Six Laser Guide Stars (LGS) are included in the design of the European Extremely Large Telescope (ELT), with all of its current instruments taking advantage of them using Shack-Hartmann (SH) wavefront sensors (WFS). However, this implementation raises new issues related to the unprecedented elongation that results from the perspective effect combined to the thickness of the sodium layer. In order to investigate wavefront sensing with an elongated LGS on a SH WFS, we are taking advantage of the presence of the multi-object adaptive optics demonstrator CANARY on the William Herschel Telescope (WHT), in La Palma island, that was upgraded with a sodium LGS WFS for our experiment. The LGS is generated by ESO’s transportable Wendelstein LGS unit and the elongation is obtained by positioning the laser launch telescope 40 meters away from the WHT. With this experiment we are able to measure wavefronts using an elongated LGS WFS. In this paper, we present results obtained during the latest run of observations in September 2017. In these results is comprised an error breakdown of wavefront measurement on elongated LGS. The performances of several centroiding methods are compared thanks to this error breakdown. Additionally, we take advantage of varying observation conditions with respect to seeing and sodium profile to establish the robustness of the different centroiding methods. Finally, these performances are evaluated for different SH designs, to explore which compromises can be reached with respect to pixel scale and sub-aperture field of view.
The optical turbulence profile is a key parameter in tomographic reconstruction. With interest in tomographic adaptive optics for the next generation of ELTs, turbulence profiling campaigns have produced large quantities of data for observing sites around the world. In order to be useful for Monte Carlo AO simulation, these large datasets must be reduced to a small number of profiles. There is commonly large variation in the structure of the turbulence, therefore statistics such as the median and interquartile range of each altitude bin become less representative as features in the profile are averaged out. Here we present the results of the use of a hierarchical clustering method to reduce the 2018A Stereo-SCIDAR dataset from ESO Paranal, consisting of over 10,000 turbulence profiles measured over 83 nights, to a small set of 18 that represent the most commonly observed profiles.
To approach optimal performance advanced Adaptive Optics (AO) systems deployed on ground-based telescopes must have accurate knowledge of atmospheric turbulence as a function of altitude. Stereo-SCIDAR is a high-resolution stereoscopic instrument dedicated to this measure. Here, its profiles are directly compared to internal AO telemetry atmospheric profiling techniques for CANARY (Vidal <i>et al.</i> 2014<sup>1</sup>), a Multi-Object AO (MOAO) pathfinder on the William Herschel Telescope (WHT), La Palma. In total twenty datasets are analysed across July and October of 2014. Levenberg-Marquardt fitting algorithms dubbed <i>Direct Fitting </i>and <i>Learn 2 Step</i> (<i>L2S</i>; Martin 2014<sup>2</sup>) are used in the recovery of profile information via covariance matrices - respectively attaining average Pearson product-moment correlation coefficients with stereo-SCIDAR of 0.2 and 0.74. By excluding the measure of covariance between orthogonal Wavefront Sensor (WFS) slopes these results have revised values of 0.65 and 0.2. A data analysis technique that combines <i>L2S </i>and SLODAR is subsequently introduced that achieves a correlation coefficient of 0.76.