Advances in Astronomy and Space Physics, Volume 12, Issue 1-2, PP. 13-17 (2022)
doi: 10.17721/2227-1481.12.13-17
VarStar Detect: a Python library for the semi-automatic detection of stellar variability
1Department of Physics and Astronomy, University College London, Gower Street, WC1E 6BT London, UK
2Facultad de Ciencias, University of Oviedo, C. Federico García Lorca, 18, 33007 Oviedo, Spain
3Escuela de Ingeniería Informática, University of Oviedo, Calle Valdés Salas, 11, 33007 Oviedo, Spain
2Facultad de Ciencias, University of Oviedo, C. Federico García Lorca, 18, 33007 Oviedo, Spain
3Escuela de Ingeniería Informática, University of Oviedo, Calle Valdés Salas, 11, 33007 Oviedo, Spain
Abstract
VarStar Detect is a Python package available on PyPI optimized for the detection of variable stars using photometric measurements. Based on the method of the Least Squares regression, VarStar Detect calculates the amplitude of a trigonometric polynomial data fit as a measure of variability to assess whether the star is indeed variable. In this work, we present the mathematical background of the package and an analysis of the code's functionality based on TESS Sector 1 Data Release.
Keywords:
methods: data analysis, techniques: photometric, stars: variables