Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 503, Issue 1, Pages 1149-1173Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stab510
Keywords
methods: numerical; catalogues; cosmology: large-scale structure of Universe
Categories
Funding
- SNF [200020 175751]
- ERC advanced grant LIDA
- P2IO LabEx [ANR-10-LABX-0038, ANR-11-IDEX-0003-01]
- Ohio State University Center for Cosmology and Particle Physics
- ANReBOSS project of the French National Research Agency [ANR-16-CE31-0021]
- National Research Foundation of Korea (NRF) - Korean Ministry of Education, Science and Technology (MoEST) [2017R1E1A1A01077508, 2020R1A2C1005655]
- Sejong University
- European Research Council through the COSFORM Research Grant [670193]
- National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility [DE-AC02-05CH11231]
- ICG
- SEPNet
- University of Portsmouth
- Alfred P. Sloan Foundation
- U.S. Department of Energy Office of Science
- Center for HighPerformance Computing at the University of Utah
- Brazilian Participation Group
- Carnegie Institution for Science
- Carnegie Mellon University
- Chilean Participation Group
- French Participation Group
- Harvard-Smithsonian Center for Astrophysics
- Instituto de Astrofisica de Canarias
- Johns Hopkins University
- Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo
- Korean Participation Group
- Lawrence Berkeley National Laboratory
- Leibniz Institut fur Astrophysik Potsdam (AIP)
- Max-Planck-Institut fur Astronomie (MPIA Heidelberg)
- Max-Planck-Institut fur Astrophysik (MPA Garching)
- Max-Planck-Institut fur Extraterrestrische Physik (MPE)
- National Astronomical Observatories of China
- New Mexico State University
- New York University
- University of Notre Dame
- Observatario Nacional/MCTI
- Ohio State University
- Pennsylvania State University
- Shanghai Astronomical Observatory
- United Kingdom Participation Group
- Universidad Nacional Autonoma de Mexico
- University of Arizona
- University of Colorado Boulder
- University of Oxford
- University of Utah
- University of Virginia
- University of Washington
- University of Wisconsin
- Vanderbilt University
- Yale University
- [ANR-17-CE31-0024-01]
Ask authors/readers for more resources
The study produced 1000 synthetic clustering catalogues to provide reliable estimates and test the robustness of the analysis of the Sloan Digital Sky Surveys data. By extending the Zel'dovich approximation density field with an effective tracer bias model, the researchers accurately reproduced the clustering statistics of the tracers in the redshift space.
We produce 1000 realizations of synthetic clustering catalogues for each type of the tracers used for the baryon acoustic oscillation and redshift space distortion analysis of the Sloan Digital Sky Surveys-IV extended Baryon Oscillation Spectroscopic Survey final data release (eBOSS DR16), covering the redshift range from 0.6 to 2.2, to provide reliable estimates of covariance matrices and test the robustness of the analysis pipeline with respect to observational systematics. By extending the Zel'dovich approximation density field with an effective tracer bias model calibrated with the clustering measurements from the observational data, we accurately reproduce the two- and three-point clustering statistics of the eBOSSDR16 tracers, including their cross-correlations in redshift space with very lowcomputational costs. In addition, we include the gravitational evolution of structures and sample selection biases at different redshifts, as well as various photometric and spectroscopic systematic effects. The agreements on the autoclustering statistics between the data and mocks are generally within 1 s variances inferred from the mocks, for scales down to a few h(-1) Mpc in configuration space, and up to 0.3 h Mpc(-1) in Fourier space. For the cross correlations between different tracers, the same level of consistency presents in configuration space, while there are only discrepancies in Fourier space for scales above 0.15 h Mpc(-1). The accurate reproduction of the data clustering statistics permits reliable covariances for multi-tracer analysis.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available