GUIBRUSHR is an open-source Python tool for the end-to-end characterization of exoplanet atmospheres. It unifies, within a single graphical environment backed by a local SQLite3 database, the complete analysis chain that is normally spread across several separate and independently configured codes: removal of telluric and stellar contamination from ground-based high-resolution (HR) spectra, forward modelling of planetary spectra, cross-correlation analysis for the detection of individual chemical species, Bayesian atmospheric retrieval, and the generation of synthetic HR datasets for testing and validation. Analyses can be run on HR data alone, on space-based low-resolution (LR) data alone, or on both simultaneously within the same retrieval, and datasets from multiple instruments and multiple observing nights can be combined. The motivation for the package is the complementarity of the two observing regimes. Ground-based high-resolution échelle spectroscopy (R > 25000, e.g., IGRINS, GIANO-B, CRIRES+, CARMENES, NIRPS) resolves individual molecular line cores and probes the upper atmosphere, but requires dedicated upstream processing (masking, blaze correction, continuum normalization, telluric/stellar removal, cross-correlation diagnostics) and loses the absolute flux reference in the process. Space-based low-resolution spectrophotometry (HST, JWST) preserves the absolute continuum level and probes deeper layers, but blends the molecular features. Most existing retrieval frameworks were designed for one regime only; GUIBRUSHR is built to handle both, and to make their joint exploitation a routine operation rather than a bespoke analysis. The package has been validated against published results for the hot Jupiter WASP-77Ab in three independent configurations: HR-only, using the pre-eclipse IGRINS/Gemini South night of 14 December 2020 analysed by Line et al. (2021); LR-only, using the JWST/NIRSpec spectrum of August et al. (2023); and the combined HR+LR analysis of Smith et al. (2024). In all cases, the retrieved parameters, including the H₂O and CO abundances, the C/O ratio, the atmospheric metallicity, and the thermal structure, are fully consistent with the reference works, and the cross-correlation analyses recover the expected species at the predicted planetary radial velocity, confirming the reliability of the whole chain from spectral processing to atmospheric inference. Amadori and Giacobbe et al. in submission
GUIBRUSHR - A comprehensive tool to characterize exoplanet atmospheres at different spectroscopic resolutions and with a multi-instrument approach (Software Zenodo)
Amadori, Francesco;
2026-01-01
Abstract
GUIBRUSHR is an open-source Python tool for the end-to-end characterization of exoplanet atmospheres. It unifies, within a single graphical environment backed by a local SQLite3 database, the complete analysis chain that is normally spread across several separate and independently configured codes: removal of telluric and stellar contamination from ground-based high-resolution (HR) spectra, forward modelling of planetary spectra, cross-correlation analysis for the detection of individual chemical species, Bayesian atmospheric retrieval, and the generation of synthetic HR datasets for testing and validation. Analyses can be run on HR data alone, on space-based low-resolution (LR) data alone, or on both simultaneously within the same retrieval, and datasets from multiple instruments and multiple observing nights can be combined. The motivation for the package is the complementarity of the two observing regimes. Ground-based high-resolution échelle spectroscopy (R > 25000, e.g., IGRINS, GIANO-B, CRIRES+, CARMENES, NIRPS) resolves individual molecular line cores and probes the upper atmosphere, but requires dedicated upstream processing (masking, blaze correction, continuum normalization, telluric/stellar removal, cross-correlation diagnostics) and loses the absolute flux reference in the process. Space-based low-resolution spectrophotometry (HST, JWST) preserves the absolute continuum level and probes deeper layers, but blends the molecular features. Most existing retrieval frameworks were designed for one regime only; GUIBRUSHR is built to handle both, and to make their joint exploitation a routine operation rather than a bespoke analysis. The package has been validated against published results for the hot Jupiter WASP-77Ab in three independent configurations: HR-only, using the pre-eclipse IGRINS/Gemini South night of 14 December 2020 analysed by Line et al. (2021); LR-only, using the JWST/NIRSpec spectrum of August et al. (2023); and the combined HR+LR analysis of Smith et al. (2024). In all cases, the retrieved parameters, including the H₂O and CO abundances, the C/O ratio, the atmospheric metallicity, and the thermal structure, are fully consistent with the reference works, and the cross-correlation analyses recover the expected species at the predicted planetary radial velocity, confirming the reliability of the whole chain from spectral processing to atmospheric inference. Amadori and Giacobbe et al. in submission
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