Galaxies in the UKIDSS Large Area Survey Jon Loveday Anthony Smith Celine Eminian University of Sussex

Outline UK Infrared Deep Sky Survey overview and status Near-IR luminosity function Photometric redshifts Physical Interpretation of near-IR Colours Conclusions/future prospects

Goals Large-scale clustering to z ~ 0.6 (BAO, neutrino mass) Evolution of galaxy properties (LF, SFR) and clustering since z ~ 0.6 Try out techniques on real data before future surveys such as DES, PanSTARRS, LSST etc begin

UKIDSS UK Infrared Deep Sky Survey UKIRT 3.8m telescope plus WFCAM (4x Hawaii-II arrays, 0.21 deg 2 ) Étendue of 2.38 m 2 deg 2 largest of any IR camera until VISTA zYJHK (1 ~ 2.5  ) near-IR filters 5 surveys, 3 extragalactic Significantly deeper than 2MASS

UKIDSS Observing started May year observing plan (~50% of UKIRT time) Pipeline processing in Cambridge, archive in Edinburgh No consortium proprietary data period Data immediately available to ESO members once verified Rest of world 18 months later

UKIDSS Surveys

Lawrence et al 2007 Comparison with 2MASS

UKIDSS survey progress

Near-IR Luminosity Function ( Smith, Cross, Loveday, in prep) UKIDSS-LAS DR2 K-band photometry + SDSS DR5 redshifts Need to allow for selection effects in –r-band flux (SDSS spectro limit) –K-band flux (UKIDSS completeness limit) –UKIDSS angular size –Surface brightness

LAS: K<16 Vega (17.9 AB)

SDSS: 5740 deg 2 453,349 galaxies with redshifts LAS-K: 476 deg 2

19,105 galaxies to K=16 over 195 deg 2 (400,000 over 4000 deg 2 by end of 2009)

Multivariate  : 1/Vmax method Vmax Too faint Too diffuse Too faint Too small Too bright Too concentrated Too large K-Petrosian magnitude r’-Petrosian magnitude K-surface brightness K-radius z = 0.01 z = ,452 galaxies within selection limits  (M r’, M K,  K, R K )

K-band BBD (1/Vmax) (Bivariate Brightness Distribution)

K-band BBD (SWML)

Red core (u-r) > 2.35 (SWML)

Blue core (u-r) < 2.35 (SWML)

K-band luminosity function

LF Summary UKIDSS K-band LF broadly consistent with previous results Some discrepancies between 1/Vmax and SWML estimates Low-luminosity discrepancy partly due to large- scale structure? UKIDSS will be competitive with 2MASS in terms of volume/galaxy numbers with DR3 onwards (expected December 2007) Extend analysis to DXS, UDS and VISTA surveys with photo-z to probe evolution

Photometric Redshifts Celine Eminian Use SDSS ugriz and UKIDSS-LAS YJHK magnitudes in ANNz (Collister & Lahav 2004) Network architecture 5:10:10:1 (5 bands) or 9:12:12:1 (9 bands) Committee of five networks For each sample, use SDSS spectroscopy: –3/8 for training –1/8 for verification –1/2 for testing (numbers shown on plots)

SDSS Main

SDSS Main + UKIDSS

SDSS Main + LRGs

+ UKIDSS

SDSS Main Adding near-IR photometry helps to reduce outliers

Photo-z Summary At low redshifts (z ≤ 0.6) addition of near-IR photometry helps to improve errors by reducing outliers Lack of improvement for LRGs with UKIDSS data due to –Small training set cf. network size? –Uniformity of LRG SED? Severe lack of spectroscopic training data for ordinary galaxies at redshifts between ~0.2 and 1 Cannot use LRG-trained network to predict redshifts of non-LRGs AAOmega service proposal in queue to obtain spectroscopic redshifts of wide range of galaxies out to z = 0.6 from coadded data in SDSS southern stripe

Physical Interpretation of near-IR Colours Eminian et al, 2007, MNRAS in press Compare 3-arcsec aperture photometry from SDSS and UKIDSS-LAS with physical galaxy properties deduced from SDSS spectra (SDSS- MPA database; Brinchmann et al 2004) and with stellar population synthesis models Pair matching technique to remove correlations with mass, redshift and concentration

Increasing star-formation rate correlates with bluer optical colours but redder near-IR colours Due to dominance of TP- AGB stars in HK bands (Marraston 2005) These stars also responsible for correlation of HK with dust?

Comparsion with BC03 Stars: constant SFR; Squares  = 3Gyr; Ages 5, 10, 15 Gyr bot-top

Comparsion with CB07 (prelim)

Conclusions/Future Prospects Goal is to measure evolution in stellar mass and clustering of a wide range of galaxy masses to z ~ 0.6 Well-calibrated photometric redshifts of representative galaxies will be vital to do this UKIDSS DR3 (December 2007) will probe volume competitive with 2MASS and provide far cleaner window function for clustering statistics Immediate goal: how well can large-scale clustering be measured using photo-z (eg. w(  ) in photo-z slices) compared with using spectroscopic redshifts? Techniques can then be applied to UKIDSS DXS & UDS, VISTA …