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README.md

Code for automated detection of comets in light curve files.

Installation

Requires Python 3 (tested in 3.5). Uses Numpy, Scipy, Astropy and Matplotlib libraries, and a working Cython install.

Install by running:

git clone https://github.com/greghope667/comet_project
cd comet_project
./make

Usage

These scripts runs on light curve files, which can be obtained from MAST.

single_analysis.py runs on a single file, for example:

wget https://archive.stsci.edu/missions/kepler/lightcurves/0035/003542116/kplr003542116-2012088054726_llc.fits
./single_analysis.py kplr003542116-2012088054726_llc.fits

batch_analyse.py runs on directories of files, outputting results to a text file with one row per file. archive_analyse.sh is a bash script for processing compressed archives of light curve files, extracting them temporarily to a directory. Both these scripts have multiple options (number of threads, output file location ...), run with help flag (-h) for more details.

Output

https://github.com/greghope667/comet_project_results contains a description of the output table format produced by this code, as well as the output when run on the entire Kepler dataset. See there also for description of the format of the txt files with dips, and how to filter then with the awk scripts.

  • all_snr_gt_5.txt is the full list of 67,532 potential transits
  • all_snr_gt_5_ok.txt is the final list of 7,217 transits

Other files

  • The jupyer notebook figs.ipynb contains code to explore individual light curves, and makes most of the plots in the paper.
  • The text file artefact_list.txt contains a list of artefacts found among candidates.
  • dr2.xml and young-cl.xml contain votables of stars from Gaia used in the HR diagrams.

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Automated exocomet hunting

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