STUDY OF FILTERING PROCESSING OF LIGHT CURVES OBTAINED WITH THE COROT SATELLITE

Authors

  • Guilherme S. S. Barbosa Escola de Engenharia Mauá (EEM/CEUN-IMT)
  • Roberto B. Menezes IAG - Universidade de São Paulo

Keywords:

Exoplanets, Light Curves, Low-pass filter

Abstract

Light curves are astronomical data used to study the brightness variability of stars, which can potentially result in the discovery of exoplanets, due to eclipses (detected in the light curves) generated by the passage of the exoplanets between the star and the observer. The light curves show high frequency noise that can make it difficult to detect eclipses, determine parameters of the exoplanets (such as their radii and distances from the stars they orbit) from modeling of these astronomical data and their intelligent classification, using Machine Learning techniques. In this work, we propose to investigate, using publicly available data from the CoRoT space telescope, which are the best filtering techniques capable of removing high frequency noise from light curves, without compromising analyzes to be applied, involving exoplanets. To evaluate the effectiveness of the filtering methods, we will determine the parameters of exoplanets, from modeling the light curves, before and after the filters, in order to verify the effect that the noise removal techniques had on the values (and uncertainties) of such parameters. Using the same data, we also intend to evaluate the effectiveness of using different machine learning techniques in the analysis of light curves, with the purpose of differentiating the curves between those containing stars with eclipsing binaries, with exoplanets or without eclipses.

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Published

2022-12-10

How to Cite

Barbosa, G. S. S., & Menezes, R. B. (2022). STUDY OF FILTERING PROCESSING OF LIGHT CURVES OBTAINED WITH THE COROT SATELLITE. Journal of Production and Automation (JPAUT) ISSN 2595-9573, 5(2), 31–37. Retrieved from https://jpaut.com.br/index.php/jpaut/article/view/10