Sub‐THz 3D printed lens based on diffractive neural network for low‐cost detection of orbital angular momentum states

Abstract

AbstractAccurate detection of orbital angular momentum (OAM) is one of the critical techniques for OAM‐related communications. However, conventional OAM identification approaches are often complicated and costly. In this letter, a convenient method based on diffraction neural network (DNN) is presented for OAM states detection in the sub‐terahertz (sub‐THz) regime. The optimal phase distribution of the lens for OAM state detection is obtained from DNN training. Then, a prototype based on three‐dimensional printing is fabricated according to the training results. Numerical simulation and experiment are performed at 140 GHz to verify the proposed approach. The results show that the proposed method can accurately detect the OAM state with lower complexity. This convenient detection approach can provide a novel pathway for realizing low‐cost THz OAM receiving systems, promoting the development of future communication technology.