Multi time-step wavefront reconstruction for tomographic adaptive-optics systems.

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 time-step 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.

Spatio-angular minimum-variance tomographic controller for multi-object adaptive-optics systems.

Multi-object astronomical adaptive optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arcminutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular linear-quadratic-Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [J. Opt. Soc. Am. A31, 101 (2014)10.1364/JOSAA.31.000101JOAOD61084-7529], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wavefronts are never explicitly estimated in the volume, providing considerable computational savings on 10-m-class telescopes and beyond. We find that for Raven, a 10-m-class MOAO system with two science channels, the SA-LQG improves the limiting magnitude by two stellar magnitudes when both the Strehl ratio and the ensquared energy are used as figures of merit. The sky coverage is therefore improved by a factor of ~5.

Linear prediction of atmospheric wave-fronts for tomographic adaptive optics systems: modelling and robustness assessment.

We use a theoretical framework to analytically assess temporal prediction error functions on von-Kármán turbulence when a zonal representation of wavefronts is assumed. The linear prediction models analyzed include auto-regressive of an order up to three, bilinear interpolation functions, and a minimum mean square error predictor. This is an extension of the authors' previously published work Correia et al. [J. Opt. Soc. Am. A31, 101 (2014)JOAOD61084-752910.1364/JOSAA.31.000101], in which the efficacy of various temporal prediction models was established. Here we examine the tolerance of these algorithms to specific forms of model errors, thus defining the expected change in behavior of the previous results under less ideal conditions. Results show that ±100% wind speed error and ±50 deg are tolerable before the best linear predictor delivers poorer performance than the no-prediction case.

Fast iterative algorithm (FIA) for controlling MEMS deformable mirrors: principle and laboratory demonstration.

We present a fast and high accuracy iterative algorithm to control Micro-Electro-Mechanical-System (MEMS) deformable mirrors (DMs) for open-loop (OL) adaptive optics (AO) applications. Our approach relies on a simple physical model for the forces applied on DM actuators and membrane, defined by a small number of parameters that we measure in an experimental setup. The algorithm iteratively applies forces and updates actuator displacements, allowing real-time utilization in an Extreme-AO system (control rate ≥ Khz). Our measurements show that it reproduces Kolmogorov type phase screens with an error equal to 7.3% of the rms of the desired phase (1.6% of the peak-to-valley of the desired phase). This performance corresponds to an improvement of a factor three compared to the standard quadratic model (common relation between voltage and actuator displacement). Originally developed for the DM control of the Subaru Coronagraphic Extreme-AO (SCExAO) project, the algorithm is also suitable for Multi-Object AO systems.

Experimental assessment of the matched filter for laser guide star wavefront sensing.

Laser guide star wavefront sensing comes with several limitations. When imaged with a Shack-Hartmann wavefront sensor, the laser guide star is seen as extended sources elongated in the directions given by the lenslet locations and the laser axis. A test bed has been built in the Adaptive Optics Laboratory of the University of Victoria that reproduces this effect as seen on extremely large telescopes. A new wavefront sensing algorithm, the matched filter, has been implemented and its performance assessed with the test bed. Its ability to mitigate laser guide star aberrations by tracking the sodium layer fluctuations in a closed loop adaptive optics system is shown.

A laser guide star wavefront sensor bench demonstrator for TMT.

Sodium laser guide stars (LGSs) allow, in theory, Adaptive Optics (AO) systems to reach a full sky coverage, but they have their own limitations. The artificial star is elongated due to the sodium layer thickness, and the temporal and spatial variability of the sodium atom density induces changing errors on wavefront measurements, especially with Extremely Large Telescopes (ELTs) for which the LGS elongation is larger. In the framework of the Thirty-Meter-Telescope project (TMT), the AO-Lab of the University of Victoria (UVic) has built an LGS-simulator test bed in order to assess the performance of new centroiding algorithms for LGS Shack-Hartmann wavefront sensors (SH-WFS). The design of the LGS-bench is presented, as well as laboratory SH-WFS images featuring 29x29 radially elongated spots, simulated for a 30-m pupil. The errors induced by the LGS variations, such as focus and spherical aberrations, are characterized and discussed. This bench is not limited to SH-WFS and can serve as an LGS-simulator test bed to any other LGS-AO projects for which sodium layer fluctuations are an issue.