hazboun6 / hasasia

Python package for calculating pulsar timing array sensitivity curves.

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.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:

@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:

@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.

hasasia's Issues

add PSR name property to Spectrum

It would be helpful to have more useful metadata bundled in the hasasia.Spectrum object. This would make it easier to save and reuse spectra by pickling a list of hasasia.Spectrum objects.

In particular for plotting and sorting, the tutorials zip lists of hasasia.Pulsar objects and hasasia.Spectrum objects together for loops in order to get the Pulsar.name. A name property could be added to the spectrum at creation. Other metadata may be helpful too.

Deterministic SNR

Suggestions for Improvement

Include functionality for using SNR with deterministic case using equation 76 in the arxiv version of the paper.