a python package for boosting the cosmos!
Project description
CosmoBoost
CosmoBoost is a python package for Lorentz boosting anisotropic temperature and polarization maps in healpix format. The calculations are done in spherical harmonic space based on the relativistic Doppler and aberration kernel formalism developed in Yasini & Pierpaoli (2017) and Dai & Chluba (2014), following up on the original idea by Challinor & van Leeuwen (2002).
Currently the supported radiation types are:
- Cosmic Microwave Background (CMB)
- Kinetic Sunyaev Zeldovich (kSZ)
- Thermal Sunyaev Zeldovich (tSZ)
See the tutorial.ipynb notebook for an overview of the features through a set of examples.
Dependencies
Installation
You can install CosmoBoost from pypi using
pip install cosmoboost
Alternatively, you can clone the repository by running
git clone https://github.com/syasini/CosmoBoost.git
then move to the CosmoBoost directory
cd CosmoBoost
and run
python setup.py install --user
or use pip
pip install [-e] .
the -e argument will install the package in editable mode which is suitable for developement. If you want to modify the code use this option.
Example Session
CosmoBoost has a simple and user friendly interface. Simply import the package using
import cosmoboost as cb
Then load the default boosting parameters dictionary (beta = 0.00123, d=1, s=0, lmax= 1000, etc.)
pars = cb.DEFAULT_PARS
Instantiate the kernel object
kernel = cb.Kernel(pars)
Now simply boost a set of alm's (recommended) using
alm_boosted = cb.boost_alm(alm_rest, kernel)
or boost the power spectrum Cl directly
Cl_boosted = cb.boost_Cl(Cl_rest, kernel)
See the tutorial for a comprehensive example.
Acknowledgement
If you find the contents of this repository useful for your research, please consider citing the following papers:
@article{Yasini:2017jqg,
author = "Yasini, Siavash and Pierpaoli, Elena",
title = "{Generalized Doppler and aberration kernel for
frequency-dependent cosmological observables}",
journal = "Phys. Rev.",
volume = "D96",
year = "2017",
number = "10",
pages = "103502",
doi = "10.1103/PhysRevD.96.103502",
eprint = "1709.08298",
archivePrefix = "arXiv",
primaryClass = "astro-ph.CO",
SLACcitation = "%%CITATION = ARXIV:1709.08298;%%"
}
@article{Dai:2014swa,
author = "Dai, Liang and Chluba, Jens",
title = "{New operator approach to the CMB aberration kernels in
harmonic space}",
journal = "Phys. Rev.",
volume = "D89",
year = "2014",
number = "12",
pages = "123504",
doi = "10.1103/PhysRevD.89.123504",
eprint = "1403.6117",
archivePrefix = "arXiv",
primaryClass = "astro-ph.CO",
SLACcitation = "%%CITATION = ARXIV:1403.6117;%%"
}
The bibtex entries are copied from inspirehep.net.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file cosmoboost-1.1.6.tar.gz.
File metadata
- Download URL: cosmoboost-1.1.6.tar.gz
- Upload date:
- Size: 170.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.7.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9784cdda30b61dfc4ea9d2a84b266a39a4a675c92adf2d078f689c1be9ca1a29
|
|
| MD5 |
1236a74dd69abb292e6e7973b56c97c8
|
|
| BLAKE2b-256 |
4353e591925c7b6a475df64fea864e2adda999f8bbb30406578f755e14e2d933
|
File details
Details for the file cosmoboost-1.1.6-py3-none-any.whl.
File metadata
- Download URL: cosmoboost-1.1.6-py3-none-any.whl
- Upload date:
- Size: 328.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.7.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0532cb213647e1033d4bd98248c3e39400b648582e0773d5a0cb2f76994e65cb
|
|
| MD5 |
e3ebd038351c73eceffe7e7c28a5f423
|
|
| BLAKE2b-256 |
621a5957c56aeec1d1ca16d7d3112483de2414088c2b02ce820cc458d99606d8
|