galaxies in the ukidss large area survey
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
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Galaxies in the UKIDSS Large Area Survey
Jon Loveday
Anthony Smith
Celine Eminian
University of Sussex
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Outline
• UK Infrared Deep Sky Survey overview and status
• Near-IR luminosity function
• Photometric redshifts
• Physical Interpretation of near-IR Colours
• Conclusions/future prospects
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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
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UKIDSS
• UK Infrared Deep Sky Survey • UKIRT 3.8m telescope plus WFCAM
(4x20482 Hawaii-II arrays, 0.21 deg2)• Étendue of 2.38 m2 deg2 largest of any IR
camera until VISTA• zYJHK (1 ~ 2.5 ) near-IR filters• 5 surveys, 3 extragalactic• Significantly deeper than 2MASS
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UKIDSS
• Observing started May 2005• 7 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
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UKIDSS Surveys
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UKIDSS survey progress
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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
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LAS: K<16 Vega (17.9 AB)
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SDSS: 5740 deg2
453,349 galaxies with redshifts
LAS-K: 476 deg2
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19,105 galaxies to K=16 over 195 deg2
(400,000 over 4000 deg2
by end of 2009)
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Multivariate : 1/Vmax method
Vmax
Too faint
Too diffuse
Too faint
Too small
Too bright
Too bright
Too concentrated
Too large
K-Petrosian magnitude
r’-Petrosian magnitude
K-surface brightness
K-radius
z = 0.01 z = 0.3
16,452 galaxies within selection limits
(Mr’, MK, K, RK)
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K-band BBD (1/Vmax)(Bivariate Brightness Distribution)
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K-band BBD (SWML)
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Red core (u-r) > 2.35 (SWML)
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Blue core (u-r) < 2.35 (SWML)
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K-band luminosity function
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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
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Photometric RedshiftsCeline 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)
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SDSS Main
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SDSS Main + UKIDSS
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SDSS Main + LRGs
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SDSS Main + LRGs
+ UKIDSS
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SDSS Main
Adding near-IR photometry
helps to reduce outliers
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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
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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
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• 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?
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Comparsion with BC03
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Stars: constant SFR; Squares = 3Gyr; Ages 5, 10, 15 Gyr bot-top
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Comparsion with CB07 (prelim)
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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 …
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