Vincent Michau

Optimal wave-front reconstruction strategies for multiconjugate adaptive optics

We propose an optimal approach for the phase reconstruction in a large field of view (FOV) for multiconjugate adaptive optics. This optimal approach is based on a minimum-mean-square-error estimator that minimizes the mean residual phase variance in the FOV of interest. It accounts for the C2n profile in order to optimally estimate the correction wave front to be applied to each deformable mirror (DM). This optimal approach also accounts for the fact that the number of DMs will always be smaller than the number of turbulent layers, since the C2n profile is a continuous function of the altitude h. Links between this optimal approach and a tomographic reconstruction of the turbulence volume are established. In particular, it is shown that the optimal approach consists of a full tomographic reconstruction of the turbulence volume followed by a projection onto the DMs accounting for the considered FOV of interest. The case where the turbulent layers are assumed to match the mirror positions [model-approximation (MA) approach], which might be a crude approximation, is also considered for comparison. This MA approach will rely on the notion of equivalent turbulent layers. A comparison between the optimal and MA approaches is proposed. It is shown that the optimal approach provides very good performance even with a small number of DMs (typically, one or two). For instance, good Strehl ratios (greater than 20%) are obtained for a 4-m telescope on a 150-arc sec x 150-arc sec FOV by using only three guide stars and two DMs.

Improvement of Shack–Hartmann wave-front sensor measurement for extreme adaptive optics

The development of high-performance adaptive optics systems requires the optimization of wave-front sensors (WFSs) working in the high-order correction regime. We propose a new method to improve the wave-front slope estimation of a Shack-Hartmann WFS in such a regime. Based on a detailed analysis of the different errors in the slope estimation with a classical centroid and with the new method, the gain in terms of wave-front-sensing accuracy in both the detector and the photon noise regimes is stressed. This improvement is proposed without major system disruption.

Retrieving parameters of the anisotropic refractive index fluctuations spectrum in the stratosphere from balloon-borne observations of stellar scintillation

Scintillation effects are not negligible in the stratosphere. We present a model based on a 3D model of anisotropic and isotropic refractive index fluctuations spectra that predicts scintillation rates within the so-called small perturbation approximation. Atmospheric observations of stellar scintillation made from the AMON-RA (AMON, Absorption par les Minoritaires Ozone et NO(x); RA, rapid) balloon-borne spectrometer allows us to remotely probe wave-turbulence characteristics in the stratosphere. Data reduction from these observations brings out values of the inner scale of the anisotropic spectrum. We find metric values of the inner scale that are compatible with space-based measurements. We find a major contribution of the anisotropic spectrum relative to the isotropic contribution. When the sight line plunges into the atmosphere, strong scintillation occurs as well as coupled chromatic refraction effects.

Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra

Adaptive optics systems provide a real-time compensation for atmospheric turbulence. However, the correction is often only partial, and a deconvolution is required for reaching the diffraction limit. The need for a regularized deconvolution is discussed, and such a deconvolution technique is presented. This technique incorporates a positivity constraint and some a priori knowledge of the object (an estimate of its local mean and a model for its power spectral density). This method is then extended to the case of an unknown point-spread function, still taking advantage of similar a priori information on the point-spread function. Deconvolution results are presented for both simulated and experimental data.

Myopic deconvolution from wave-front sensing

Deconvolution from wave-front sensing is a powerful and low-cost high-resolution imaging technique designed to compensate for the image degradation due to atmospheric turbulence. It is based on a simultaneous recording of short-exposure images and wave-front sensor (WFS) data. Conventional data processing consists of a sequential estimation of the wave fronts given the WFS data and then of the object given the reconstructed wave fronts and the images. However, the object estimation does not take into account the wave-front reconstruction errors. A joint estimation of the object and the respective wave fronts has therefore been proposed to overcome this limitation. The aim of our study is to derive and validate a robust joint estimation approach, called myopic deconvolution from wave-front sensing. Our estimator uses all data simultaneously in a coherent Bayesian framework. It takes into account the noise in the images and in the WFS measurements and the available a priori information on the object to be restored as well as on the wave fronts. Regarding the a priori information on the object, an edge-preserving prior is implemented and validated. This method is validated on simulations and on experimental astronomical data.

Scintillation and phase anisoplanatism in Shack-Hartmann wavefront sensing

Adaptive optics provides a real-time compensation for atmospheric turbulence that severely limits the resolution of ground-based observation systems. The correction quality relies on a key component, that is, the wavefront sensor (WFS). When observing extended sources, WFS precision is limited by anisoplanatism effects. Anisoplanatism induces a variation of the turbulent phase and of the collected flux in the field of view. We study the effect of this phase and scintillation anisoplanatism on wavefront analysis. An analytical expression of the error induced is given in the Rytov regime. The formalism is applied to a solar and an endoatmospheric observation. Scintillation effects are generally disregarded, especially in astronomical conditions. We shall prove that this approximation is not valid with extended objects.

ATLAS: the E-ELT laser tomographic adaptive optics system

ATLAS is a generic Laser Tomographic AO (LTAO) system for the E-ELT. Based on modular, relatively simple, and yet innovative concepts, it aims at providing diffraction limited images in the near infra-red for a close to 100 percent sky coverage.

Optimization of a Shack-Hartmann-based wavefront sensor for XAO systems

Optimization of a Shack-Hartmann based WFS is proposed for XAO systems. Both aliasing effects and noise propagation issues is investigated in order to optimize the WFS device. In particular a new estimator of the spot position is proposed and characterized both analytically and using end-to-end simulations. Analytical expressions of the slope measurement errors is derived and the gain brought by our new Weighted Center of Gravity estimator is quantified.

Isoplanatic angle and optimal guide star separation for multiconjugate adaptive optics

We propose a first orae performance estimation of multiconjugate adaptive optics (MCAO) systems. An important and restrictive parameter is the angular guide star (GS) separation for a field of view (FOV) of interest to be compensated. An analytical approach is proposed to estimate the residual variance of a MCAO systems for a given position in the FOV as a function of GS separation. This approach allows us to define expected isoplanatic angles for MCAO systems as a function of the atmospheric and observing conditions (turbulence profile, telescope diameter and GS separation). The analytical results are also compared with the numerical simulation of a MCAO system, in which a great care has been taken in the 3D wavefront reconstruction from 2D wavefront sensor (WFS) measurements. For a 8 m telescope, we show that 3 GSs and 3 deformable mirrors provides very good performance in a 200 arcseconds FOV at 2.2 micrometer.

C n 2 profile measurement from Shack-Hartmann data

C(n)(2) profile monitoring usually relies on the exploitation of wavefront slope correlations or of scintillation pattern correlations. Scintillation is rather sensitive to high turbulence layers whereas wavefront slope correlations are mainly due to layers close to the receiving plane. Wavefront slope and scintillation correlations are therefore complementary. A Shack-Hartmann wavefront sensor (SHWFS) is currently used to measure wavefront slopes only. But it could also be sensitive to scintillation as the average intensity in a given subaperture can be obtained by adding pixel intensities in the subaperture focal plane up. With slopes and scintillation being recorded simultaneously, their correlation is also theoretically available. We propose to exploit wavefront slope and scintillation correlations recorded with a SHWFS to retrieve the C(n)(2) profile. Two measurement methods are exposed. In CO-SLIDAR (Coupled SLODAR SCIDAR), correlations of SHWFS data recorded on two separated stars are exploited. SCO-SLIDAR (Single CO-SLIDAR) relies on the same principle as CO-SLIDAR, but SHWFS data are recorded on a single star. Results of C(n)(2) estimation from simulated SHWFS data are presented.