Polarization conversion devices which can manipulate the polarization status of electromagnetic waves are essential to various areas of photonic applications such as communication, imaging, and remote sensing. Due to its wide bandwidth and high penetration through dielectric materials, THz wave, range from 0.1 to 10 THz is increasingly popular for noninvasive screening, high-resolution imaging, and more precise data collection. Metamaterials (MM) are artificial materials fabricated from repeated arrays of subwavelength-sized meta-atoms, and MM-based THz polarization conversion devices can be thin, extremely compact, easy to integrate, and even flexible, unlike conventional polarization devices. In light of that information, we utilized a stereo-metamaterial (SMM) structure for new-generation THz polarizers converting the polarization from linearly to circularly and elliptically polarized wave at the THz frequency range in reflection mode. In this work, we present the processes and results of the inverse design of SMM using the artificial neural network (ANN), trained by various parameters, including polarization status and ellipticity angle, to achieve highly efficient device performance. Training and testing our ANN with the created datasets by simulation for the inverse design of the device, design parameters were obtained by giving an artificial EM response or ellipticity angle spectrum or vice versa more efficiently and rapidly. With the device fabricated based on the ANN-powered design, we demonstrated effective sensing of different polarization statuses using THz polarimetry spectroscopy.
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