Abstract
CANARY is the Multi-Object Adaptive Optics (MOAO) pathfinder for the future MOAO-Assisted Integral-Field Units (IFU) proposed for Extremely Large Telescopes (ELT). The MOAO concept relies on tomographically reconstructing the turbulence using multiple measurements along different lines of sight. Tomography requires the knowledge of the statistical turbulence parameters, commonly recovered from the system telemetry using a dedicated profiling technique. For demonstration purposes with the MOAO pathfinder CANARY, this identification is performed thanks to the Learn & Apply (L&A) algorithm, that consists in model-fitting the covariance matrix of WFS measurements dependant on relevant parameters: Cn2(h) profile, outer scale profile and system mis-registration. We explore an upgrade of this algorithm, the Learn 3 Steps (L3S) approach, that allows one to dissociate the identification of the altitude layers from the ground in order to mitigate the lack of convergence of the required empirical covariance matrices therefore reducing the required length of data time-series for reaching a given accuracy. For nominal observation conditions, the L3S can reach the same level of tomographic error in using five times less data frames than the L&A approach. The L3S technique has been applied over a large amount of CANARY data to characterize the turbulence above the William Herschel Telescope (WHT). These data have been acquired the 13th, 15th, 16th, 17th and 18th September 2013 and we find 0.67"/8.9m/3.07m.s-1 of total seeing/outer scale/wind-speed, with 0.552"/9.2m/2.89m.s-1 below 1.5 km and 0.263"/10.3m/5.22m.s-1 between 1.5 and 20 km. We have also determined the high altitude layers above 20 km, missed by the tomographic reconstruction on CANARY, have a median seeing of 0.187" and have occurred 16% of observation time.

Abstract
HARMONI is a visible and NIR integral field spectrograph, providing the E-ELT's core spectroscopic capability at first light. HARMONI will work at the diffraction limit of the E-ELT, thanks to a Classical and a Laser Tomographic AO system. In this paper, we present the system choices that have been made for these SCAO and LTAO modules. In particular, we describe the strategy developed for the different Wave-Front Sensors: pyramid for SCAO, the LGSWFS concept, the NGSWFS path, and the truth sensor capabilities. We present first potential implementations. And we asses the first system performance.

Abstract
This paper presents the AO performance we got on-sky with RAVEN, a Multi-Object Adaptive Optics (MOAO) technical and science demonstrator installed and tested at the Subaru telescope. We report Ensquared-Energy (EE) and Full Width at Half Maximum (FWHM) measured from science images on Subaru's IRCS taken during all of the on-sky observing runs. We show these metrics as function of different AO modes and atmospheric conditions for two asterisms of natural guide stars. The performances of the MOAO and Ground-Layer AO (GLAO) modes are between the classical Single-Conjugate AO (SCAO) and seeing-limited modes. We achieve the EE of 30% in H-band with the MOAO correction, which is a science requirement for RAVEN. The MOAO provides sightly better performance than the GLAO mode in both asterisms. One of the reasons which cause this small difference between the MOAO and GLAO modes may be the strong GL contribution. Also, the performance of the MOAO modes is affected by the accuracy of the on-sky turbulence profiling by the SLOpe Detection And Ranging (SLODAR) method.

Abstract
Innovative optical designs allow tackling the spot elongation issues in Shack-Hartman based laser guide star wavefront sensors. We propose two solutions using either a combination of two arrays of freeform microlenses, or a combination of freeform optics, to perform a shrinkage of the laser spots as well as a magnification of the SH focal plane. These approaches will drastically reduce the number of needed pixels, thus making possible the use of existing detectors. We present the recent advances on this activity as well as the estimation of performance, linearity and sensitivity of the compressed system in presence of aberrations.

Abstract
Prior statistical knowledge of the turbulence such as turbulence strength, layer altitudes and the outer scale is essential for atmospheric tomography in adaptive-optics (AO). These atmospheric parameters can be estimated from measurements of multiple Shack-Hartmann wave-front sensors (SH-WFSs) by the SLOpe Detection And Ranging (SLODAR). In this paper, we present the statistics of the vertical CN2 and the outer scale L0 at Maunakea in Hawaii estimated from 60 hours telemetry data in total from multiple SH-WFSs of RAVEN, which is an on-sky multi-object AO demonstrator tested on the Subaru telescope. The mean seeing during the RAVEN on-sky observations is 0.475 arcsec, and 55% turbulence is below 1.5 km. The vertical profile of CN2 from the RAVEN SLODAR is consistent with the profiles from CFHT DIMM and MASS, and TMT site characterization.

Abstract
We propose and apply two methods for estimating phase discontinuities for two realistic scenarios on VLT and Keck. The methods use both phase diversity and a form of image sharpening. For the case of VLT, we simulate the 'low wind effect' (LWE) which is responsible for focal plane errors in low wind and good seeing conditions. We successfully estimate the LWE using both methods, and show that using both methods both independently and together yields promising results. We also show the use of single image phase diversity in the LWE estimation, and show that it too yields promising results. Finally, we simulate segmented piston effects on Keck/NIRC2 images and successfully recover the induced phase errors using single image phase diversity. We also show that on Keck we can estimate both the segmented piston errors and any Zernike modes affiliated with the non-common path.