| Name | cardiac JSON |
| Version |
1.1.6
JSON |
| download |
| home_page | None |
| Summary | Code for Anisotropic Redshift Distributions in Angular Clustering |
| upload_time | 2024-03-27 00:51:43 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | None |
| keywords |
feed
reader
tutorial
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# CARDiAC
**C**ode for **A**nisotropic **R**edshift **D**istributions **i**n **A**ngular **C**lustering
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](https://arxiv.org/abs/2305.15406).
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
The code can be installed simply by running
python -m pip install
###### 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.
## Usage
See `Tutorial.ipynb` at [the code's repository](https://github.com/abaleato/CARDiAC) on Github.
## Attribution
If you use the code, please cite [Baleato Lizancos & White 2023](https://arxiv.org/abs/2305.15406).
Raw data
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