SPGD and Newton iteration mixed algorithm used in freeform surface metrology

Yu Zhang; Xiaobo Tian; Rongguang Liang

doi:10.1016/j.optlaseng.2020.106050

SPGD and Newton iteration mixed algorithm used in freeform surface metrology

Yu Zhang, Xiaobo Tian, Rongguang Liang

Optical Sciences

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

17 Scopus citations

Abstract

Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metrology. To ensure the efficiency, a stochastic parallel gradient descent (SPGD) and Newton iteration mixed algorithm to drive the DM has been proposed, it can achieve the minimum value of the optimization and is suitable for the different interferograms. The simulation and experimental results verify the correctness and feasibility of the proposed DM driving algorithm.

Original language	English (US)
Article number	106050
Journal	Optics and Lasers in Engineering
Volume	129
DOIs	https://doi.org/10.1016/j.optlaseng.2020.106050
State	Published - Jun 2020

Keywords

Deformable mirror
Freeform surface
Newton iteration algorithm
Optimization
Stochastic parallel gradient descent algorithm

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics
Mechanical Engineering
Electrical and Electronic Engineering

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10.1016/j.optlaseng.2020.106050

Cite this

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title = "SPGD and Newton iteration mixed algorithm used in freeform surface metrology",

abstract = "Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metrology. To ensure the efficiency, a stochastic parallel gradient descent (SPGD) and Newton iteration mixed algorithm to drive the DM has been proposed, it can achieve the minimum value of the optimization and is suitable for the different interferograms. The simulation and experimental results verify the correctness and feasibility of the proposed DM driving algorithm.",

keywords = "Deformable mirror, Freeform surface, Newton iteration algorithm, Optimization, Stochastic parallel gradient descent algorithm",

author = "Yu Zhang and Xiaobo Tian and Rongguang Liang",

note = "Funding Information: This work was supported by the National Natural Science Foundation of China (NSFC) ( 61905039 ); Jilin Scientific and Technological Development Program ( 20190701018GH ); Education Department of Jilin Province ( JJKH20190691KJ ) and State Key Laboratory of Applied Optics . Publisher Copyright: {\textcopyright} 2020 Elsevier Ltd",

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doi = "10.1016/j.optlaseng.2020.106050",

language = "English (US)",

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T1 - SPGD and Newton iteration mixed algorithm used in freeform surface metrology

AU - Zhang, Yu

AU - Tian, Xiaobo

AU - Liang, Rongguang

N1 - Funding Information: This work was supported by the National Natural Science Foundation of China (NSFC) ( 61905039 ); Jilin Scientific and Technological Development Program ( 20190701018GH ); Education Department of Jilin Province ( JJKH20190691KJ ) and State Key Laboratory of Applied Optics . Publisher Copyright: © 2020 Elsevier Ltd

PY - 2020/6

Y1 - 2020/6

N2 - Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metrology. To ensure the efficiency, a stochastic parallel gradient descent (SPGD) and Newton iteration mixed algorithm to drive the DM has been proposed, it can achieve the minimum value of the optimization and is suitable for the different interferograms. The simulation and experimental results verify the correctness and feasibility of the proposed DM driving algorithm.

AB - Freeform surfaces are widely used in advanced optical systems. In order to accurately measure freeform surfaces, an adaptive interferometer with deformable mirror (DM) has been developed for the freeform surface metrology. To ensure the efficiency, a stochastic parallel gradient descent (SPGD) and Newton iteration mixed algorithm to drive the DM has been proposed, it can achieve the minimum value of the optimization and is suitable for the different interferograms. The simulation and experimental results verify the correctness and feasibility of the proposed DM driving algorithm.

KW - Deformable mirror

KW - Freeform surface

KW - Newton iteration algorithm

KW - Optimization

KW - Stochastic parallel gradient descent algorithm

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SPGD and Newton iteration mixed algorithm used in freeform surface metrology

Abstract

Keywords

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