Deep learning-enabled broadband full-Stokes polarimeter with a portable fiber optical spectrometer

Abstract

Portable fiber optical spectrometers (PFOSs) have been widely used in the contemporary industrial and agricultural production and life due its low cost and small volume. PFOSs mainly combine one fiber to guide light and one optical spectrometer to detect spectra. In this work, we demonstrate that PFOSs can work as a broadband full-Stokes polarimeter through slightly bending the fiber several times and establishing the mapping relationship between the Stokes parameters S^ and the bending-dependent light intensities I^, i.e., S^=f(I^). The different bending geometries bring different birefringence effects and reflection effects that change the polarization state of the out-going light. In the meanwhile, the grating owns a polarization-depended diffraction efficiency especially for the asymmetric illumination geometry that introduces an extrinsic chiroptical effect, which is sensitive to both the linear and spin components of light. The minimum mean squared error (MSE) can reach to smaller than 1% for S 1, S 2, and S 3 at 810 nm, and the averaged MSE in the wave band from 440 nm to 840 nm is smaller than 2.5%, where the working wavelength can be easily extended to arbitrary wave band by applying PFOSs with proper parameters. Our findings provide a convenient and practical method for detecting full-Stokes parameters.