Polarimetry with Disordered Photonic Structures

Abstract

In conventional Stokes polarimetry, where the polarimetric information is obtained from a series of intensity measurements, stable and accurate measurements typically require the optical elements to be carefully designed. Here, we propose a paradigm shift where deep neural network assisted polarimeters based on disordered photonic structures perform high quality polarimetric measurements while completely removing the need for specially designed polarization analyzers, demonstrating how disordered photonic structures fabricated without the use of any nanolithography techniques can enable accurate analysis of optical signals. We implement this concept with disorder- engineered nano-scatterers that allow for analyzing varying degrees of disorder and cellophane film that demonstrate the cost-saving potential of the concept. We demonstrate polarimetric performances, calibrated using deep neural networks, that are comparable to commercial polarimeters, does not require prior knowledge of the input wavelength and show a high degree of mechanical stability.