This code implements the Gaussian Streaming Model using components from Convolution Lagrangian Effective Field Theory as described in:
Z.Vlah, E.Castorina, M.White
The Gaussian streaming model and Convolution Lagrangian effective field theory
JCAP 12(2016)007, [https://arxiv.org/abs/1609.02908]
The code is written (mostly) in C++. It can be run from the command line, or called from Python (wrappers provided).
The C++ version in "config2pt" currently only implements the configuration-space statistics (i.e. the correlation function). The Fortran routines in "ps_fortran" provide an implementation of the power spectrum routines.
We additionally provide fast and simple Python routines for computing the ZEFT, Halo-Zeldovich and GSM models' real-space auto- and cross-correlations of biased tracers as described in
C.Modi, M.White, Z.Vlah
Modeling CMB Lensing Cross Correlations with CLEFT
JCAP, 08(2017)009, [https://arxiv.org/abs/1706.03173]
This code is available in the HaloZeldovich and ps_python3 directories.