Correcting stellar contamination in transmission spectroscopy with contemporaneous monitoring: Application to GJ 1214 b

Abstract

Transmission spectroscopy has emerged as an essential tool for characterising the atmospheres of transiting exoplanets. However, stellar surface inhomogeneities contaminate transmission spectra, posing a major challenge to high-precision observations such as those from the James Webb Space Telescope (JWST). We develop and apply methods to correct for stellar contamination, improving the accuracy of exoplanet atmospheric characterisation. We obtained coordinated multi-band photometry and high-resolution spectroscopy around JWST observations of GJ 1214 b and applied two frameworks: (i) a StarSim inversion, which infers stellar activity parameters from the monitoring data and propagates them to corrections; and (ii) UnSPOTTER, in which neural networks trained on StarSim simulations learn the mapping from monitoring data to corrections. Both frameworks agree within uncertainties and indicate that the JWST observations of GJ 1214 occurred at a favourable rotation phase with low stellar contamination. For UnSPOTTER, the inferred corrections can be constrained at approximately 15 ppm across the JWST wavelength range, implying post-correction residuals of the same order. If the same system were observed near activity maximum, the predicted contamination would be strongly chromatic and affect atmospheric retrievals, highlighting the importance of coordinated monitoring and robust activity correction techniques. The two approaches are complementary but serve different roles. The inversion yields physically interpretable parameters and surface maps, whereas UnSPOTTER marginalises over surface-configuration degeneracies and provides tighter predictive corrections within its validated simulation domain. Our pipeline can be generalised to other active stars: with multi-band and multi-technique monitoring around JWST visits, it can provide activity forecasts for scheduling and activity corrections.