Abstract
Gemini Observatory has been awarded a major funding from the National Science Foundation to build a complete new state of the art multi-conjugate adaptive optics system for Gemini North. The system will be designed to provide an MCAO facility delivering close to diffraction limit correction in the near-infrared over a 2 arcminutes field of view and feed imaging and spectroscopic instruments. We present in this paper the results of the conceptual design phase with details on the new proposed laser guide star facilities and adaptive optics bench. We will present results on the performance simulation assessments as well as the developed selected science cases.

Abstract
Context. Here we describe a simple, efficient, and most importantly fully operational point-spread-function (PSF)-reconstruction approach for laser-assisted ground layer adaptive optics (GLAO) in the frame of the Multi Unit Spectroscopic Explorer (MUSE) wide field mode. Aims. Based on clear astrophysical requirements derived by the MUSE team and using the functionality of the current ESO Adaptive Optics Facility we aim to develop an operational PSF-reconstruction (PSFR) algorithm and test it both in simulations and using on-sky data. Methods. The PSFR approach is based on a Fourier description of the GLAO correction to which the specific instrumental effects of MUSE wide field mode (pixel size, internal aberrations, etc.) have been added. It was first thoroughly validated with full end-to-end simulations. Sensitivity to the main atmospheric and AO system parameters was analysed and the code was re-optimised to account for the sensitivity found. Finally, the optimised algorithm was tested and commissioned using more than one year of on-sky MUSE data. Results. We demonstrate with an on-sky data analysis that our algorithm meets all the requirements imposed by the MUSE scientists, namely an accuracy better than a few percent on the critical PSF parameters including full width at half maximum and global PSF shape through the kurtosis parameter of a Moffat function. Conclusions. The PSFR algorithm is publicly available and is used routinely to assess the MUSE image quality for each observation. It can be included in any post-processing activity which requires knowledge of the PSF.

Abstract
The performance of tomographic adaptive optics (AO) systems is intrinsically linked to the vertical profile of optical turbulence. First, a sufficient number of discrete turbulent layers must be reconstructed to model the true continuous turbulence profile. Secondly over the course of an observation, the profile as seen by the telescope changes and the tomographic reconstructor must be updated. These changes can be due to the unpredictable evolution of turbulent layers on meteorological time-scales as short as minutes. Here, we investigate the effect of changing atmospheric conditions on the quality of tomographic reconstruction by coupling fast analyticalAOsimulation to a large data base of 10 691 high-resolution turbulence profiles measured over two years by the Stereo-SCIDAR instrument at ESO Paranal, Chile. This work represents the first investigation of these effects with a large, statistically significant sample of turbulence profiles. The statistical nature of the study allows us to assess not only the degradation and variability in tomographic error with a set of system parameters (e.g. number of layers and temporal update period), but also the required parameters to meet some error threshold. In the most challenging conditions where the profile is rapidly changing, these parameters must be far more tightly constrained in order to meet this threshold. By providing estimates of these constraints for a wide range of system geometries as well as the impact of different temporal optimization strategies we may assist the designers of tomographic AO for the extremely large telescope to dimension their systems.

Abstract
Advanced adaptive-optics (AO) systems will likely utilize pyramid wavefront sensors (PWFSs) over the traditional Shack-Hartmann sensor in the quest for increased sensitivity, peak performance and ultimate contrast. Here, we explain and quantify the PWFS theoretical limits as a means to highlight its properties and applications. We explore forward models for the PWFS in the spatial-frequency domain: these prove useful because (i) they emanate directly from physical-optics (Fourier) diffraction theory; (ii) they provide a straightforward path to meaningful error breakdowns; (iii) they allow for reconstruction algorithms with O(n log(n)) complexity for large-scale systems; and (iv) they tie in seamlessly with decoupled (distributed) optimal predictive dynamic control for performance and contrast optimization. All these aspects are dealt with here. We focus on recent analytical PWFS developments and demonstrate the performance using both analytic and end-to-end simulations. We anchor our estimates on observed on-sky contrast on existing systems, and then show very good agreement between analytical and Monte Carlo performance estimates on AO systems featuring the PWFS. For a potential upgrade of existing high-contrast imagers on 10-m-class telescopes with visible or near-infrared PWFSs, we show, under median conditions at Paranal, a contrast improvement (limited by chromatic and scintillation effects) of 2×-5× when just replacing the wavefront sensor at large separations close to the AO control radius where aliasing dominates, and of factors in excess of 10× by coupling distributed control with the PWFS over most of the AO control region, from small separations starting with an inner working angle of typically 1-2 ?/D to the AO correction edge (here 20 ?/D).

