A Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.
Project description
hasasia
A Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.
حساسية (hasasia) is Arabic for sensitivity . Image Credit: Reem Tasyakan
Free software: MIT license
Documentation: https://hasasia.readthedocs.io.
Features
Calculates the following structures needed for signal analysis with pulsars:
Pulsar transmission functions
Inverse-noise-weighted transmission functions
Individual pulsar sensitivity curves.
Pulsar timing array sensitivity curves as characteristic strain, strain sensitivity or energy density.
Power-law integrated sensitivity curves.
Sensitivity sky maps for pulsar timing arrays
Getting Started
hasasia is on the Python Package Inventory, so the easiest way to get started is by using pip to install:
pip install hasasia
The pulsar and spectrum objects are used to build sensitivity curves for full PTAs. The Spectrum object has all of the information needed for the pulsar.
import hasasia.senstivity as hsen
toas = np.arange(54378,59765,22) #Choose a range of times-of-arrival
toaerrs = 1e-7*np.ones_like(toas) #Set all errors to 100 ns
psr = hsen.Pulsar(toas=toas,toaerrs=toaerrs)
spec = hsen.Spectrum(psr)
Publication
This work is featured in a publication, currently released on the arXiv. If you would like to reference this work please use the following attribution:
@article{Hazboun:2019vhv,
author = "Hazboun, Jeffrey S. and Romano, Joseph D. and Smith, Tristan L.",
title = "{Realistic sensitivity curves for pulsar timing arrays}",
year = "2019",
eprint = "1907.04341",
archivePrefix = "arXiv",
primaryClass = "gr-qc",
SLACcitation = "%%CITATION = ARXIV:1907.04341;%%"
}
Credits
Development Team: Jeffrey S. Hazboun, Joseph D. Romano and Tristan L. Smith
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.1.6 (2019-08-30) 0.1.6 (2019-08-29) 0.1.5 (2019-08-13) 0.1.4 (2019-08-13) 0.1.3 (2019-08-13) 0.1.2 (2019-06-23) 0.1.1 (2019-06-23) 0.1.0 (2019-06-23)* ——————
First release on PyPI.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.