COBRA (Cosmology with Optimally factorized Bases for Rapid Approximation) rapidly computes large-scale structure observables, separating scale dependence from cosmological parameters in the linear matter power spectrum while also minimizing the number of necessary basis terms. This enables direct and efficient computation of derived and nonlinear observables. Moreover, the dependence on cosmological parameters is efficiently approximated using radial basis function interpolation. COBRA opens a new window for efficient computations of higher loop and higher order correlators involving multiple powers of the linear matter power spectra. The resulting factorization can also be utilied in clustering, weak lensing and CMB analyses.

OneCovariance calculates the covariance matrix of photometric large-scale structure surveys. It can produce the covariance matrix for all the 2-point statistics used within the Kilo-Degree-Survey (KiDS), including configuration space statistics, bandpowers, and COSEBIs. These observables are derived from projected Fourier space quantities. OneCovariance is flexible, in that it can read in the ingredients from a harmonic space covariance matrix and produce one of the mentioned statistics.

The Core Cosmology Library (CCL) computes basic cosmological observables and provides predictions 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. 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. Predictions for correlation functions of galaxy clustering, galaxy-galaxy lensing and cosmic shear are 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 written in C and has a python interface.