https://github.com/grburgess/pyipn

A time-delayed light curve simulation code for GRB location triangulation via random Fourier features.
https://github.com/grburgess/pyipn

astronomy bayesian-inference grb ipn localization multi-messenger poisson-process random-fourier-features stan time-series-analysis

Last synced: 30 days ago
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A time-delayed light curve simulation code for GRB location triangulation via random Fourier features.

• Host: GitHub
• URL: https://github.com/grburgess/pyipn
• Owner: grburgess
• License: gpl-3.0
• Created: 2019-04-24T15:38:18.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2021-06-17T09:42:02.000Z (over 3 years ago)
• Last Synced: 2024-07-30T19:28:15.055Z (5 months ago)
• Topics: astronomy, bayesian-inference, grb, ipn, localization, multi-messenger, poisson-process, random-fourier-features, stan, time-series-analysis
• Language: Python
• Homepage:
• Size: 47.6 MB
• Stars: 7
• Watchers: 3
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: docs/contributing.rst
  • License: LICENSE

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# pyipn

![alt text](https://raw.githubusercontent.com/grburgess/pyipn/master/logo.png)

PyIPN is a tool for simulating GRB light curves observed by gamma-ray detectors dispersed throughout the Universe (theorectically, but mostly in the Sol system). 

The sister fitting code that recovers the time-delays and localizations of the simulated GRBs is [Nazgul](https://github.com/grburgess/nazgul). 

This work is built upon the classical [InterPlanetary Network (IPN)](http://www.ssl.berkeley.edu/ipn3/) developed to do source tringulation via cross-corelation of the observed light curves. 

---

This work is a joint effort by:

* J. Michael Burgess

* Ewan Cameron

* Dmitry Svinkin

---

If you find this work useful, please cite  our paper [here](https://arxiv.org/abs/2009.08350)

## Install

```bash

$> pip install pyipn

```