The repository shows three Jupyter notebooks that demonstrate the usage of the lightkurve library to analyse variable stars in the TESS data archiv. The file tess_lightcurve.ipynb demonstrates the usages of pipeline generated lightcurves and the applicatoin of periodograms. In tess_tpf.ipynb the handling of target pixel files is explained. tess_cut.ipynb demonstrates the usage of tess_cut to extract targets from the full frame images of TESS.

This research made use of Lightkurve, a Python package for Kepler and TESS data analysis (Lightkurve Collaboration, 2018).

@MISC{2018ascl.soft12013L, author = {{Lightkurve Collaboration} and {Cardoso}, J.~V.~d.~M. and {Hedges}, C. and {Gully-Santiago}, M. and {Saunders}, N. and {Cody}, A.~M. and {Barclay}, T. and {Hall}, O. and {Sagear}, S. and {Turtelboom}, E. and {Zhang}, J. and {Tzanidakis}, A. and {Mighell}, K. and {Coughlin}, J. and {Bell}, K. and {Berta-Thompson}, Z. and {Williams}, P. and {Dotson}, J. and {Barentsen}, G.}, title = "{Lightkurve: Kepler and TESS time series analysis in Python}", keywords = {Software, NASA}, howpublished = {Astrophysics Source Code Library}, year = 2018, month = dec, archivePrefix = "ascl", eprint = {1812.013}, adsurl = {http://adsabs.harvard.edu/abs/2018ascl.soft12013L}, }