• Corpus ID: 226222106

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots

@article{Nikolaou2020LessonsLF,
  title={Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots},
  author={N. Nikolaou and Ingo P. Waldmann and Angelos Tsiaras and Mario Morvan and Billy Edwards and Kai Hou Yip and Giovanna Tinetti and Subhajit Sarkar and James M. Dawson and Vadim Borisov and Gjergji Kasneci and Matej Petkovi{\'c} and Tomaz Stepisnik and Tarek Al-Ubaidi and Rachel Louise Bailey and Michael Granitzer and Sahib Julka and Roman Kern and Patrick Ofner and Stefan Wagner and Lukas Heppe and Mirko Bunse and Katharina Morik},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.15996}
}
The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed using machine learning methodology. For instance, the most prolific method for detecting exoplanets and inferring several of their characteristics, transit photometry, is very sensitive to the presence of stellar spots. The current practice in the literature is to identify the effects of spots visually and correct for… 

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