Coronagraphic phase diversity: performance study and laboratory demonstration

TL;DR

This paper introduces COFFEE, a Bayesian focal-plane wave-front sensing method for high-contrast imaging, validated through simulations and laboratory experiments, aiming to improve exoplanet detection by correcting quasi-static aberrations.

Contribution

The paper presents a novel focal-plane wave-front sensing technique, COFFEE, extending phase diversity for high-contrast imaging, with experimental validation demonstrating its effectiveness.

Findings

COFFEE accurately estimates differential aberrations from two focal-plane images.

Experimental results closely match numerical simulations, confirming COFFEE's reliability.

Preliminary tests show COFFEE can effectively compensate aberrations upstream of a coronagraph.

Abstract

The final performance of current and future instruments dedicated to exoplanet detection and characterization (such as SPHERE on the European Very Large Telescope, GPI on Gemini North, or future instruments on Extremely Large Telescopes) is limited by uncorrected quasi-static aberrations. These aberrations create long-lived speckles in the scientific image plane, which can easily be mistaken for planets. Common adaptive optics systems require dedicated components to perform wave-front analysis. The ultimate wave-front measurement performance is thus limited by the unavoidable differential aberrations between the wavefront sensor and the scientific camera. To reach the level of detectivity required by high-contrast imaging, these differential aberrations must be estimated and compensated for. In this paper, we characterize and experimentally validate a wave-front sensing method that relies on focal-plane data. Our method, called COFFEE (for COronagraphic Focal-plane wave-Front Estimation for Exoplanet detection), is based on a Bayesian approach, and it consists in an extension of phase diversity to high-contrast imaging. It estimates the differential aberrations using only two focal-plane coronagraphic images recorded from the scientific camera itself. In this paper, we first present a thorough characterization of COFFEE's performance by means of numerical simulations. This characterization is then compared with an experimental validation of COFFEE using an in-house adaptive optics bench and an apodized Roddier & Roddier phase mask coronagraph. An excellent match between experimental results and the theoretical study is found. Lastly, we present a preliminary validation of COFFEE's ability to compensate for the aberrations upstream of a coronagraph.