DESI mock challenge: Halo and galaxy catalogues with the bias assignment method

Journal Article · Thu May 18 00:00:00 EDT 2023 · Astronomy and Astrophysics

DOI:https://doi.org/10.1051/0004-6361/202245618· OSTI ID:2212459

Balaguera-Antolínez, Andrés  ^[1]; Kitaura, Francisco-Shu ^[1]; Alam, Shadab ^[2]; Chuang, Chia-Hsun ^[3]; Yu, Yu ^[4]; Favole, Ginevra ^[1]; Sinigaglia, Francesco ^[5]; Zhao, Cheng ^[6]; Brooks, David ^[7]; de la Macorra, Axel ^[8]; Font-Ribera, Andreu ^[9]; Gontcho A Gontcho, Satya ^[10]; Honscheid, Klaus ^[11]; Kehoe, Robert ^[12]; Meisner, Aron ^[13]; Miquel, Ramon ^[14]; Tarlé, Gregory ^[15]; Vargas-Magaña, Mariana ^[8]; Zhou, Zhimin ^[16]

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1. Instituto de Astrofísica de Canarias, La Laguna (Spain); Universidad de La Laguna (Spain)
2. University of Edinburgh, Scotland (United Kingdom). The Royal Observatory; Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai (India)
3. Stanford University, CA (United States)
4. Shanghai Jiao Tong University (China)
5. Instituto de Astrofísica de Canarias, La Laguna (Spain); Universidad de La Laguna (Spain); Università degli Studi di Padova (Italy)
6. Ecole Polytechnique Federale Lausanne (EPFL) (Switzerland)
7. University College London (United Kingdom)
8. Universidad Nacional Autónoma de México, Ciudad de México (México)
9. Universitat Autonoma de Barcelona (Spain)
10. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
11. The Ohio State University, Columbus, OH (United States)
12. Southern Methodist University, Dallas, TX (United States)
13. NSF’s NOIRLab, Tucson, AZ (United States)
14. Universitat Autonoma de Barcelona (Spain); Institució Catalana de Recerca i Estudis Avançats, Barcelona (Spain)
15. University of Michigan, Ann Arbor, MI (United States)
16. Chinese Academy of Sciences (CAS), Beijing (China)

We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. We aim to produce mock galaxy catalogues capable of generating accurate covariance matrices for a number of cosmological probes that are expected to be measured in current and forthcoming galaxy redshift surveys (e.g. two- and three-point statistics). The construction of the catalogues shown in this paper is part of a mock-comparison project within the Dark Energy Spectroscopic Instrument (DESI) collaboration. We use the bias assignment method (BAM) to model the statistics of halo distribution through a learning algorithm using a few detailed N-body simulations, and approximated gravity solvers based on Lagrangian perturbation theory. We introduce cosmic-web-dependent corrections to modelling redshift-space distortions at the N-body level – both in the halo and galaxy distributions –, as well as a multi-scale approach for accurate assignment of halo properties. Using specific models of halo occupation distributions to populate halos, we generate galaxy mocks with the expected number density and central-satellite fraction of emission-line galaxies, which are a key target of the DESI experiment. BAM generates mock catalogues with per cent accuracy in a number of summary statistics, such as the abundance, the two- and three-point statistics of halo distributions, both in real and redshift space. In particular, the mock galaxy catalogues display ~3%-10% accuracy in the multipoles of the power spectrum up to scales of k ~ 0.4 h^-1Mpc. We show that covariance matrices of two- and three-point statistics obtained with BAM display a similar structure to the reference simulation. BAM offers an efficient way to produce mock halo catalogues with accurate two- and three-point statistics and is able to generate a variety of multi-tracer catalogues with precise covariance matrices of several cosmological probes. We discuss future developments of the algorithm towards mock production in DESI and other galaxy-redshift surveys.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); National Science Foundation (NSF)
• Grant/Contract Number: AC02-05CH11231; AST-0950945
• OSTI ID: 2212459
• Journal Information: Astronomy and Astrophysics, Vol. 673; ISSN 0004-6361
• Publisher: EDP Sciences
• Country of Publication: United States
• Language: English

Related Subjects

79 ASTRONOMY AND ASTROPHYSICS
methods: numerical
Galaxy: halo
galaxies: statistics