COLOSSUS: A python toolkit for cosmology, large-scale structure, and dark matter halos

Abstract

This paper introduces Colossus, a public, open-source python package for calculations related to cosmology, the large-scale structure (LSS) of matter in the universe, and the properties of dark matter halos. The code is designed to be fast and easy to use, with a coherent, well-documented user interface. The cosmology module implements Friedman-Lemaitre-Robertson-Walker cosmologies including curvature, relativistic species, and different dark energy equations of state, and provides fast computations of the linear matter power spectrum, variance, and correlation function. The LSS module is concerned with the properties of peaks in Gaussian random fields and halos in a statistical sense, including their peak height, peak curvature, halo bias, and mass function. The halo module deals with spherical overdensity radii and masses, density profiles, concentration, and the splashback radius. To facilitate the rapid exploration of these quantities, Colossus implements more than 40 different fitting functions from the literature. I discuss the core routines in detail, with particular emphasis on their accuracy. Colossus is available at bitbucket.org/bdiemer/colossus.

13 pages, 6 figures. Moderate changes to match published version. Updated code available at https://bitbucket.org/bdiemer/colossus

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• Improving cosmological covariance matrices with machine learning
• Across the Universe: GW231123 as a magnified and diffracted black hole merger
• (Re)solving the Complex Multiscale Morphology and V-shaped Spectral Energy Distribution of a Newly Discovered Strongly Lensed Little Red Dot in A383
• Slow neutrinos: non-linearity and momentum-space emulation
• Detecting dark matter substructure with lensed quasars in optical bands
• Unveiling the evolution of the CO excitation ladder through cross-correlation of CONCERTO-like experiments and galaxy redshift surveys