Machine-Learning-Optimized OAM Excitation in Optical Fibers

Abstract

We develop a machine learning algorithm for in situ control and optimization of OAM excitation in optical fibers, ensuring high-purity and low-loss coupling. The algorithm can correct intentional misalignments, as well as compensate alignment drift.