The Single-mode Complex Amplitude Refinement (SCAR) coronagraph: I. Concept, theory and design

preprint2018arXivOpen access

Abstract

The discovery of an Earth-mass exoplanet around the nearby star Proxima Centauri provides a prime target for the search for life on planets outside our solar system. Atmospheric characterization of these planets has been proposed by blocking the starlight with a stellar coronagraph and using a high-resolution spectrograph to search for reflected starlight off the planet. Due to the large flux ratio and small angular separation between Proxima b and its host star (≲10−7\lesssim10^{-7} and ≲2.2λ/D\lesssim2.2λ/D respectively; at 750nm for an 8m-class telescope) the coronagraph needs to have a high starlight suppression at low inner-working angles. We aim to find the global optimum of an integrated coronagraphic integral-field spectrograph. We present the Single-mode Complex Amplitude Refinement (SCAR) coronagraph that uses a microlens-fed single-mode fiber array in the focal plane downstream from a pupil-plane phase plate. The mode-filtering property of the single-mode fibers allows for the nulling of starlight on the fibers. The phase pattern in the pupil plane is specifically designed to take advantage of this mode-filtering capability. Second-order nulling on the fibers expands the spectral bandwidth and decreases the tip-tilt sensitivity of the coronagraph. The SCAR coronagraph has a low inner-working angle (∼1λ/D\sim1λ/D) at a contrast of <3×10−5<3\times10^{-5} for the 6 fibers surrounding the star using a sufficiently-good adaptive optics system. It can operate over broad spectral bandwidths (∼20%\sim20\%) and delivers high throughput (>50%>50\% including fiber injection losses). Additionally, it is robust against tip-tilt errors (∼0.1λ/D\sim0.1λ/D rms). We present SCAR designs for both an unobstructed and a VLT-like pupil. The SCAR coronagraph is a promising candidate for exoplanet detection and characterization around nearby stars using current high-resolution imaging instruments.

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