ExoIris enables efficient transmission spectroscopy for exoplanets using Python, supporting analysis of diverse datasets.
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. These features enable a self-consistent estimation of both wavelength-independent and wavelength-dependent parameters. They offer a more robust workflow compared to the commonly used two-step approach, where 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.
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H. Parviainen (2025) studied this question.
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