mata62n / rascalc

RascalC: A Fast Code for Galaxy Covariance Matrix Estimation

RascalC

A Rapid Sampler For Large Cross-Covariance Matrices in C++

C++ code to simulate correlation function covariance matrices from large surveys, using a grid and jackknife based approach. This can be used to find covariances of (a) the angularly binned anisotropic 2PCF, (b) the Legendre-binned anisotropic 2PCF and (c) the Legendre-binned isotropic 3PCF in arbitrary survey geometries. For (a) we can also compute the jackknife covariance matrix, which can be used to fit our non-Gaussianity model. There is additionally functionality to compute multi-tracer cross-covariances for the 2PCF.

For full usage, see the ReadTheDocs documentation.

Any usage of this code should cite Philcox et al. 2019 (for the angularly binned 2PCF) and Philcox & Eisenstein 2019 (for the Legendre-binned 2PCF and 3PCF).

New for version 2: Legendre moment covariances and the 3PCF

Authors

• Oliver Philcox (Princeton / Harvard)
• Daniel Eisenstein (Harvard)
• Ross O'Connell (Pittsburgh)
• Alexander Wiegand (Garching)

We thank Yuting Wang and Ryuichiro Hada for pointing out minor issues in the code and documentation.