Real-time computing methods for astronomical. Adaptive Optics.
An iterative, wavelet-based real-time reconstructor for atmospheric tomography.
Johannes Kepler Universität Linz (JKU)
Information and Communication Technology
Astronomical imaging with ground based telescopes suffers from quickly varying optical distortions in the atmosphere. Sharpness and contrast of these images are essential for astronomical observations therefore, Adaptive Optics (AO) systems are applied. These systems are based on wavefront sensors, deformable mirrors and appropriate control algorithms.
Challenges and goals
Satisfying the demands on the AO system of the Extremely Large Telescope (ELT) of the European Southern Observatory is a challenging task In real time huge amounts of data have to be processed and thousands of actuators controlled by elaborated algorithms. Our project aims to develop and implement efficient control algorithms for the ELT first light instrument MAORY.
Mathematical and computational methods
In our project we developed and implemented an efficient real time reconstruction algorithm for the ELT instrument MAORY on the high performance hardware of the industrial partner. Our algorithm, called Finite Element Wavelet Hybrid Algorithm (FEWHA), is a conjugate gradient (CG) based solver for atmospheric tomography. FEWHA utilizes a dual domain discretization strategy into a wavelet and finite element domain to obtain sparse operators. The matrix free representation of these operators leads to a significant reduction in the computational load and memory resources. Moreover, the method is highly parallelizable. We use preconditioning and an augmented Krylov subspace method in order to reduce the number of CG iterations.
Results and Benefits
The main result of our project is an accurate and fast solver for atmospheric tomography optimized for the hardware of the industrial partner. The iterative real time reconstructor FEWHA is running in real time and provides an excellent reconstruction quality for the MAORY instrument. Microgate has benefited from the knowledge transfer on AO algorithms that can be used in further developments. Moreover, the company is able to extend its product portfolio and provide a package including efficient hardware and software for the real time control of AO systems, not limited to astronomy applications.