Core Cosmology Library: Precision Cosmological Predictions for LSST
arxiv:1812.05995
Published:
Published in: ApJS
Abstract:
The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias, and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for the Large Synoptic Survey Telescope (LSST) are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows us to establish a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, galaxy─galaxy lensing, and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a Python interface and publicly available at https://github.com/LSSTDESC/CCL.
Summary
This is the paper published to describe the Core Cosmology Library (CCL) created by members of the LSST Dark Energy Science Collaboration (DESC). It is also the paper to reference for any paper that uses CCL.
Contribution
I am on the author list because I contributed to the code before it was published. As discussed on my page for the CCL code, I helped to resolve an issue during a hack session at the DESC collaboration meeting in July 2017.
Recommended Citation
Nora Elisa Chisari et al.
2019,
ApJS
242, 2
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