Accurate halo-galaxy mocks from automatic bias estimation and particle mesh gravity solvers

Abstract

Reliable extraction of cosmological information from clustering measurements of galaxy surveys requires estimation of the error covariance matrices of observables. The accuracy of covariance matrices is limited by our ability to generate sufficiently large number of independent mock catalogs that can describe the physics of galaxy clustering across a wide range of scales. Furthermore, galaxy mock catalogs are required to study systematics in galaxy surveys and to test analysis tools. In this investigation, we present a fast and accurate approach for generation of mock catalogs for the upcoming galaxy surveys. Our method relies on low-resolution approximate gravity solvers to simulate the large scale dark matter field, which we then populate with halos according to a flexible nonlinear and stochastic bias model. In particular, we extend the \textsc{patchy} code with an efficient particle mesh algorithm to simulate the dark matter field (the \textsc{FastPM} code), and with a robust MCMC method relying on the \textsc{emcee} code for constraining the parameters of the bias model. Using the halos in the BigMultiDark high-resolution $N$-body simulation as a reference catalog, we demonstrate that our technique can model the bivariate probability distribution function (counts-in-cells), power spectrum, and bispectrum of halos in the reference catalog. Specifically, we show that the new ingredients permit us to reach percentage accuracy in the power spectrum up to $k\sim 0.4h{\mathrm{Mpc}}^{-1}$ (within 5\% up to $k\sim 0.6h{\mathrm{Mpc}}^{-1}$) with accurate bispectra improving previous results based on Lagrangian perturbation theory.

12 pages, 4 figures, published version

References in corpus (15)

• Wide-Field InfrarRed Survey Telescope-Astrophysics Focused Telescope Assets WFIRST-AFTA 2015 Report
• Why your model parameter confidences might be too optimistic -- unbiased estimation of the inverse covariance matrix
• Nonlinear shrinkage estimation of large-dimensional covariance matrices
• The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: RSD measurement from the power spectrum and bispectrum of the DR12 BOSS galaxies
• `Eppur Si Muove': On The Motion of the Acoustic Peak in the Correlation Function
• Detection of Baryon Acoustic Oscillation Features in the Large-Scale 3-Point Correlation Function of SDSS BOSS DR12 CMASS Galaxies
• nIFTy Cosmology: Galaxy/halo mock catalogue comparison project on clustering statistics
• Constraining the halo bispectrum in real and redshift space from perturbation theory and non-linear stochastic bias
• Shrinkage Estimation of the Power Spectrum Covariance Matrix
• Bayesian inference of cosmic density fields from non-linear, scale-dependent, and stochastic biased tracers
• Constraining the Baryon-Dark Matter Relative Velocity with the Large-Scale 3-Point Correlation Function of the SDSS BOSS DR12 CMASS Galaxies
• Non-linear shrinkage estimation of large-scale structure covariance
• Nonlinear Bias of Cosmological Halo Formation in the Early Universe
• sCOLA: The N-body COLA Method Extended to the Spatial Domain
• Galaxy Three-Point Correlation Functions and Halo/Subhalo Models

Cited by in corpus (13)

• The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: 1000 multi-tracer mock catalogues with redshift evolution and systematics for galaxies and quasars of the final data release
• Comparing approximate methods for mock catalogues and covariance matrices I: correlation function
• Comparing approximate methods for mock catalogues and covariance matrices III: Bispectrum
• Inflation and Early Dark Energy with a Stage II Hydrogen Intensity Mapping Experiment
• BAM: Bias Assignment Method to generate mock catalogs
• The bias of dark matter tracers: assessing the accuracy of mapping techniques
• Bayesian cosmic density field inference from redshift space dark matter maps
• One simulation to have them all: performance of the Bias Assignment Method against N-body simulations
• The cosmic web connection to the dark matter halo distribution through gravity
• Robustness of the covariance matrix for galaxy clustering measurements
• $\text{PineTree}$: A generative, fast, and differentiable halo model for wide-field galaxy surveys
• Study on the mapping of halo clustering from real space to redshift space
• Fast simulation mapping: from standard to modified gravity cosmologies using the bias assignment method