ExoIris: fast exoplanet transmission spectroscopy in Python
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866912892681453568 |
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| author | Parviainen, Hannu |
| author_facet | Parviainen, Hannu |
| contents | I present ExoIris, a user-friendly Python package for exoplanet transmission and emission spectroscopy. Unlike existing tools, ExoIris models two-dimensional spectrophotometric transit time series directly and supports the joint analysis of multiple datasets obtained with different instruments and at different epochs, as well as modeling stellar spot crossings and the influence of unocculted heterogeneities (the transit light source effect). These features enable a self-consistent estimation of both wavelength-independent and wavelength-dependent parameters. They offer a more robust workflow than the commonly used two-step approach, in which a "white" light curve is fitted first, and the transmission spectrum is then derived from independent fits constrained by the white-light solution. Despite its increased flexibility and robustness, ExoIris remains computationally efficient. A low-resolution transmission spectrum can be estimated from a single JWST NIRISS transit observation in ~5 minutes assuming white noise, and in ~15 minutes when accounting for time-correlated systematics using a Gaussian process noise model, on a standard desktop computer. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_15913 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | ExoIris: fast exoplanet transmission spectroscopy in Python Parviainen, Hannu Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics I present ExoIris, a user-friendly Python package for exoplanet transmission and emission spectroscopy. Unlike existing tools, ExoIris models two-dimensional spectrophotometric transit time series directly and supports the joint analysis of multiple datasets obtained with different instruments and at different epochs, as well as modeling stellar spot crossings and the influence of unocculted heterogeneities (the transit light source effect). These features enable a self-consistent estimation of both wavelength-independent and wavelength-dependent parameters. They offer a more robust workflow than the commonly used two-step approach, in which a "white" light curve is fitted first, and the transmission spectrum is then derived from independent fits constrained by the white-light solution. Despite its increased flexibility and robustness, ExoIris remains computationally efficient. A low-resolution transmission spectrum can be estimated from a single JWST NIRISS transit observation in ~5 minutes assuming white noise, and in ~15 minutes when accounting for time-correlated systematics using a Gaussian process noise model, on a standard desktop computer. |
| title | ExoIris: fast exoplanet transmission spectroscopy in Python |
| topic | Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2509.15913 |