Dark Energy Survey year 1 results: Galaxy clustering for combined probes

(Dark Energy Survey Collaboration)

Research output: Contribution to journalArticle

33 Scopus citations

Abstract

We measure the clustering of DES year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of 6.6×105 luminous red galaxies selected using the redMaGiC algorithm over an area of 1321 square degrees, in the redshift range 0.15<z<0.9, split into five tomographic redshift bins. The sample has a mean redshift uncertainty of σz/(1+z)=0.017. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample's robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto- and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be b(σ8/0.81)|z=0.24=1.40±0.07, b(σ8/0.81)|z=0.38=1.60±0.05, b(σ8/0.81)|z=0.53=1.60±0.04 for galaxies with luminosities L/L∗>0.5, b(σ8/0.81)|z=0.68=1.93±0.04 for L/L∗>1 and b(σ8/0.81)|z=0.83=1.98±0.07 for L/L∗>1.5, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

Original languageEnglish (US)
Article number042006
JournalPhysical Review D
Volume98
Issue number4
DOIs
StatePublished - Aug 15 2018

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy (miscellaneous)

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