Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm

To satisfy the demands of high image quality and resolutions, telescope alignment is indispensable. In this paper, a wavefront sensorless method based on a modified stochastic parallel gradient descent algorithm (SPGD) called the adaptive moment estimation SPGD (Adam SPGD) algorithm is proposed. Sim...

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Main Authors: Min Li, Xin Liu, Junbo Zhang, Hao Xian
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Photonics
Subjects:
Online Access:https://www.mdpi.com/2304-6732/11/11/993
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author Min Li
Xin Liu
Junbo Zhang
Hao Xian
author_facet Min Li
Xin Liu
Junbo Zhang
Hao Xian
author_sort Min Li
collection DOAJ
description To satisfy the demands of high image quality and resolutions, telescope alignment is indispensable. In this paper, a wavefront sensorless method based on a modified stochastic parallel gradient descent algorithm (SPGD) called the adaptive moment estimation SPGD (Adam SPGD) algorithm is proposed. Simulations are carried out using a four-mirror telescope, whose aperture is 6 m and fields of view are Φ2°. Three misalignments are shown as examples. Positions of the secondary mirror and third mirror are employed to compensate aberrations. The results show that merit functions and energy distributions of corrected images match with the designed ones. The mean RMS of residual wavefront errors is smaller than <i>λ</i>/14 (<i>λ</i> = 0.5 μm), indicating that the misalignments are well compensated. The results verify the effectiveness of our method.
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spelling doaj-art-106d28ea52d3457a88baed8ffe1384f72025-08-20T01:53:57ZengMDPI AGPhotonics2304-67322024-10-01111199310.3390/photonics11110993Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent AlgorithmMin Li0Xin Liu1Junbo Zhang2Hao Xian3National Laboratory on Adaptive Optics, Chengdu 610209, ChinaInstitute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, ChinaNational Laboratory on Adaptive Optics, Chengdu 610209, ChinaNational Laboratory on Adaptive Optics, Chengdu 610209, ChinaTo satisfy the demands of high image quality and resolutions, telescope alignment is indispensable. In this paper, a wavefront sensorless method based on a modified stochastic parallel gradient descent algorithm (SPGD) called the adaptive moment estimation SPGD (Adam SPGD) algorithm is proposed. Simulations are carried out using a four-mirror telescope, whose aperture is 6 m and fields of view are Φ2°. Three misalignments are shown as examples. Positions of the secondary mirror and third mirror are employed to compensate aberrations. The results show that merit functions and energy distributions of corrected images match with the designed ones. The mean RMS of residual wavefront errors is smaller than <i>λ</i>/14 (<i>λ</i> = 0.5 μm), indicating that the misalignments are well compensated. The results verify the effectiveness of our method.https://www.mdpi.com/2304-6732/11/11/993telescope alignmentwavefront sensorless methodAdam SPGD algorithmmulti-field alignmenthigh precision
spellingShingle Min Li
Xin Liu
Junbo Zhang
Hao Xian
Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
Photonics
telescope alignment
wavefront sensorless method
Adam SPGD algorithm
multi-field alignment
high precision
title Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
title_full Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
title_fullStr Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
title_full_unstemmed Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
title_short Telescope Alignment Method Using a Modified Stochastic Parallel Gradient Descent Algorithm
title_sort telescope alignment method using a modified stochastic parallel gradient descent algorithm
topic telescope alignment
wavefront sensorless method
Adam SPGD algorithm
multi-field alignment
high precision
url https://www.mdpi.com/2304-6732/11/11/993
work_keys_str_mv AT minli telescopealignmentmethodusingamodifiedstochasticparallelgradientdescentalgorithm
AT xinliu telescopealignmentmethodusingamodifiedstochasticparallelgradientdescentalgorithm
AT junbozhang telescopealignmentmethodusingamodifiedstochasticparallelgradientdescentalgorithm
AT haoxian telescopealignmentmethodusingamodifiedstochasticparallelgradientdescentalgorithm