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Transmission spectroscopy is among the most fruitful techniques to infer themain opacity sources present in the upper atmosphere of a transiting planet andto constrain the composition of the thermosphere and of the unbound exosphere.Not having a public tool able to automatically extract a high-resolutiontransmission spectrum creates a problem of reproducibility for scientificresults. As a consequence, it is very difficult to compare the results obtainedby different research groups and to carry out a homogeneous characterization ofthe exoplanetary atmospheres. In this work, we present a standard, publiclyavailable, user-friendly tool, named SLOPpy (Spectral Lines Of Planets withpython), to automatically extract and analyze the optical transmission spectrumof exoplanets as accurately as possible. Several data reduction steps are firstperformed by SLOPpy to correct the input spectra for sky emission, atmosphericdispersion, the presence of telluric features and interstellar lines,center-to-limb variation, and Rossiter-McLaughlin effect, thus making it astate-of-the-art tool. The pipeline has successfully been applied to HARPS andHARPS-N data of ideal targets for atmospheric characterization. To first assessthe code's performance and to validate its suitability, here we present acomparison with the results obtained from the previous analyses of other workson HD 189733 b, WASP-76 b, WASP-127 b, and KELT-20 b. Comparing our resultswith other works that have analyzed the same datasets, we conclude that thistool gives results in agreement with the published results within 1$\sigma$most of the time, while extracting, with SLOPpy, the planetary signal with asimilar or higher statistical significance.

Characterization of exoplanetary atmospheres with SLOPpy