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https://github.com/hazboun6/pta_forecasts

Various codes used to forecast the sensitivities of PTAs.

https://github.com/hazboun6/pta_forecasts

Science Score: 10.0%

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    Low similarity (6.4%) to scientific vocabulary
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Various codes used to forecast the sensitivities of PTAs.

Basic Info
  • Host: GitHub
  • Owner: Hazboun6
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 131 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 3
  • Open Issues: 0
  • Releases: 0
Created over 5 years ago · Last pushed over 5 years ago

https://github.com/Hazboun6/pta_forecasts/blob/master/ 

# pta_forecasts

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1TvgfOk61pMaq0RHSKUEczftLJyf6TFuc?usp=sharing)

These notebooks reproduce the PTA forecasts from:

[_Xin, Mingarelli and Hazboun, 2020. "Multimessenger pulsar timing array constraints on supermassive black hole binaries traced by periodic light curves"_](https://arxiv.org/abs/2009.11865)

They use the Python package [`Hasasia`](https://hasasia.readthedocs.io/en/latest/) developed to produce sensitivity curves and skymaps for pulsar timing arrays. The notebook that makes the various forecasted PTA products can be accessed in Google Colab, via the badge above. 

The simulated PTAs are made by pulling parameters from various empirical distributions based on current and forecasted PTA propertires, hence they are realization dependent. The exact versions used in the paper are included in the repo, except for the IPTA 2025 forecasted PTA which can be downloaded via this [link](https://drive.google.com/file/d/1QBKYSyhh1dRWp9qm-K5Mk2JBX3PIP92z/view?usp=sharing). Of particular interest are the __SKA1__ and __SKA2__ sky maps which are based on a PTA using the first generation of SKA millisecond pulsars __and__ the long baseline datasets of current PTA experiments forecasted into the SKA era.

Owner

  • Name: Jeff Hazboun
  • Login: Hazboun6
  • Kind: user

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