2025/09/19 by H. Parviainen, Parviainen, Hannu · 1 citation
Physics and Astronomy · #Astronomy and Astrophysical Research #Computation #Earth and Planetary Astrophysics (astro-ph.EP) #Exoplanet #FOS: Physical sciences #Gaussian #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Light curve #Python (programming language) #Scientific Research and Discoveries #Stellar, planetary, and galactic studies #Transit (satellite) #Transmission (telecommunications) #Workflow
paper · pdf · doi:10.48550/arxiv.2509.15913
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/09/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.