TAU: A neural network based telluric correction framework

• Published in: Astronomy and astrophysics (Berlin) Vol. 677; p. A120
• Main Authors: Kjærsgaard, R. D., Bello-Arufe, A., Rathcke, A. D., Buchhave, L. A., Clemmensen, L. K. H.
• Format: Journal Article
• Language: English
• Published: 15.09.2023
• ISSN: 0004-6361; 1432-0746
• DOI: 10.1051/0004-6361/202346652

Context. Telluric correction is one of the critically important outstanding issues for extreme precision radial velocities and exoplanet atmosphere observations. Thorough removal of small so-called micro tellurics across the entire wavelength range of optical spectro-graphs is necessary in order to reach the extreme radial velocity precision required to detect Earth-analog exoplanets orbiting in the habitable zone of solar-type stars. Likewise, proper treatment of telluric absorption will be important for exoplanetary atmosphere observations with high-resolution spectrographs on future extremely large telescopes (ELTs). Aims. In this work, we introduce the Telluric AUtoencoder ( TAU ). TAU is an accurate high-speed telluric correction framework built to extract the telluric spectrum with previously unobtained precision in a computationally efficient manner. Methods. TAU is built on a neural network autoencoder trained to extract a highly detailed telluric transmission spectrum from a large set of high-precision observed solar spectra. We accomplished this by reducing the data into a compressed representation, allowing us to unveil the underlying solar spectrum and simultaneously uncover the different modes of variation in the observed spectra relating to the absorption from H 2 O and O 2 in the atmosphere of Earth. Results. We demonstrate the approach on data from the HARPS-N spectrograph and show how the extracted components can be scaled to remove H 2 O and O 2 telluric contamination with improved accuracy and at a significantly lower computational expense than the current state of the art synthetic approach molecfit . We also demonstrate the capabilities of TAU to remove telluric contamination from observations of the ultra-hot Jupiter HAT-P-70b allowing for the retrieval of the atmospheric signal. We publish the extracted components and an open-source code base allowing scholars to apply TAU on their own data.