Comparing approximate methods for mock catalogues and covariance matrices II: power spectrum multiples

Linda Blot, Martin Crocce, Emiliano Sefusatti, Martha Lippich, Ariel G. Sánchez, Manuel Colavincenzo, Pierluigi Monaco, Marcelo A. Alvarez, Aniket Agrawal, Santiago Avila, Andrés Balaguera-Antolínez, Richard Bond, Sandrine Codis, Claudio Dalla Vecchia, Antonio Dorta, Pablo Fosalba, Albert Izard, Francisco-Shu Kitaura, Marcos Pellejero-Ibanez, George SteinMohammadjavad Vakili, Gustavo Yepes

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We study the accuracy of several approximate methods for gravitational dynamics in terms of halo power spectrum multipoles and their estimated covariance matrix. We propagate the differences in covariances into parameter constraints related to growth rate of structure, Alcock–Paczynski distortions, and biasing. We consider seven methods in three broad categories: algorithms that solve for halo density evolution deterministically using Lagrangian trajectories (ICE–COLA, PINOCCHIO, and PEAKPATCH), methods that rely on halo assignment schemes on to dark matter overdensities calibrated with a target N-body run (HALOGEN, PATCHY), and two standard assumptions about the full density probability distribution function (Gaussian and lognormal). We benchmark their performance against a set of three hundred N-body simulations, running similar sets of approximate simulations with matched initial conditions, for each method. We find that most methods reproduce the monopole to within 5 per cent⁠, while residuals for the quadrupole are sometimes larger and scale dependent. The variance of the multipoles is typically reproduced within 10 per cent⁠. Overall, we find that covariances built from approximate simulations yield errors on model parameters within 10 per cent of those from the N-body-based covariance.
Original languageEnglish
Pages (from-to)2806-2824
Number of pages19
JournalMonthly Notices of the Royal Astronomical Society
Issue number2
Early online date19 Feb 2019
Publication statusPublished - 1 May 2019


  • astro-ph.CO
  • RCUK
  • STFC
  • ST/K00283X/1
  • methods: data analysis
  • methods: numerical
  • cosmological parameters
  • large-scale structure of Universe


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