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

Bing Dong; De Qing Ren; Xi Zhang

doi:10.1088/1674-4527/11/8/011

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

Bing Dong^*, De Qing Ren, Xi Zhang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

14 Citations (Scopus)

Abstract

An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of 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 an angular distance of 2λ/D after being corrected by SPGD based AO.

Original language	English
Pages (from-to)	997-1002
Number of pages	6
Journal	Research in Astronomy and Astrophysics
Volume	11
Issue number	8
DOIs	https://doi.org/10.1088/1674-4527/11/8/011
Publication status	Published - Aug 2011
Externally published	Yes

Keywords

instrumentation: adaptive optics
methods: laboratory
techniques: image processing, coronagraph

Access to Document

10.1088/1674-4527/11/8/011

Cite this

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title = "Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph",

abstract = "An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of 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 an angular distance of 2λ/D after being corrected by SPGD based AO.",

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AU - Ren, De Qing

AU - Zhang, Xi

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AB - An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of 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 an angular distance of 2λ/D after being corrected by SPGD based AO.

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KW - methods: laboratory

KW - techniques: image processing, coronagraph

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

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Keywords

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