Abstract
Context.The wind-driven halo is a feature that is observed in images that were delivered by the latest generation of ground-based instruments that are equipped with an extreme adaptive optics system and a coronagraphic device, such as SPHERE at the Very Large Telescope (VLT). This signature appears when the atmospheric turbulence conditions vary faster than the adaptive optics loop can correct for. The wind-driven halo is observed as a radial extension of the point spread function along a distinct direction (this is sometimes referred to as the butterfly pattern). When this is present, it significantly limits the contrast capabilities of the instrument and prevents the extraction of signals at close separation or extended signals such as circumstellar disks. This limitation is consequential because it contaminates the data for a substantial fraction of the time: about 30% of the data produced by the VLT/SPHERE instrument are affected by the wind-driven halo.Aims.This paper reviews the causes of the wind-driven halo and presents a method for analyzing its contribution directly from the scientific images. Its effect on the raw contrast and on the final contrast after post-processing is demonstrated.Methods.We used simulations and on-sky SPHERE data to verify that the parameters extracted with our method can describe the wind-driven halo in the images. We studied the temporal, spatial, and spectral variation of these parameters to point out its deleterious effect on the final contrast.Results.The data-driven analysis we propose provides information to accurately describe the wind-driven halo contribution in the images. This analysis confirms that this is a fundamental limitation of the finally reached contrast performance.Conclusions.With the established procedure, we will analyze a large sample of data delivered by SPHERE in order to propose post-processing techniques that are tailored to removing the wind-driven halo.

Abstract
Context. Extremely large telescopes are overwhelmingly equipped with pyramid wavefront sensors (PyWFS) over the more widely used Shack-Hartmann wavefront sensor to perform their single-conjugate adaptive optics (SCAO) mode. The PyWFS, a sensor based on Fourier filtering, has proven to be highly successful in many astronomy applications. However, this sensor exhibits non-linear behaviours that lead to a reduction of the sensitivity of the instrument when working with non-zero residual wavefronts. This so-called optical gains (OG) effect, degrades the closed-loop performance of SCAO systems and prevents accurate correction of non-common path aberrations (NCPA). Aims. In this paper, we aim to compute the OG using a fast and agile strategy to control PyWFS measurements in adaptive optics closed-loop systems. Methods. Using a novel theoretical description of PyWFS, which is based on a convolutional model, we are able to analytically predict the behaviour of the PyWFS in closed-loop operation. This model enables us to explore the impact of residual wavefront errors on particular aspects such as sensitivity and associated OG. The proposed method relies on the knowledge of the residual wavefront statistics and enables automatic estimation of the current OG. End-to-end numerical simulations are used to validate our predictions and test the relevance of our approach. Results. We demonstrate, using on non-invasive strategy, that our method provides an accurate estimation of the OG. The model itself only requires adaptive optics telemetry data to derive statistical information on atmospheric turbulence. Furthermore, we show that by only using an estimation of the current Fried parameter r0 and the basic system-level characteristics, OGs can be estimated with an accuracy of less than 10%. Finally, we highlight the importance of OG estimation in the case of NCPA compensation. The proposed method is applied to the PyWFS. However, it remains valid for any wavefront sensor based on Fourier filtering subject from OG variations.