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Jupyter Notebooks and Data used in the discovery of an exocomet around the star beta Pictoris
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betaPic_movies
frequency_analysis
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README.md

README.md

A transiting exocomet detected in broadband light by TESS in the β Pictoris system

Contents

This repository containts various files, which were used for the paper Zieba et al. (2019).

This repository containts the following folders:

Contains the Jupyter Notebook with was used for the MCMC routine.

Contains the light curve and target pixel files of beta Pictoris for Sector 4 through 7 downloaded from the MAST archive.

Contains three plots which also can be found in the publication and two Jupyter Notebooks:

betaPic_lightkurve.ipynb analyses beta Pictoris using the lightkurve package.

construction_of_the_lightcurve.ipynb uses the files in mast_files. We also take a look at the closest stars using the lightkurve package.

Contains a Jupyter Notebook which was used in order to create two plots visible in the publication. For the frequency analysis we used the software package Period04 and the python package SMURFS.

Contains four short (each ~1min and ~10MB) movies of beta Pictoris created by cutting out a 60x60 pixel area around the star using a jupyter notebook (which also can be found there). The mid-exposure time is marked just above the animation in BTJD (BJD - 2457000). Every movie shows the observations of beta Pic for a specific sector. No background objects (asteroids, ...) are visible before, during or after the dimming events. The flash-like events every approx. 3 days are caused by the momentum dumps.

Dependencies

You will need the python packages numpy, matplotlib, astropy, lightkurve, scipy, emcee and corner

Quick start

  1. Clone this repository with:
git clone https://github.com/sebastian-zieba/betaPic_comet 
  1. Then run a Jupyter Notebook with:
jupyter notebook <name of the notebook>.ipynb 

License

The code is released under a MIT licence.

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