Robust Data Interpretation for Perturbed Nulling Interferometers via Proper Handling of Correlated Errors

The detection and atmospheric characterization of potentially habitable, temperate terrestrial exoplanets using a space-based mid-infrared nulling interferometer is a major goal of contemporary astrophysics. A central part of the analysis of such an instrument is the treatment of correlated errors arising from perturbations in the system. While previous studies have often accounted for their effects in a limited manner, we aim to treat them comprehensively here, and we argue that data whitening based on the covariance of these errors is a suitable method to mitigate their impact. We present a framework that quantitatively connects instrumental perturbations to performance metrics, and we develop two computational tools to support our analysis: PHRINGE, for the generation of synthetic nulling data, and LIFEsimMC, a new Monte Carlo–based end-to-end simulator for the Large Interferometer For Exoplanets. Applying our framework to a reference observation of an Earth twin orbiting a Sun twin at 10 pc, we find that whitening is not only essential for a correct interpretation of the detection metric used in hypothesis testing, but also improves the estimates of the planetary properties. Moreover, our approach enables an estimation of the spectral covariance of the extracted planetary spectra, providing valuable additional input for future atmospheric retrievals. We therefore recommend incorporating the framework into performance assessments and requirement derivations for future nulling interferometers.