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Complete self-calibration compact binary magneto-optic rotator based Mueller matrix polarimetry.
Opt Express ; 29(19): 30392-30408, 2021 Sep 13.
Article em En | MEDLINE | ID: mdl-34614764
ABSTRACT
Magneto-optic (MO) based Mueller matrix polarimetry (MMP) has several advantages of compact size, no-mechanical movement and high speed. Inaccuracies of components in the polarization state generator (PSG) optical parameters will influence the measurement accuracy of MMP. In this paper, we present a PSG self-calibration method in the compact MMP based on binary MO polarization rotators. Since PSG can generate enough numbers of non-degenerate polarization states, the optical parameters in PSG and the Mueller matrix of the sample can totally be numerically solved, which realizes a self-calibration in the PSG. Combining the previous self-calibration method in polarization state analyzer (PSA), we realize a complete self-calibration compact MO based MMP. Based on the numerical simulation results, the errors of measured phase retardance and optical axis of the sample decrease two to three orders of magnitude after applying the PSG self-calibration method. In experimental results of a variable retarder as a sample, the Euclidean distance of retardance between the measurement and reference curves comparing PSG self-calibration with no PSG self-calibration can be reduced from 0.035 rad to 0.033 rad and the Euclidean distance of optical axis can be reduced from 3.39° to 1.51°. Compared with the experimental results, the numerical simulation results more accurately verify the performance of the presented PSG self-calibration method without being influenced by other errors because the Mueller matrix of the sample is known and the error source only comes from these components in PSG.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article