavelength coverage; they will have large samples of bright, star-forming galaxies at z~1. 100x larger samples may be feasible.

Possible systematics To change   by 0.5 , a systematic must change      by Å rest frame, or      by 0.15Å rest frame. Systematics tested so far are: Systematic Max. effect on  Max. effect on Broad continuum subtraction 5  Å5  Å Stellar absorption lines 4  Å2  Å Template sky spec. calibration 8  Å4  Å Air-to-vacuum conversions 3  Å3  Å

[OIII] vs. Many-multiplet The first attempts to look for variations in  with QSOs used [OIII] emission (e.g. Bahcall & Salpeter 1965). Absorption lines became preferred as they could yield more measurements per spectrum (limited by # of absorbers, while each object has 1 redshift) and can be observed to higher z. Bahcall et al. 2003

Be wary of highest/lowest z’s… Shown are residuals between single-spectrum and global fits to the perturbation to the wavelength system from skylines. Residuals are worst at the ends of the spectra. Quantifying now…

Spitzer observations are complete IRAC 3.6 µmIRAC 8.0 µm 5’x5’ (~11 galaxies/sq-arcmin have R<24.1)

Redshift Distribution of Data: z~ Status: -three-year survey -began summer currently >80% complete -finish this summer Our color cuts are very successful! ~90% of our targets are at z>0.75 and we miss only 3% of high-z objects - test in the EGS, where we do not apply the photo-z cut.

Redshift Maps in 4 Fields: z= Cone diagram of 1/12 of the full DEEP2 sample

2-point correlation function:  (r) (L>L*, preliminary:) z= : r 0 =4.32 (0.10)  =1.85 (0.05) z= : r 0 =3.48 (0.07)  =1.70 (0.05) Locally:  (r) is roughly a power-law: (r 0 /r)  w/ r 0 ~5 Mpc/h and  ~1.8 Errors are estimated using the variance across fields Coil et al. in prep Initial results: Coil et al. 2004, ApJ, 609, color, spectral type, L - updating now with volume-limited samples z~1:  (r) is ~power-law and we see evolution within the sample:

Galaxy Clustering as a Function of Color Red galaxies have a larger correlation length and larger velocity dispersion/fingers of god: reside in more clustered / dense environments. Detect coherent infall on large scales for both blue and red galaxies.

Galaxy Clustering as a Function of Color Within the red population, clustering does not depend on color, while for the blue population, redder galaxies are more clustered than bluer galaxies. Next: L, spectral type, linewidth, morphology, etc. Coil et al. in prep (for L>=L*, z= , preliminary:) red: r 0 =5.09 (0.11)  =1.95 (0.05) blue: r 0 =3.56 (0.07)  =1.74 (0.05)

Galaxy Properties and Environment Measure galaxy environment using projected 3rd-nearest neighbor distance. See strong trends of restframe color and OII equivalent width with environment. No residual trend in OII EW once the correlation of environment with color is removed. Cooper et al. in prep blue color red log environment OII equivalent width (SFR)

Color vs. Equivalent Width of OII Red galaxies have low OII EW, while blue galaxies span a range of EW’s. Red galaxies have low OII EW, while blue galaxies span a range of EW’s. It appears that the scatter in this relation is most likely not due to environment. We are currently matching the DEEP2 colors and magnitudes to SDSS to measure the strength of the correlation between environment and galaxy color - look for evolution in the environmental dependence between z=1 and z=0.

Color-Magnitude vs. Environment - DEEP2 results at z=1 Red galaxies reside in denser environments than blue galaxies. There is some trend within the red population with luminosity. Within the blue population, the brightest also seem to lie in the most dense environments - progenitors of central cluster galaxies at z~0? AGN? Density contours: darker regions = higher density Bright blue galaxies in densest environments? Cooper et al. in prep

Finding groups in DEEP2 We find groups using the locations of galaxies in redshift space - no selection based on color, magnitude, etc. - just overdensity in the galaxy distribution. Use a Voronoi tesselation - not FoF. position (For our purposes, “clusters” are just especially massive groups.) Uses of groups include: 1.LSS/cosmology: N( ,z) constrains w 2.Galaxy formation and evolution: e.g., the Butcher-Oemler effect

First DEEP2 Group Catalog Gerke et al. astro-ph/ We currently have group catalogs for 3 fields

Galaxy properties in groups We are using the group catalog to study galaxy properties in groups. We find that redder, early-type galaxies are preferentially found in groups at z~1, similar to local trends. 0.7<z<0.9 Gerke et al. in prep

Group-galaxy cross-correlation function Coil et al. in prep Cross-correlation between galaxies and groups shows how the galaxies are clustered within/ around groups. Find that in the centers of groups at z=1, red galaxies are preferentially found, and there is a lack of blue galaxies.

Voids at z=1 Void Probability Function (VPF) -probability that a given spherical region of radius R contains no galaxies The VPF can be described as an infinite sum of higher- order correlation functions (also depends on the density of galaxies) and potentially contains a wealth of information on hierarchical scaling, gravitational collapse, cosmological parameters, and galaxy biasing. The “reduced” VPF removes the dependence on density and depends only on the hierarchical scaling coefficients.

Measuring the VPF We measure voids in a statistical sense, using the probability for a given random point to contain a void of radius R. We do not search for individual voids.

The VPF in DEEP2 data 2 fields, 2 different mag. limits - VPF depends on galaxy density and magnitude limit. Voids are larger for brighter galaxies / lower galaxy density. Currently comparing to SDSS to look for evolution… Conroy et al. in prep

The VPF in Mock Catalogs The observed VPF matches mock catalogs well. Now testing different mock catalogs with different halo model parameters. Conroy et al. in prep Also using the reduced VPF to constrain the higher-order correlation functions / hierarchical scaling…

K+A Post-Starburst Galaxies Yan et al. in prep K+A galaxies show little on-going star-formation (lack of OII) but strong Balmer features due to recent star-formation (within 1 Gry) - ‘post-starburst galaxies’. These objects are rare, but we cover a large enough volume to find a large statistical sample. Have ~100 galaxies with features of K stars (old, elliptical-type spectra) and A stars (youngish, <1 Gyr) - K+A galaxies.

K+A Post-Starburst Galaxies These galaxies populate the ‘gap’ in the color bi- modality and lie on the red sequence - they may provide clues as to how galaxies move onto the red sequence. We are currently estimating evolution in the rate of K+A galaxies from z=1 to z=0 and investigating their morphologies and environments. Yan et al. in prep

Other recent and upcoming papers include: Angular clustering of galaxies in the DEEP2 fields: Coil et al., 2004, ApJ, 617, 765 DEEP2 survey strategy and constraints on dark energy: Davis et al., astro-ph/ Evolution of close-pairs/merger rates: Lin et al., 2004, ApJ, 617, 9 Satellite galaxy kinematics: Conroy et al., astro-ph/ K+A galaxies in the DEEP2 sample: Yan et al., in prep. Overview of the DEEP2 sample: Faber et al., in prep. Multi-wavelength LSS studies in the EGS: use IRAC/MIPS to understand DEEP2 redshift-completeness and selection effects clustering/environments of GALEX, IRAC, K-band sources environments for x-ray and radio sources study merging in optical/IR/radio populations