Orbital angular momentum terahertz holography and computing enabled by low-loss wax-imprinted diffractive optical neural networks
Berardi Sensale‐Rodriguez, Wei Jia · 2024
In this work we discuss a diffractive optical neural network approach for recognizing the mode of OAM waves and their superposition. Experimentally, diffractive neural networks are fabricated through an imprinting technique with low loss parowax material. We also show that the diffractive networks can enable mathematical operations through the topological charges of the superposed OAM waves, being capable of displaying these results in a digit format across different operation planes. The approaches herein are general and could be used to arbitrarily manipulate multiple superposed OAM states, which can enable a myriad of potential applications in the next generation of terahertz communications systems.