Caroline Kulcsár

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCGs computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKFs cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKFs sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

Towards minimum-variance control of ELTs AO systems

Minimum-variance control of adaptive optics (AO) systems relies on a stochastic dynamical model of the perturbation and on models of the components, including loop delays. Resulting LQG controllers have been implemented in SCAO and WFAO both on laboratory benches and on-sky. Their efficiency has been recognized in several modes of operation, e.g. i) on-sky control of TT or low-order modes with vibration mitigation (SPHERE, GPI, CANARY, Raven, GeMS, in H2 formulation at the McMath-Pierce solar telescope) ii) full SCAO mode (CANARY) and MOAO mode (CANARY, Raven) and iv) in general it is advocated to control the low-order modes in laser tomography systems (E-ELT HARMONI LTAO, NFIRAOS). We first point out two examples related to VLT AO controllers to illustrate the need for RTC flexibility. The implementation of LQG control in the framework of the future ELTs raises many questions related both to real-time control computation and associated parameter updates (at a far lower rate), and to the performance that can be reached compared with simpler control strategies. By gathering many lab and on-sky results, we draw the performance trends observed so far. We then outline some promising research directions for control design and implementations for future ELTs AO systems.

Tip-tilt modelling and control for GeMS: a performance comparison of identification techniques

Perturbation modelling and vibration compensation are key issues to reach better performance in adaptive optics systems for VLTs and future ELTs. In this context, an LQG controller is to be implemented for the tip-tilt loop of the multi-conjugate adaptive optics instrument GeMS. The performance of several models, associated with their identification techniques are considered for tip-tilt disturbance.

Analysis of GeMS tip-tilt on-sky data: LQG implementation for vibration rejections

Adaptive Optics (AO) systems aim at detecting and correcting for optical distortions induced by atmospheric turbulences on ground based telescopes astronomical images. They are also extremely sensitive to extraneous sources of perturbations such as vibrations, which degrade their performance. A new well defined vibration at 37Hz has been detected in January 2015 and is still currently affecting the Gemini South telescope secondary mirror. We show how its existence limits the performance of the operational systems at Gemini South: The Gemini Planet Imager (GPI) and the Gemini Multi-Conjugated AO system (GeMS). We further focus on how these vibrations are affecting GeMS performance and propose to implement the Tip-Tilt control strategy first tested on CANARY and routinely used on SPHERE. It combines identification of a sum of auto-regressive models of order 2 with a Linear Quadratic Gaussian (LQG) control. LQG is now routinely used for Tip-Tilt and focus control for GPI and has been successfully tested on all modes on CANARY. We show that the expected gain in performance brought by this LQG Tip-Tilt control strategy on GeMS compared with an Integral Controller is on the order of 15 to 20mas. The analysis was conducted in ”replay mode” using GeMS Tip-Tilt on-sky data. This allows realistic performance assessment before implementation inside the Real-Time Computer (RTC) of GeMS and on-sky tests during the first semester of 2016.

First on-sky validation of full LQG control with vibration mitigation on the CANARY MOAO pathfinder (Orale)

We present in this paper the very first on-sky results of full Multi-Object Adaptive Optics (MOAO) LQG control (i.e. all modes, with coupling, controlled with an LQG regulator), obtained in Spring 2013 on the CANARY demonstrator at the William Herschel Telescope (La Palma, Spain). The MOAO on-sky pathfinder CANARY features two AO configurations that have both been tested: single-conjugated AO and multi-object AO with NGS and NGS+LGS, together with vibration mitigation on tip and tilt modes. The successful MOAO results are presented and shortly analyzed in terms of performance and tuning.