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.

Abstract
Over the last few years the Laboratoire d'Astrophysique de Marseille (LAM) has been heavily involved in R&D for adaptive optics systems dedicated to future large telescopes, particularly in preparation for the European Extremely Large Telescope (E-ELT). Within this framework an investigation into a Pyramid wave-front sensor is underway. The Pyramid sensor is at the cutting edge of high order, high precision wave-front sensing for ground based telescopes. Investigations have demonstrated the ability to achieve a greater sensitivity than the standard Shack-Hartmann wave-front sensor whilst the implementation of a Pyramid sensor on the Large Binocular Telescope (LBT) has provided compelling operational results.1, 2 The Pyramid now forms part of the baseline for several next generation Extremely Large Telescopes (ELTs). As such its behaviour under realistic operating conditions must be further understood in order to optimise performance. At LAM a detailed investigation into the performance of the Pyramid aims to fully characterise the behaviour of this wave-front sensor in terms of linearity, sensitivity and operation. We have implemented a Pyramid sensor using a high speed OCAM2 camera (with close to 0 readout noise and a frame rate of 1.5kHz) in order to study the performance of the Pyramid within a full closed loop adaptive optics system. This investigation involves tests on all fronts, from theoretical models and numerical simulations to experimental tests under controlled laboratory conditions, with an aim to fully understand the Pyramid sensor in both modulated and non-modulated configurations. We include results demonstrating the linearity of the Pyramid signals, compare measured interaction matrices with those derived in simulation and evaluate the performance in closed loop operation. The final goal is to provide an on sky comparison between the Pyramid and a Shack-Hartmann wave-front sensor, at Observatoire de la Côte d'Azur (ONERA-ODISSEE bench). Here we present the adaptive optics setup at LAM and latest experimental and modelling results. The loop is closed on different static wave-front errors: The initial shape of the deformable mirror (DM) and a turbulent-like shape projected onto the DM. The results demonstrate a Pyramid closed loop performance of 7-8nm rms wave-front error compared to a reference at surface.

Abstract
We propose two methods to characterize the Non-Common Path Aberrations (NCPA) on the TMT/NFIRAOS system; these techniques are known as Phase Diversity and Focal Plane Sharpening. We demonstrate the feasibility of these techniques on an experimental bench. We also explore the operational effects of Phase Diversity and how it might be best applied to a NFIRAOS-like system. In particular we explore the technique of single image Phase Diversity along with the effects of i) estimating either Zernike modes or Disk Harmonics, ii) using multiple diverse images, and III) using diversities other than focus. These operational considerations are explored in a simulation of the NFIRAOS system and we aim to find the best estimation of the NFIRAOS NCPA in the presence of different levels of noise. We find a realistic estimation of NFIRAOS NCPA would be with multi-image Phase Diversity-with focus-diverse images sampled at asymmetric positions on either side of the focal plane (with no estimation of the object).

Abstract
In preparation of future multiobject spectrographs (MOS) whose one of the major role is to provide an extensive statistical studies of high redshifted galaxies surveyed, the demonstrator CANARY has been designed to tackle technical challenges related to open-loop adaptive optics (AO) control with jointed Natural Guide Star and Laser Guide Star tomography. We have developed a point spread function (PSF) reconstruction algorithm dedicated to multiobject adaptive optics systems using system telemetry to estimate the PSF potentially anywhere in the observed field, a prerequisite to postprocess AO-corrected observations in integral field spectroscopy. We show how to handle off-axis data to estimate the PSF using atmospheric tomography and compare it to a classical approach that uses on-axis residual phase from a truth sensor observing a natural bright source. We have reconstructed over 450 on-sky CANARY PSFs and we get bias/1-s standard-deviation (std) of 1.3/4.8 on the H-band Strehl ratio (SR) with 92.3% of correlation between reconstructed and sky SR. On the full-width at half-maximum, we get, respectively, 2.94 mas, 19.9 mas, and 88.3% for the bias, std, and correlation. The reference method achieves 0.4/3.5/95% on the SR and 2.71 mas/14.9 mas/92.5% on the FWHM for the bias/std/correlation.

Abstract
In tomographic adaptive-optics (AO) systems, errors due to tomographic wavefront reconstruction limit the performance and angular size of the scientific field of view (FoV), where AO correction is effective. We propose a multi time-step tomographic wavefront reconstruction method to reduce the tomographic error by using measurements from both the current and previous time steps simultaneously. We further outline the method to feed the reconstructor with both wind speed and direction of each turbulence layer. An end-to-end numerical simulation, assuming a multi-object AO (MOAO) system on a 30 m aperture telescope, shows that the multi timestep reconstruction increases the Strehl ratio (SR) over a scientific FoV of 10 arc min in diameter by a factor of 1.5-1.8 when compared to the classical tomographic reconstructor, depending on the guide star asterism and with perfect knowledge of wind speeds and directions. We also evaluate the multi time-step reconstruction method and the wind estimation method on the RAVEN demonstrator under laboratory setting conditions. The wind speeds and directions at multiple atmospheric layers are measured successfully in the laboratory experiment by our wind estimation method with errors below 2 ms-1. With these wind estimates, the multi time-step reconstructor increases the SR value by a factor of 1.2-1.5, which is consistent with a prediction from the end-to-end numerical simulation.