Near ground horizontal high resolution Cn2 profiling from Shack-Hartmann slopeand scintillation data.

Coupled slope and scintillation detection and ranging (CO-SLIDAR) is a very promising technique for the metrology of near ground Cn2 profiles. It exploits both phase and scintillation measurements obtained with a dedicated wavefront sensor and allows profiling on the full line of sight between pupil and sources. This technique is applied to an associated instrument based on a mid-IR Shack-Hartmann wavefront sensor coupled to a 0.35 m telescope, which observes two cooperative sources. This paper presents what we believe is the first comprehensive description of the CO-SLIDAR method in the context of near-ground optical turbulence metrology. It includes the presentation of the physics principles underlying the measurements of our unsupervised Cn2 profile reconstruction strategy together with the error bar estimation on the reconstructed values. The application to data acquired in a heterogeneous rural landscape during an experimental campaign in Lannemezan, France, demonstrates the ability to obtain profiles with a sampling pitch of about 220 m over a 2.7 km line of sight. The retrieved Cn2 profiles are presented and their variability in space and time is discussed.

Image-based adaptive optics for in vivo imaging in the hippocampus.

Adaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 µm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus.

Revisiting the comparison between the Shack-Hartmann and the pyramid wavefront sensors via the Fisher information matrix.

Exoplanet direct imaging with large ground based telescopes requires eXtreme Adaptive Optics that couples high-order adaptive optics and coronagraphy. A key element of such systems is the high-order wavefront sensor. We study here several high-order wavefront sensing approaches, and more precisely compare their sensitivity to noise. Three techniques are considered: the classical Shack-Hartmann sensor, the pyramid sensor and the recently proposed LIFTed Shack-Hartmann sensor. They are compared in a unified framework based on precise diffractive models and on the Fisher information matrix, which conveys the information present in the data whatever the estimation method. The diagonal elements of the inverse of the Fisher information matrix, which we use as a figure of merit, are similar to noise propagation coefficients. With these diagonal elements, so called "Fisher coefficients", we show that the LIFTed Shack-Hartmann and pyramid sensors outperform the classical Shack-Hartmann sensor. In photon noise regime, the LIFTed Shack-Hartmann and modulated pyramid sensors obtain a similar overall noise propagation. The LIFTed Shack-Hartmann sensor however provides attractive noise properties on high orders.

Experimental validation of LIFT for estimation of low-order modes in low-flux wavefront sensing.

Laser Tomographic and Multi-Conjugate Adaptive Optics systems rely on natural guide stars to sense low order aberrations (tip/tilt and focus). LIFT is a novel focal plane wavefront sensor (WFS), performing a maximum likelihood phase retrieval on a single image, with better sensitivity than a 2 × 2 Hartmann-Shack WFS. Its performance for the estimation of tip/tilt and focus is similar to a pyramid WFS without modulation, but with a simpler set-up. We present here the LIFT concept and associated data processing, as well as experimental results. We validate the estimation of tip/tilt and focus, with monochromatic and large bandwidth light, and verify the low noise sensitivity predicted by theory.

Closed-loop experimental validation of the spatially filtered Shack-Hartmann concept.

An experimental validation of the spatially filtered Shack-Hartmann concept (F-SH) is presented that allows aliasing effects to be decreased. This effect is studied by use of an adaptive optical testbed with a focal plane pinhole in front of the wave-front sensor. First, the ability to close the loop on turbulence is demonstrated. Then the performance gain conferred by the device is quantified and compared with end-to-end simulation results. Another property of the F-SH concept, i.e., the reduction of the waffle modes, is highlighted.

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.

Efficient phase estimation for large-field-of-view adaptive optics.

We propose a maximum a posteriori-based estimation of the turbulent phase in a large field of view (FOV) to overcome the anisoplanatism limitation in adaptive optics. We show that, whatever the true atmospheric profile, a small number of equivalent layers (two or three) is required for accurate restoration of the phase in the whole FOV. The implications for multiconjugate adaptive optics are discussed in terms of the number and conjugated heights of the deformable mirrors. The number of guide stars required for wave-front measurements in the field is also discussed: three (or even two) guide stars are sufficient to produce good performance.

Noise propagation in wave-front sensing with phase diversity.

The phase diversity technique is studied as a wave-front sensor to be implemented with widely extended sources. The wave-front phase expanded on the Zernike polynomials is estimated from a pair of images (in focus and out of focus) by use of a maximum-likelihood approach. The propagation of the photon noise in the images on the estimated phase is derived from a theoretical analysis. The covariance matrix of the phase estimator is calculated, and the optimal distance between the observation planes that minimizes the noise propagation is determined. The phase error is inversely proportional to the number of photons in the images. The noise variance on the Zernike polynomials increases with the order of the polynomial. These results are confirmed with both numerical and experimental validations. The influence of the spectral bandwidth on the phase estimator is also studied with simulations.

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.