CARDiAC

Code for Anisotropic Redshift Distributions in Angular Clustering

CARDiAC is a python code that computes the impact of anisotropic redshift distributions on a wide class of angular clustering observables, following Baleato Lizancos & White 2023.

At present, the code supports auto- and cross-correlations of galaxy samples and cosmic shear maps, including galaxy -galaxy lensing. The anisotropy can be present in the mean redshift and/or width of Gaussian distributions, as well as in the fraction of galaxies in each component of multi-modal distributions. Templates of these variations can be provided by the user or simulated internally within the code.

Installation

Dependencies:

numpy, scipy, matplotlib
astropy
healpy
py3nj
camb
numba for JIT compilation of galaxy lensing kernels, which are slow to compute otherwise

Optionally, galaxy-galaxy and galaxy-matter spectra can be obtained from a Lagrangian bias expansion using the anzu code if the user has it installed.

PyPI:

pip install cardiac==1.1.6

Editable installation in-place:

First, clone the repository

git clone https://github.com/abaleato/CARDiAC.git

and from within it run

python -m pip install -e .

Usage

See Tutorial.ipynb.

Attribution

If you use the code, please cite

@ARTICLE{2023JCAP...07..044B,
       author = {{Baleato Lizancos}, Ant{\'o}n and {White}, Martin},
        title = "{The impact of anisotropic redshift distributions on angular clustering}",
      journal = {\jcap},
     keywords = {cosmological parameters from LSS, power spectrum, Astrophysics - Cosmology and Nongalactic Astrophysics},
         year = 2023,
        month = jul,
       volume = {2023},
       number = {7},
          eid = {044},
        pages = {044},
          doi = {10.1088/1475-7516/2023/07/044},
archivePrefix = {arXiv},
       eprint = {2305.15406},
 primaryClass = {astro-ph.CO},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2023JCAP...07..044B},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}