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FastBox

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Fast simulations of cosmological density fields, subject to anisotropic filtering, biasing, redshift-space distortions, foregrounds etc. This is intended to be a fast and simple simulator for post-EoR 21cm intensity maps and their cross-correlation with galaxy samples, with enough complexity to test realistic cosmological analysis methods.

Installation

To install fastbox, simply run python setup.py install. The following are required dependencies (all of which can be installed via pip):

  • numpy>=1.18
  • scipy>=1.5
  • matplotlib>=2.2
  • scikit-learn
  • pyccl

The following optional dependencies are needed for some of the foreground modelling and filtering functions to work:

  • healpy
  • lmfit
  • multiprocessing
  • GPy

Current features

  • Gaussian and log-normal density fields for any cosmology
  • Redshift-space transform, linear biasing etc
  • Arbitrary anisotropic filters as a function of kperp and kparallel
  • Poisson realisations of halo/galaxy samples
  • Radiometer noise and beam convolutions (FFT and direct convolution)
  • Several diffuse and point source foreground models, including GSM, Planck Sky Model, and the Battye et al. point source model.
  • Foreground filtering via PCA, ICA, Kernel PCA, least-squares etc.
  • Integration with the DESC Core Cosmology Library (pyccl)
  • Calculate power spectra, correlation functions, and their multipoles, via nbodykit
  • Detect and generate catalogues of cosmic voids

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Fast simulations of cosmological density fields, subject to anisotropic filters

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