Cosmology from large-scale galaxy clustering and galaxy-galaxy lensing with Dark Energy Survey Science Verification data

The DES Collaboration

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 deg2 contiguous patch of DES data from the Science Verification (SV) period of observations. Using large-scale measurements, we constrain the matter density of the Universe as Ω m = 0.31 ± 0.09 and the clustering amplitude of the matter power spectrum as σ8 = 0.74 ± 0.13 after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into S8 = σ8(Ωm/0.3)0.16 = 0.74 ± 0.12 for our fiducial lens redshift bin at 0.35 < z < 0.5, while S8 = 0.78 ± 0.09 using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck Cosmic Microwave Background data, baryon accoustic oscillations and Supernova Type Ia measurements.

Original languageEnglish (US)
Pages (from-to)4045-4062
Number of pages18
JournalMonthly Notices of the Royal Astronomical Society
Volume464
Issue number4
DOIs
StatePublished - 2017

Keywords

  • Cosmological parameters
  • Gravitational lensing: weak
  • Large-scale structure of Universe

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

Fingerprint Dive into the research topics of 'Cosmology from large-scale galaxy clustering and galaxy-galaxy lensing with Dark Energy Survey Science Verification data'. Together they form a unique fingerprint.

Cite this