Abstract
Context. To reach its optimal performance, Fizeau interferometry requires that we work to resolve instrumental biases through calibration. One common technique used in high contrast imaging is angular differential imaging, which calibrates the point spread function and flux leakage using a rotation in the focal plane. Aims. Our aim is to experimentally demonstrate and validate the efficacy of an angular differential kernel-phase approach, a new method for self-calibrating interferometric observables that operates similarly to angular differential imaging, while retaining their statistical properties. Methods. We used linear algebra to construct new observables that evolve outside of the subspace spanned by static biases. On-sky observations of a binary star with the SCExAO instrument at the Subaru telescope were used to demonstrate the practicality of this technique. We used a classical approach on the same data to compare the effectiveness of this method. Results. The proposed method shows smaller and more Gaussian residuals compared to classical calibration methods, while retaining compatibility with the statistical tools available. We also provide a measurement of the stability of the SCExAO instrument that is relevant to the application of the technique. Conclusions. Angular differential kernel phases provide a reliable method for calibrating biased observables. Although the sensitivity at small separations is reduced for small field rotations, the calibration is effectively improved and the number of subjective choices is reduced.
Highlights
Since the advent of speckle interferometry (Labeyrie 1970), Fizeau interferometry techniques that use the aperture of a single telescope have proven to be a reliable way to obtain measurements at and beyond the classically defined resolution limit of telescopes
By working with the Fourier transform of images, they exploit observables that were originally developed for long baseline interferometry, such as closure phases (Jennison 1958; Baldwin et al 1986), to provide observables that are robust for instrumental phase errors
angular differential kernels (ADK) is a new approach proposed for the calibration of robust observables that is aimed at removing most of the subjective choices that may often affect classical calibration techniques
Summary
Since the advent of speckle interferometry (Labeyrie 1970), Fizeau interferometry techniques that use the aperture of a single telescope have proven to be a reliable way to obtain measurements at and beyond the classically defined resolution limit of telescopes. Non-redundant masking, in particular, has been established as an observing mode in most of the high-resolution instruments available (Tuthill et al 2010). Kernel-phase observables (Martinache 2010) rely on a generalization of the notion of closure phase for redundant apertures that is applicable in the high Strehl regime. These interferometric techniques rely on simplifications, such as the monochromatic approximation, the short exposure approximation, or the absence of scintillation and instrumental amplitude errors. Calibration observations, where calibrator targets are observed in the same conditions as the science target, are routinely used to remove these instrumental biases
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