High-order myopic coronagraphic phase diversity (COFFEE) for wave-front control in high-contrast imaging systems.

The estimation and compensation of quasi-static aberrations is mandatory to reach the ultimate performance of high-contrast imaging systems. COFFEE is a focal plane wave-front sensing method that consists in the extension of phase diversity to high-contrast imaging systems. Based on a Bayesian approach, it estimates the quasi-static aberrations from two focal plane images recorded from the scientific camera itself. In this paper, we present COFFEE's extension which allows an estimation of low and high order aberrations with nanometric precision for any coronagraphic device. The performance is evaluated by realistic simulations, performed in the SPHERE instrument framework. We develop a myopic estimation that allows us to take into account an imperfect knowledge on the used diversity phase. Lastly, we evaluate COFFEE's performance in a compensation process, to optimize the contrast on the detector, and show it allows one to reach the 10(-6) contrast required by SPHERE at a few resolution elements from the star. Notably, we present a non-linear energy minimization method which can be used to reach very high contrast levels (better than 10(7) in a SPHERE-like context).

Coronagraphic phase diversity: a simple focal plane sensor for high-contrast imaging.

Exoplanet direct imaging is a challenging goal of today's astronomical instrumentation. Several high-contrast imaging instruments dedicated to this task are currently being integrated; they are ultimately limited by the presence of quasi-static speckles in the imaging focal plane. These speckles originate in residual quasi-static optical aberrations, which must be measured and compensated for, typically at a nanometric level. We present a novel focal plane wavefront sensor (WFS) designed for this particular application. It is an extension of the phase diversity technique to coronagraphic imaging. This sensor requires no dedicated hardware and uses only two scientific images differing from a known aberration, which can be conveniently introduced by the adaptive optics subsystem. The aberrations are therefore calibrated all the way down to the scientific camera, without any differential aberrations between the sensor and the scientific camera. We show the potential of this WFS by means of simulations, and we perform a preliminary experimental validation.

Analytical expression of long-exposure adaptive-optics-corrected coronagraphic image. First application to exoplanet detection.

In this paper we derive an analytical model of a long-exposure star image for an adaptive-optics(AO)-corrected coronagraphic imaging system. This expression accounts for static aberrations upstream and downstream of the coronagraphic mask as well as turbulence residuals. It is based on the perfect coronagraph model. The analytical model is validated by means of simulations using the design and parameters of the SPHERE instrument. The analytical model is also compared to a simulated four-quadrant phase-mask coronagraph. Then, its sensitivity to a miscalibration of structure function and upstream static aberrations is studied, and the impact on exoplanet detectability is quantified. Last, a first inversion method is presented for a simulation case using a single monochromatic image with no reference. The obtained result shows a planet detectability increase by two orders of magnitude with respect to the raw image. This analytical model presents numerous potential applications in coronographic imaging, such as exoplanet direct detection, and circumstellar disk observation.

On-line long-exposure phase diversity: a powerful tool for sensing quasi-static aberrations of extreme adaptive optics imaging systems.

The phase diversity technique is a useful tool to measure and pre-compensate for quasi-static aberrations, in particular non-common path aberrations, in an adaptive optics corrected imaging system. In this paper, we propose and validate by simulations an extension of the phase diversity technique that uses long exposure adaptive optics corrected images for sensing quasi-static aberrations during the scientific observation, in particular for high-contrast imaging. The principle of the method is that, for a sufficiently long exposure time, the residual turbulence is averaged into a convolutive component of the image and that phase diversity estimates the sole static aberrations of interest. The advantages of such a procedure, compared to the processing of shortexposure image pairs, are that the separation between static aberrations and turbulence-induced ones is performed by the long-exposure itself and not numerically, that only one image pair must be processed, that the estimation benefits from the high SNR of long-exposure images, and that only the static aberrations of interest are to be estimated. Long-exposure phase diversity can also be used as a phasing sensor for a segmented aperture telescope. Thus, it may be particularly useful for future planet finder projects such as EPICS on the European ELT.

High-order adaptive optics requirements for direct detection of extrasolar planets: Application to the SPHERE instrument.

The detection of extrasolar planets implies an extremely high-contrast, long-exposure imaging capability at near infrared and probably visible wavelengths. We present here the core of any Planet Finder instrument, that is, the extreme adaptive optics (XAO) subsystem. The level of AO correction directly impacts the exposure time required for planet detection. In addition, the capacity of the AO system to calibrate all the instrument static defects ultimately limits detectivity. Hence, the extreme AO system has to adjust for the perturbations induced by the atmospheric turbulence, as well as for the internal aberrations of the instrument itself. We propose a feasibility study for an extreme AO system in the frame of the SPHERE (Spectro-Polarimetry High-contrast Exoplanet Research) instrument, which is currently under design and should equip one of the four VLT 8-m telescopes in 2010.