Performances Index and Convergence Speed of Parallel Gradient Descent Algorithm in Adaptive Optics of Point Source

Bo, 陈波 Chen; Huizhen, 杨慧珍 Yang; Jinbao, 张金宝 Zhang; Xinyang, 李新阳 Li; Wenhan, 姜文汉 Jiang

doi:10.3788/aos20092905.1143

Cited by 7 publications

(1 citation statement)

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“…In our case, a point source will be imaged on the focal plane and several metrics can be used to evaluate the system performance (Chen et al 2009). Here the mean radius of image spot is chosen as the performance metric to be minimized:…”

Section: Principle Of Spgd Algorithmmentioning

confidence: 99%

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

Dong¹,

Ren²,

Zhang³

2011

Res. Astron. Astrophys.

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An adaptive optics (AO) system based on stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of stellar coronagraph in order to further improve the contrast. The principle of SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of SPGD algorithm is demonstrated by experimental system featured with a 140-actuators deformable mirror (DM) and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph. The LCA can modulate the incoming light to generate a pupil apodization mask in any pattern. A circular stepped pattern is used in our preliminary experiment and the image contrast shows improvement from 10 -3 to 10 -4.5 at angular distance of 2λ/D after corrected by SPGD based AO.

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Section: Principle Of Spgd Algorithmmentioning

confidence: 99%

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

Dong¹,

Ren²,

Zhang³

2011

Res. Astron. Astrophys.

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High-speed SPGD wavefront controller for an adaptive optics system without wavefront sensor

Wang

et al. 2010

SPIE Proceedings

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A non-conventional adaptive optics system based on direct system performance metric optimization is illustrated. The system does not require wave-front sensor which is difficult to work under the poor condition such as beam cleanup for the anomalous light beam. The system comprises a high speed wavefront controller based on Stochastic Parallel Gradient Descent (SPGD) Algorithm, a deformable mirror, a tip/tilt mirror and a far-field system performance metric sensor. The architecture of the wave-front controller is based on a combination of Field Programmable Gate Array (FPGA) and floating-point Digital Signal Processor (DSP). The Zernike coefficient information is applied to improve the iteration speed. The experimental results show that the beam cleanup system based on SPGD keep a high iteration speed. The controller can compensate the wavefront aberration and tilt excursion effectively.

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Optimization of Stochastic Parallel Gradient Descent Algorithm via Power Spectrum Method

Song¹,

Chen²,

Wang³

et al. 2016

Appl. Math. Inf. Sci.

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Performances Index and Convergence Speed of Parallel Gradient Descent Algorithm in Adaptive Optics of Point Source

Cited by 7 publications

References 0 publications

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

High-speed SPGD wavefront controller for an adaptive optics system without wavefront sensor

Optimization of Stochastic Parallel Gradient Descent Algorithm via Power Spectrum Method

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