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.
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
- 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