Telluric Contamination Removal with Deep Learning: a preprocessed dataset of KELT-9b observations

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Official dataset used for the experiments presented in the paper "A data-driven approach for extracting exoplanetary atmospheric features": https://doi.org/10.1016/j.ascom.2025.100964 The dataset includes 6 preprocessed observation nights of the exoplanet "KELT-9b". Data augmentation can be performed by following instruction in the README of the corresponding Github repo: https://github.com/gomax22/ganastro/The authors acknowledge financial contribution from the European Union - Next Generation EU RRF M4C2 1.1 PRIN MUR 2022 project 2022CERJ49 (ESPLORA) "Finanziato dall'Unione europea- Next Generation EU, Missione 4 Componente 2 CUP Master C53D23001060006, CUP I53D23000660006". Part of this work was carried out with the support from the grant: “A caccia di un’altra Terra con tecniche di calcolo parallelo e intelligenza artificiale”, D.M. 737/2021, from the University of Naples “Parthenope”.We also are grateful for the support of the Parthenope University of Naples, Department of Science and Technology, Research Computing Facilities for assistance with the calculations carried out in this work.

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