Opto-Electronic Engineering, Volume. 44, Issue 7, 701(2017)

Optical microcavity transmission spectrum fitting algorithm based on the implicit function model

Xiaoting Wang1, Ruiqiang Chen1, Shundi Hu1、*, Peng Zhao1, Luhong Wen1, and Xiang Wu2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    The optical microcavity has high Q factors and high sensitivity, and has a good application prospect in high-precision biosensing. In order to deal with the problem that the Lorentz fitting algorithm cannot fit the asymmetric waveform and the splitting mode waveform of the optical microcavity, the implicit function model al-gorithm is proposed. Firstly, according to the method, the template waveform was established and operated by panning and zooming.Then the parameter values were optimized by the Levenberg-Marquardt (LM) algorithm. Finally, data fitting of symmetrical waveform, asymmetric waveform and splitting mode waveform could be achieved. Through constructing the data acquisition system of optical microcavity, the Gauss, the Lorentz and the implicit function model algorithm were used to fit the experimental data of different refractive index of solutions. The results show that MSE of the implicit function model algorithm is one order of magnitude lower than other two algorithms, and has a coefficient of determination (R2) of 0.99. The resonant frequency error of implicit func-tion model algorithm is the smallest, the resonant frequency of implicit function model algorithm is the largest, and the sensitivity of implicit function model algorithm is the highest. Therefore, the fitting effect of the implicit function model algorithm is better and it can efficiently improve the sensitivity of the optical microcavity.

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    Xiaoting Wang, Ruiqiang Chen, Shundi Hu, Peng Zhao, Luhong Wen, Xiang Wu. Optical microcavity transmission spectrum fitting algorithm based on the implicit function model[J]. Opto-Electronic Engineering, 2017, 44(7): 701

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    Paper Information

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    Received: Apr. 20, 2017

    Accepted: --

    Published Online: Nov. 27, 2017

    The Author Email: Hu Shundi (hushundi@nbu.edu.cn)

    DOI:10.3969/j.issn.1003-501x.2017.07.006

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