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[ascl:1505.016]
CUTE: Correlation Utilities and Two-point Estimation

CUTE (Correlation Utilities and Two-point Estimation) extracts any two-point statistic from enormous datasets with hundreds of millions of objects, such as large galaxy surveys. The computational time grows with the square of the number of objects to be correlated; technology provides multiple means to massively parallelize this problem and CUTE is specifically designed for these kind of calculations. Two implementations are provided: one for execution on shared-memory machines using OpenMP and one that runs on graphical processing units (GPUs) using CUDA.

[ascl:1704.007]
PySM: Python Sky Model

PySM generates full-sky simulations of Galactic foregrounds in intensity and polarization relevant for CMB experiments. The components simulated are thermal dust, synchrotron, AME, free-free, and CMB at a given Nside, with an option to integrate over a top hat bandpass, to add white instrument noise, and to smooth with a given beam. PySM is based on the large-scale Galactic part of Planck Sky Model code and uses some of its inputs.

[ascl:1901.003]
CCL: Core Cosmology Library

Chisari, Nora Elisa; Alonso, David; Krause, Elisabeth; Leonard, C. Daniellle; Bull, Philip; Neveu, Jérémy; Villarreal, Antonio; Singh, Sukhdeep; McClintock, Thomas; Ellison, John; Du, Zilong; Zuntz, Joe; Mead, Alexander; Joudaki, Shahab; Lorenz, Christiane S.; Troester, Tilman; Sanchez, Javier; Lanusse, Francois; Ishak, Mustapha; Hlozek, Renée; Blazek, Jonathan; Campagne, Jean-Eric; Almoubayyed, Husni; Eifler, Tim; Kirby, Matthew; Kirkby, David; Plaszczynski, Stéphane; Slosar, Anze; Vrastil, Michal; Wagoner, Erika L.

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.