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Title: Dark Energy Survey Year 1 Results: galaxy mock catalogues for BAO

Abstract

Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimisation of analysis methodology and validation of data sets. In this paper, we present a set of 1800 galaxy mock catalogues designed to match the Dark Energy Survey Year-1 BAO sample (Crocce et al. 2017) in abundance, observational volume, redshift distribution and uncertainty, and redshift dependent clustering. The simulated samples were built upon HALOGEN (Avila et al. 2015) halo catalogues, based on a $2LPT$ density field with an exponential bias. For each of them, a lightcone is constructed by the superposition of snapshots in the redshift range $0.45

Authors:
;
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Contributing Org.:
DES
OSTI Identifier:
1431578
Report Number(s):
arXiv:1712.06232; FERMILAB-PUB-17-587; IFT-UAM-CSIC-17-124; DES-2017-0292
1643782
DOE Contract Number:
AC02-07CH11359
Resource Type:
Journal Article
Resource Relation:
Journal Name: Mon.Not.Roy.Astron.Soc.
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS

Citation Formats

Avila, S., and et al. Dark Energy Survey Year 1 Results: galaxy mock catalogues for BAO. United States: N. p., 2017. Web.
Avila, S., & et al. Dark Energy Survey Year 1 Results: galaxy mock catalogues for BAO. United States.
Avila, S., and et al. Sun . "Dark Energy Survey Year 1 Results: galaxy mock catalogues for BAO". United States. doi:. https://www.osti.gov/servlets/purl/1431578.
@article{osti_1431578,
title = {Dark Energy Survey Year 1 Results: galaxy mock catalogues for BAO},
author = {Avila, S. and et al.},
abstractNote = {Mock catalogues are a crucial tool in the analysis of galaxy surveys data, both for the accurate computation of covariance matrices, and for the optimisation of analysis methodology and validation of data sets. In this paper, we present a set of 1800 galaxy mock catalogues designed to match the Dark Energy Survey Year-1 BAO sample (Crocce et al. 2017) in abundance, observational volume, redshift distribution and uncertainty, and redshift dependent clustering. The simulated samples were built upon HALOGEN (Avila et al. 2015) halo catalogues, based on a $2LPT$ density field with an exponential bias. For each of them, a lightcone is constructed by the superposition of snapshots in the redshift range $0.45},
doi = {},
journal = {Mon.Not.Roy.Astron.Soc.},
number = ,
volume = ,
place = {United States},
year = {Sun Dec 17 00:00:00 EST 2017},
month = {Sun Dec 17 00:00:00 EST 2017}
}