Diffractive Neural Network on a 3D Photonic Device for Spatial Mode Bases Mapping

Mode‐division multiplexing (MDM) techniques based on various spatial mode bases are of great significance in satisfying the demand for efficient capacity scaling. With the development of diverse MDM systems, the seamless connection and integration between them are particularly important. In this scenario, a laudable goal would be to implement flexible spatial mode bases mapping. To break the barrier between different MDM systems, a compact 3D photonic device based on diffractive neural network (DNN) is presented for mode bases mapping, transforming orbital angular momentum (OAM) modes into linearly polarized (LP) modes. Through simulations and experiments, a four‐layer optical neural network mode mapper (ONNMM) is successfully demonstrated, exhibiting its capability of mapping five orthogonal spatial modes between OAM and LP mode bases simultaneously. The ONNMM shows a vision for grooming MDM optical communications and interconnects, as well as other emerging applications enabled by intelligent 3D integrated compact devices. This work achieves a four‐layer optical neural network mode mapperchip with a compact size of 160 × 160 × 150 µm using two‐photon polymerization. It transforms five orbital angular momentum modes into linearly polarized modes experimentally and shows polarization independence, which can operate within a wavelength bandwidth of 1550 ± 30 nm. This approach offers a solution to realize a compact mode‐division multiplexing (MDM) system, thereby boosting the development of MDM long‐distance optical communications.