VarStar Detect, a Python library dedicated to the semi-automatic detection of stellar variability

TL;DR

VarStar Detect is a Python library that uses Fourier Polynomial fitting and Least Squares regression to semi-automatically identify variable stars from photometric data, demonstrated on TESS Sector 1 data.

Contribution

The paper introduces VarStar Detect, a new Python package for detecting stellar variability using Fourier Polynomial fits and Least Squares regression, with mathematical background and practical analysis.

Findings

Effective detection of stellar variability demonstrated on TESS data.

Mathematical foundation provided for the variability detection method.

Open-source Python package available on PyPI.

Abstract

VarStar Detect is a Python package available on PyPI optimized for the detection of variability inside photometric measurements. Based off of the Least Squares method of regression, VarStar Detect calculates the amplitude of a Fourier Polynomial fit of the data as a measure of variability to assess if the star is indeed variable. This work shows the mathematical background of the package and an analysis of the code's functionality on TESS Sector 1 Data.