M. Gatti

Density Split Statistics: Cosmological Constraints from Counts and Lensing in Cells in DES Y1 and SDSS Data

NASA through Einstein Postdoctoral Fellowship - Chandra X-ray Center [PF5-160138]; NASA [NAS8-03060]; Deutsche Forschungsgemeinschaft (DFG) [SFB-Transregio 33]; DFG Cluster of Excellence Origin and Structure of the Universe; U.S. Department of Energy; U.S. National Science Foundation; Ministry of Science and Education of Spain; Science and Technology Facilities Council of the United Kingdom; Higher Education Funding Council for England; National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign; Kavli Institute of Cosmological Physics at the University of Chicago; Center for Cosmology and Astro-Particle Physics at the Ohio State University; Mitchell Institute for Fundamental Physics and Astronomy at Texas AM University; Financiadora de Estudos e Projetos; Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia; Tecnologia e Inovacao; Deutsche Forschungsgemeinschaft; Collaborating Institutions in the Dark Energy Survey; Argonne National Laboratory; University of California at Santa Cruz; University of Cambridge; Centro de Investigaciones Energeticas; Medioambientales y Tecnologicas-Madrid; University of Chicago; University College London; DES-Brazil Consortium; University of Edinburgh; Eidgenossische Technische Hochschule (ETH) Zurich; Fermi National Accelerator Laboratory; University of Illinois at Urbana-Champaign; Institut de Ciencies de lEspai (IEEC/CSIC); Institut de Fisica dAltes Energies; Lawrence Berkeley National Laboratory; Ludwig-Maximilians Universitat Munchen; Excellence Cluster Universe; University of Michigan; National Optical Astronomy Observatory; University of Nottingham; Ohio State University; University of Pennsylvania; University of Portsmouth; SLAC National Accelerator Laboratory; Stanford University; University of Sussex; Texas AM University; OzDES Membership Consortium; National Science Foundation [AST-1138766, AST-1536171]; MINECO [AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV-2012-0234, SEV-2016-0597, MDM-2015-0509]; ERDF funds from the European Union; CERCA program of the Generalitat de Catalunya; European Research Council under the European Unions Seventh Framework Program (FP7); ERC [240672, 291329, 306478]; Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO) [CE110001020]; Fermi Research Alliance, LLC [DE-AC02-07CH11359]; U.S. Department of Energy, Office of Science, Office of High Energy Physics

Cross-correlation redshift calibration without spectroscopic calibration samples in DES Science Verification Data

Galaxy cross-correlations with high-fidelity redshift samples hold the potential to precisely calibrate systematic photometric redshift uncertainties arising from the unavailability of complete and representative training and validation samples of galaxies. However, application of this technique in the Dark Energy Survey (DES) is hampered by the relatively low number density, small area, and modest redshift overlap between photometric and spectroscopic samples. We propose instead using photometric catalogues with reliable photometric redshifts for photo-z calibration via cross-correlations. We verify the viability of our proposal using redMaPPer clusters from the Sloan Digital Sky Survey (SDSS) to successfully recover the redshift distribution of SDSS spectroscopic galaxies.We demonstrate how to combine photo-z with cross-correlation data to calibrate photometric redshift biases while marginalizing over possible clustering bias evolution in either the calibration or unknown photometric samples. We apply our method to DES Science Verification (DES SV) data in order to constrain the photometric redshift distribution of a galaxy sample selected for weak lensing studies, constraining the mean of the tomographic redshift distributions to a statistical uncertainty of Δz ~ ±0.01. We forecast that our proposal can, in principle, control photometric redshift uncertainties in DES weak lensing experiments at a level near the intrinsic statistical noise of the experiment over the range of redshifts where redMaPPer clusters are available. Our results provide strong motivation to launch a programme to fully characterize the systematic errors from bias evolution and photo-z shapes in our calibration procedure.

Dark Energy Survey Year 1 Results: calibration of redMaGiC redshift distributions in DES and SDSS from cross-correlations

We present calibrations of the redshift distributions of redMaGiC galaxies in the Dark Energy Survey Year 1 (DES Y1) and Sloan Digital Sky Survey (SDSS) DR8 data. These results determine the priors of the redshift distribution of redMaGiC galaxies, which were used for galaxy clustering measurements and as lenses for galaxy-galaxy lensing measurements in DES Y1 cosmological analyses. We empirically determine the bias in redMaGiC photometric redshift estimates using angular cross-correlations with Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. For DES, we calibrate a single-parameter redshift bias in three photometric redshift bins: z is an element of [0.15, 0.3], [0.3,0.45], and [0.45,0.6]. Our best-fit results in each bin give photometric redshift biases of vertical bar Delta z vertical bar < 0.01. To further test the redMaGiC algorithm, we apply our calibration procedure to SDSS redMaGiC galaxies, where the statistical precision of the cross-correlation measurement is much higher due to a greater overlap with BOSS galaxies. For SDSS, we also find best-fit results of vertical bar Delta z vertical bar < 0.01. We compare our results to other analyses of redMaGiC photometric redshifts.