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Seokyoung Ju

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Proceedings Article | 27 November 2023 Paper

Reconstruction error analysis in LGS tomography for adaptive optics applications

S. Han, J. Joo, S. Ju, J. Lee, T. Butterley

Proceedings Volume 12767, 127670J (2023) https://doi.org/10.1117/12.2687115

KEYWORDS: Tomography, Error analysis, Adaptive optics, MATLAB, Reconstruction algorithms, Algorithm development, Turbulence, Reliability, Atmospheric turbulence

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We present an implementation of tomography using MATLAB, specifically focusing on the Learn & Apply technique. The primary objective of our study is to assess the level of reconstruction errors encountered in tomography. We compare the results obtained from our implementation with the Object-Oriented, Matlab and Adaptive Optics (OOMAO) code, aiming to quantify the discrepancies between the two approaches. Furthermore, we investigate the impact of laser guide star (LGS) altitude variations on the reconstruction errors. By simulating tomographic reconstructions under different LGS altitudes, we analyze the variations in the error values and their relation to the atmospheric conditions. Additionally, we examine the influence of LGS divergence angle on the reconstruction errors, considering various divergence angles in our simulations. Afterwards, we explore the effect of increasing the number of layers used in the learning process on the simulation time.

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