اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدA dedicated tool for a full 3D Cn2 investigation
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We present in this study a mapping of the optical turbulence (OT) above different astronomical sites. The mesoscale model Meso-NH was used together with the Astro-Meso-Nh package and a set of diagnostic tools allowing for a full 3D investigation of the Cn2. The diagnostics implemented in the Astro-Meso-Nh, allowing for a full 3D investigation of the OT structure in a volumetric space above different sites, are presented. To illustrate the different diagnostics and their potentialities, we investigated one night and looked at instantaneous fields of meteorologic and astroclimatic parameters. To show the potentialities of this tool for applications in an Observatory we ran the model above sites with very different OT distributions: the antarctic plateau (Dome C, Dome A, South Pole) and a mid-latitude site (Mt. Graham, Arizona). We put particular emphasis on the 2D maps of integrated astroclimatic parameters (seeing, isoplanatic angles) calculated in different slices at different heights in the troposhere. This is an useful tool of prediction and investigation of the turbulence structure. It can support the optimization of the AO, GLAO and MCAO systems running at the focus of the ground-based telescopes.From this studies it emerges that the astronomical sites clearly present different OT behaviors. Besides, our tool allowed us for discriminating these sites.
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Wide Field Adaptive Optics (WFAO) systems represent the more sophisticated AO systems available today at large telescopes. A critical aspect for these WFAO systems in order to deliver an optimised performance is the knowledge of the vertical spatiote
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he spatial point-spread function (PSF) to generate a three-dimensional kernel whose characteristics are instrument specific or user generated. The algorithm returns the intrinsic modeled properties along with both an `intrinsic model data cube and the modeled galaxy convolved with the 3D-kernel. The algorithm uses a Markov Chain Monte Carlo (MCMC) approach with a nontraditional proposal distribution in order to efficiently probe the parameter space. We demonstrate the robustness of the algorithm using 1728 mock galaxies and galaxies generated from hydrodynamical simulations in various seeing conditions from 0.6 to 1.2. We find that the algorithm can recover the morphological parameters (inclination, position angle) to within 10% and the kinematic parameters (maximum rotation velocity) to within 20%, irrespectively of the PSF in seeing (up to 1.2) provided that the maximum signal-to-noise ratio (SNR) is greater than $sim3$ pixel$^{-1}$ and that the ratio of the galaxy half-light radius to seeing radius is greater than about 1.5. One can use such an algorithm to constrain simultaneously the kinematics and morphological parameters of (nonmerging) galaxies observed in nonoptimal seeing conditions. The algorithm can also be used on adaptive-optics (AO) data or on high-quality, high-SNR data to look for nonaxisymmetric structures in the residuals.
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