Spectrally dispersed kernel phase interferometry with SCExAO/CHARIS: proof of concept and calibration strategies

Abstract

.Kernel phase interferometry (KPI) is a data processing technique that allows for the detection of asymmetries (such as companions or disks) in high-Strehl images, close to and within the classical diffraction limit. We show that KPI can successfully be applied to hyperspectral image cubes generated from integral field spectrographs (IFSs). We demonstrate this technique of spectrally dispersed kernel phase by recovering a known binary with the SCExAO/CHARIS IFS in high-resolution K-band mode. We also explore a spectral differential imaging (SDI) calibration strategy that takes advantage of the information available in images from multiple wavelength bins. Such calibrations have the potential to mitigate high-order, residual systematic kernel phase errors, which currently limit the achievable contrast of KPI. The SDI calibration presented is applicable to searches for line emission or sharp absorption features and is a promising avenue toward achieving photon-noise-limited kernel phase observations. The high angular resolution and spectral coverage provided by dispersed kernel phase offers opportunities for science observations that would have been challenging to achieve otherwise.

Searching for Protoplanets around MWC 758 and MWC 480 in Br-γ Using Kernel Phase and SCExAO/CHARIS

“…As can be seen in Figure 2, the final pupil geometry results in 182 subapertures and 288 UVsampling points with baselines less than the 5.8 m cutoff when using a 0.43 m grid spacing. Somewhat counterintuitively, removing baselines longer than 5.8 m greatly improves the SNR of the final kernel phases as was found in Chaushev et al (2023). This is unexpected since longer baselines, which correspond to higher spatial frequencies, should improve the sensitivity of the kernel phases at small separations.…”

“…Here we summarize the theory behind kernel phases and the data processing pipeline used to extract them. The data processing pipeline used to derive kernel phases from the CHARIS data cubes is detailed in Chaushev et al (2023).…”

“…Each subaperture is given a transmission value as specified in Martinache et al (2020), and the kernel-phase matrix is then computed using the XARA pipeline (Martinache 2010; Martinache et al 2020). 12 Spatial frequencies corresponding to baselines above 5.8 m were removed prior to calculating the matrices in order to maximize the signal-to-noise ratio (SNR; Chaushev et al 2023). As can be seen in Figure 2, the final pupil geometry results in 182 subapertures and 288 UVsampling points with baselines less than the 5.8 m cutoff when using a 0.43 m grid spacing.…”

“…We recently demonstrated the use of the kernel-phase interferometry technique (KPI; Martinache 2010; Martinache et al 2020) with the Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) instrument on the Subaru Telescope (Chaushev et al 2023). CHARIS is an integral field spectrograph (IFS) that sits behind the SCExAO extreme AO system (Groff et al 2015(Groff et al , 2016Brandt et al 2017).…”

DUET: dual use exoplanet telescope

“…This particular thread of research was first published in 2010 6 and treats a conventional telescope as "an interferometric array by discretizing the pupil into a set of virtual subapertures." 7 The process shows that spectral data can be used to sharpen images.…”