A novel method for telescope polarization modeling based on an artificial neural network  

作　　者：Jian-Guo Peng Shu Yuan Kai-Fan Ji Zhi Xu 

机构地区：[1]Yunnan Observatories,Chinese Academy of Sciences,Kunming 650216,China [2]University of Chinese Academy of Sciences,Beijing 100049,China

出　　处：《Research in Astronomy and Astrophysics》2021年第7期41-50,共10页天文和天体物理学研究（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.11833010,11773069,11773072,11873091 and 12073077);Key Research and Development Project of Yunnan Province(202003AD150019);Yunnan Province Basic Research Plan(2019FA001);the CAS‘Light of West China’Program(Y9XB015001)。

摘　　要：The polarization characteristics of an astronomical telescope is an important factor that affects polarimetry accuracy. Polarization modeling is an essential means to achieve high precision and efficient polarization measurement of the telescope, especially for the alt-azimuth mount telescope. At present, the polarization model for the telescope(i.e., the physical parametric model) is mainly constructed using the polarization parameters of each optical element. In this paper, an artificial neural network(ANN) is used to model the polarization characteristics of the telescope. The ANN model between the physical parametric model residual and the pointing direction of the telescope is obtained, which reduces the model deviation caused by the incompleteness of the physical parametric model. Compared with the physical parametric model, the model fitting and predictive accuracy of the New Vacuum Solar Telescope(NVST) is improved after adopting the ANN model. After using the ANN model, the polarization cross-talk from I to Q, U, and V can be reduced from 0.011 to 0.007, and the crosstalk among Q, U, and V can be reduced from 0.047 to 0.020, which effectively improves the polarization measurement accuracy of the telescope.

关 键 词：techniques:polarimetric telescopes POLARIZATION instrumentation:polarimeters 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] P111[自动化与计算机技术—控制科学与工程]