The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey:a large sample of mock galaxy catalogues

By Marc Manera, R. Scoccimarro, Will J. Percival, L. Samushia, Cameron McBride, A. Ross, R. Sheth, M. White, B. Reid, Ariel G. Sánchez and 10 more. 2012

257 citations recorded by the source corpus.

We present a fast method for producing mock galaxy catalogues that can be used to compute the covariance of large-scale clustering measurements and test analysis techniques. Our method populates a second-order Lagrangian perturbation theory (2LPT) matter field, where we calibrate masses of dark matter haloes by detailed comparisons with N-body simulations. We demonstrate that the clustering of haloes is recovered at ∼10 per cent accuracy. We populate haloes with mock galaxies using a halo occupation distribution (HOD) prescription, which has been calibrated to reproduce the clustering measurements on scales between 30 and 80 h−1 Mpc. We compare the sample covariance matrix from our mocks with analytic estimates, and discuss differences. We have used this method to make catalogues corresponding to Data Release 9 of the Baryon Oscillation Spectroscopic Survey (BOSS), producing 600 mock catalogues of the ‘CMASS’ galaxy sample. These mocks have enabled detailed tests of methods and errors, and have formed an integral part of companion analyses of these galaxy data.

Subfields: Astronomy and Astrophysics, Ecology, Instrumentation

View Paper: https://www.semanticscholar.org/paper/711b222f869c569f8d5013d0a9dd837371a29fc7

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Citations in the corpus

The power spectrum and bispectrum of SDSS DR11 BOSS galaxies – I. Bias and gravity (2014, methodology): “This is the galaxy catalogue presented in Manera et al. (2013) based on PTHALOS.”
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: Measuring growth rate and geometry with anisotropic clustering (2013, methodology): “The validity of our second assumption is helped by the fact that the signal-to-noise ratio is high and the mock catalogues were tuned to reproduce the observed clustering of CMASS sample on average (see Manera et al. 2013, for details).”
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Cosmological implications of the configuration-space clustering wedges (2016, methodology): “The values of the parameters characterizing this HOD are similar to those used by Manera et al. (2013), but the mass resolution of the MINERVA simulations allows us to resolve the haloes of the low-mass tail of the distribution.”
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: mock galaxy catalogues for the BOSS Final Data Release (2015, methodology): “A few pioneering works explored a viable strategy more than a decade ago relying on simplified fast gravity solvers using perturbation theory (PT): PINOCCHIO (Monaco et al. 2002, 2013) and PTHALOS (Scoccimarro & Sheth 2002).”
Modelling baryon acoustic oscillations with perturbation theory and stochastic halo biasing (2013, background): “A number of approaches has been proposed in the literature for the generation of mock galaxy cataloguesbased on Lagrangian Perturbation Theory (LPT), such as PINOCCHIO (Monaco et al. 2002, 2013) or PTHALOS (Scoccimarro & Sheth 2002; Manera et al. 2013).”
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: single-probe measurements and the strong power of f(z)σ8(z) on constraining dark energy (2013, methodology): “We use the 600 mock catalogues created by Manera et al. (2013) for the BOSS CMASS DR9 to estimate the covariance matrix of the observed correlation function.”
The clustering of Galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: including covariance matrix errors (2013, methodology): “The low amplitude of the systematic errors post-reconstruction strongly suggests that we do not have any systematic biases due to the survey mask, our modelling of the resulting window function, or effects from the galaxy bias as implemented within the PTHaloe methodology (Manera et al. 2013).”
The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: modelling the clustering and halo occupation distribution of BOSS CMASS galaxies in the Final Data Release (2015, methodology): “We use the periodic boundary conditions to maximize the use of the volume (Manera et al. 2013), but we do not reuse any region of the box.”
The MICE Grand Challenge lightcone simulation – II. Halo and galaxy catalogues (2013, methodology): “We stress however that our galaxy catalogue is not intended to reproduce one given galaxy population, as typically needed for spectroscopic surveys (e.g. the CMASS sample for BOSS in Manera et al. 2013; White, Tinker & McBride 2014).”
The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: First measurement of baryon acoustic oscillations between redshift 0.8 and 2.2 (2017, result): “Our approach in this respect is similar to previous BOSS analyses (Manera et al. 2013; Anderson et al. 2014; Alam et al. 2017).”
Improved WiggleZ Dark Energy Survey Distance Measurements to z = 1 with Reconstruction of the Baryonic Acoustic Feature (2014, unknown): “In our ﬁrst attempt to build mock catalogues, we tried implementing the second-order Lagrangian Perturbation Theory method (Bernardeau et al. 2002), as described in Manera et al. (2013).”
Mock galaxy catalogues using the quick particle mesh method (2013, methodology): “…the frozen flow approximation [Matarrese et al. 1992]; the free-particle approximation [Short & Coles 2006]; PThalos [Scoccimarro & Sheth 2002; Manera et al. 2013]; Pinocchio [Monaco, Theuns & Taffoni 2002; Monaco et al. 2013]; remapping Lagrangian perturbation theory [LPT; Leclercq et al.…”
The clustering of the SDSS main galaxy sample – II. Mock galaxy catalogues and a measurement of the growth of structure from redshift space distortions at z = 0.15 (2014, methodology): “Recent analyses of BOSS have emphasized the importance of accurate mock catalogues (Manera et al. 2013, 2015); these provide both a mechanism to test analysis pipelines and to determine covariances for the measurements made.”