hasasia 0.1.3

A Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.

hasasia

A Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.

حساسية (hasasia) is Arabic for sensitivity

• 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

0.1.2 (2019-06-23) 0.1.1 (2019-06-23) 0.1.0 (2019-06-23) ——————

• First release on PyPI.