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

Fusco, Thierry; Conan, Jean-Marc; Michau, Vincent; Mugnier, Laurent M.; Rousset, G.

doi:10.1364/ol.24.001472

Cited by 46 publications

(37 citation statements)

References 9 publications

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“…This means that, the best scientific programs requiring high angular resolution could be scheduled in this period. Moreover, we remember that one of the critical points for the successful application of some of the adaptive optics techniques such as the tomographic one (Ragazzoni et al 1999;Ragazzoni et al 2000) or the Multiconjugated Adaptive Optics MCAO (Fusco et al 1999;Fusco et al 2000) is the characterization of the C 2 N during a long period and in a whole 3D domain around the telescope. Indeed, the optical turbulence has a typically non-uniform distribution in the atmosphere and the model indicates that different lines of sight can provide large differences in the seeing estimation (Masciadri et al 2000b).…”

Section: Discussionmentioning

confidence: 99%

Wavefront coherence time seasonal variability and forecasting at the San Pedro Mártir site

Masciadri

Garfias

2001

A&A

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Abstract. In order to efficiently use the recent astronomy high angular resolution techniques (Adaptive Optics and Interferometry) to correct the perturbed wavefront arriving at the telescope pupil, it is necessary to characterize a set of astroclimatic parameters. One of these is the wavefront coherence time τAO. It is an integral parameter, defining the maximum temporal correlation of the perturbed wavefront and it depends on the optical turbulence C 2 N (x, y, z) and the wind intensity |V (x, y, z)| in the whole troposphere. In this paper we use an atmospheric non-hydrostatic model (Meso-NH) conceived to simulate the classical meteorological parameters (p, T and V ) and adapted to simulate the optical turbulence (C 2 N ) to characterize the τAO in a region of some kilometers around the astronomical site of San Pedro Mártir (SPM) in Baja California (Mexico). We study the seasonal variability of the wind intensity in the whole atmosphere (20 km) above the SPM site during one year. We show that, using the C 2 N profiles simulated by Meso-Nh initialized with ECMWF (European Center for Medium Weather Forecasts) data, we obtain typical τAO values in the V band (λ = 0.5 µm). We calculate the seasonal variability of the τAO in SPM and also some preliminary results about the seasonal variability of C 2 N . Moreover, we suggest a physical explication of these variabilities. Finally we investigate the possibility of forecasting τAO.

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Section: Discussionmentioning

confidence: 99%

Wavefront coherence time seasonal variability and forecasting at the San Pedro Mártir site

Masciadri

Garfias

2001

A&A

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“…Providing that the matrix (M o f f axis M o f f axis t ) can be inverted, the matrix C can be written as a Minimum Meam Square Estimator (MMSE) solution type (Fusco et al [8]) and leads to:…”

Section: Tomography With Covariance Of Slopesmentioning

confidence: 99%

Tomography reconstruction using the Learn and Apply algorithm

Vidal¹,

Gendron²,

Brangier³

et al. 2010

1st AO4ELT Conference - Adaptive Optics for Extremely Large Telescopes

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Abstract. In the framework of the MOAO demonstrator CANARY, we developped a new concept of tomography algorithm that allows to measure the tomographic reconstructor directly on-sky, using or not, a priori from the turbulence profile. This simple algorithm, working in open-loop, uses the measured covariance of slopes between all the wavefront sensors (WFS) to deduce the geometric and atmospheric parameters that are used to compute the tomographic reconstructor. This method called "Learn and Apply" (L&A) has also the advantage to measure and take into account all the misalignments between the WFSs in order to calibrate any MOAO instrument. We present the main principle of the algorithm and the last experimental results performed in MOAO scheme at the SESAME bench. ContextOne of the key scientific drivers of the future giant telescopes of the class 30-50m is the formation of the early universe, and in particular the way distant galaxies assembled. These extremely dim and small objects require both the large light-collecting power of an Extremely Large Telescope (ELT) together with a high spatial resolution brought by adaptive optics (AO). Moreover, the galaxies need to be studied through a statistical approach, that require to be able to observe a wealth of them. Dealing with minimum integration times of the order 8 hours for each, the only way to achieve this is thus to multiplex the observations. These requirements led in 2004 [1] to the concept of Multi-Object Adaptive Optics, or MOAO, fully inherited from the FALCON concept presented in 2001 [2] . A MOAO instrument is composed of individual systems that split the field. Some compensate the wavefront onto the small (few arcsecond) areas of the galaxies. They are driven by the wavefront information collected from the others systems : the off-axis wavefront sensors (WFS) that pick their signals from either natural or artificial stars across the field. The way the wavefront measurement are combined together in order to extract the wavefront control is the tomographic reconstruction.EAGLE [3] is an MOAO instrument under conceptual study for the European Extremely Large Telescope (E-ELT). It will cover a field of view of 5 arcminutes. The top level requirements of the instrument call for 20 spectroscopic channels in the near infrared. Each of them will use 1 Deformable Mirror (DM) working in open-loop driven by the tomographic reconstruction using the wavefront information provided by the 6 Laser Guide Stars (LGS) WFS and 5 Natural Guide Stars (NGS) off-axis WFS. CANARY [4], the MOAO pathfinder for EAGLE, is an open loop and tomography experiment that will be installed in 2010 at the William Herschel Telescope (D=4.2m) at La Palma, in the Canaries islands. TomographyOne of the main adaptive optics limitation is the anisoplanetism angle. A guide star is required to sense the wavefront. The angular distance between the object and the guide star needs to be sufficiently short or the AO performance will decrease as the guide star gets further. This limiting angle is call...

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“…Finally, note that we have implicitly supposed that the number of turbulence layers that we sought to estimate is equal to the number of DMs, and that the DMs are conjugated to the same altitudes as the turbulence layers. This is the so-called model approximation as introduced by [9]. A more complete reconstruction scheme (e.g.…”

Section: Minimum Mean Square Error (Mmse)mentioning

confidence: 99%

Reconstruction Strategies for GeMS

Neichel

Rigaut

Bec

et al. 2010

1st AO4ELT Conference - Adaptive Optics for Extremely Large Telescopes

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Abstract. The Gemini Multi-conjugate adaptive optics System (GeMS) is a facility instrument for the GeminiSouth telescope that can provide near-uniform atmospheric compensation over a 1 arc minute square field of view. To provide diffraction-limited image quality at near IR wavelengths across an extended field-of-view, the system includes 5 laser guide stars, 3 natural guide stars and 3 deformable mirrors optically conjugated at 0, 4.5 and 9km. By many ways, GeMS represents a unique system to prepare and understand any future wide field AO systems planned for the ELTs. In this paper, we present the different strategies developed for the phase volume estimation and correction relative to the LGS high-order path. We compare the performance obtained by a Least-Square Estimator (LSE) and a Minimum Mean Square Error (MMSE) reconstructor. The MMSE reconstructor is found to improve the performance compared to the classical LSE, particularly when the system is affected by noise. We show the results obtained by realistic simulations as well as the first results obtained in laboratory on CANOPUS, the GeMS AO bench.

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

Cited by 46 publications

References 9 publications

Wavefront coherence time seasonal variability and forecasting at the San Pedro Mártir site

Wavefront coherence time seasonal variability and forecasting at the San Pedro Mártir site

Tomography reconstruction using the Learn and Apply algorithm

Reconstruction Strategies for GeMS

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