=========== hasasia

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

.. image:: https://raw.githubusercontent.com/Hazboun6/hasasia/master/hasasia_calligraphy.jpg :align: center

حساسية (hasasia) is Arabic for sensitivity_ . Image Credit: Reem Tasyakan

.. _sensitivity: https://translate.google.com/#view=home&op=translate&sl=auto&tl=ar&text=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.

.. code-block:: python

import hasasia.sensitivity 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 the formalism used in this work please use the following attribution:

.. _publication: https://arxiv.org/pdf/1907.04341.pdf

.. code-block:: tex

@article{Hazboun:2019vhv, author = {{Hazboun}, Jeffrey S. and {Romano}, Joseph D. and {Smith}, Tristan L.}, title = "{Realistic sensitivity curves for pulsar timing arrays}", journal = {\prd}, keywords = {General Relativity and Quantum Cosmology, Astrophysics - Instrumentation and Methods for Astrophysics}, year = 2019, month = nov, volume = {100}, number = {10}, eid = {104028}, pages = {104028}, doi = {10.1103/PhysRevD.100.104028}, archivePrefix = {arXiv}, eprint = {1907.04341}, primaryClass = {gr-qc}, adsurl = {https://ui.adsabs.harvard.edu/abs/2019PhRvD.100j4028H}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }

Otherwise if you would like to reference the Python package use the following citation:

.. code-block:: tex

@article{Hazboun2019Hasasia, journal = {Journal of Open Source Software}, doi = {10.21105/joss.01775}, issn = {2475-9066}, number = {42}, publisher = {The Open Journal}, title = {Hasasia: A Python package for Pulsar Timing Array Sensitivity Curves}, url = {http://dx.doi.org/10.21105/joss.01775}, volume = {4}, author = {Hazboun, Jeffrey and Romano, Joseph and Smith, Tristan}, pages = {1775}, date = {2019-10-23}, year = {2019}, month = {10}, day = {23}, }

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.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage