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Future Adaptive Optics (AO) systems aim at delivering sharper and more uniform image quality among wider Field of View (FoV) in short wavelengths. The concept of Multi Conjugate Adaptive Optics (MCAO) makes this possible by using multiple guide stars and deformable mirrors. Generating an optimal tomography algorithm that minimizes the impact of various error sources is one of the most critical parts in the development of future AO systems. The first Visible band AO facility, MCAO Assisted Visible Imager and Spectrograph (MAVIS), is proposed to achieve 15% Strehl Ratio among 30” square FOV. In this thesis proposal talk, I will introduce the planned work during my PhD on the tomography algorithm for MAVIS as well as other future MCAO systems in general. In particular, the three stages of my thesis project are: 1.) End-to-end simulations for the estimation of MAVIS performance, 2.) Tomography algorithm optimization with Learn and Apply method, Predictive Control and other noise suppression methods, 3.) Demonstrating experiments on AITC Optics Test Bench. |
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