Publications

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Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

This paper combines DES Y1 measurements of galaxy clustering, galaxy-galaxy lensing, and weak lensing cosmic shear to derive constraints on cosmological parameters, compares with measurements from other experiments, and combines with external data to obtain stringent constraints. For more information, please contact the DES collaboration (des-publication-queries@fnal.gov).

Dark Energy Survey Year 1 Results: Weak Lensing Shape Catalogues

This paper presents galaxy shape catalogues for the DES Y1 weak lensing measurements, using two independent shear measurement pipelines, Metacalibration and im3shape. These measurements are used in the Cosmic Shear analysis (Troxel, et al) and the Galaxy-galaxy lensing analysis (Prat, et al). For more information, please contact Joe Zuntz (joe.zuntz@ed.ac.uk) or Erin Sheldon (erin.sheldon@gmail.com).

Dark Energy Survey Year 1 Results: Galaxy clustering for combined probes

This paper presents measurements of the spatial clustering of 660,000 red galaxies in 5 redshift bins and demonstrates robustness of the results against systematic errors. This is one of the 3 measurements used in “Cosmological Constraints from Galaxy Clustering and Weak Lensing.” For more information, please contact Jack Elvin-Poole (jack.elvin-poole@postgrad.manchester.ac.uk).

Dark Energy Survey Year 1 Results: Curved-Sky Weak Lensing Mass Map

Using slight distortions of the shapes of 26 million distant galaxies due to weak gravitational lensing, DES scientists have constructed a map of the projected density of dark matter that spans several billion light years. For more information, contact Chihway Chang (chihway@kicp.uchicago.edu).

Dark Energy Survey Year 1 Results: Redshift distributions of the weak lensing source galaxies

This paper describes the derivation and validation of the distribution of redshifts for the source galaxies used in the DES Y1 weak lensing measurements. For more information, please contact Ben Hoyle (hoyleb@usm.uni-muenchen.de) or Daniel Gruen (dgruen@stanford.edu).