Statistical tests with multi-wavelength Kernel-phase analysis for the detection and characterization of planetary companions
Mamadou N'Diaye, David Mary, Frantz Martinache, Roxanne Ligi, Nick, Cvetojevic, Peter Chingaipe, Romain Laugier

TL;DR
This paper extends kernel-phase analysis to multi-wavelength data cubes from integral field spectrographs, improving detection and atmospheric characterization of exoplanets around nearby stars.
Contribution
It introduces a novel multi-spectral kernel-phase approach for ground-based and space telescopes, enhancing exoplanet detection and spectral analysis capabilities.
Findings
Detection limits are estimated using synthetic and real data.
Multi-wavelength kernel-phase improves sensitivity to planetary companions.
Potential for detailed atmospheric characterization of exoplanets.
Abstract
Kernel phase is a method to interpret stellar point source images by considering their formation as the analytical result of an interferometric process. Using Fourier formalism, this method allows for observing planetary companions around nearby stars at separations down to half a telescope resolution element, typically 20\,mas for a 8\,m class telescope in H band. The Kernel-phase analysis has so far been mainly focused on working with a single monochromatic light image, recently providing theoretical contrast detection limits down to at 200\,mas with JWST/NIRISS in the mid-infrared by using hypothesis testing theory. In this communication, we propose to extend this approach to data cubes provided by integral field spectrographs (IFS) on ground-based telescopes with adaptive optics to enhance the detection of planetary companions and explore the spectral characterization of…
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Taxonomy
TopicsAstronomy and Astrophysical Research · Adaptive optics and wavefront sensing · Stellar, planetary, and galactic studies
