Versatile manipulation of orbital angular momentum combs enabled by diffractive neural networks

The orbital angular momentum (OAM) of light, which can be created through the helical phase front, has attracted significant attention and found numerous applications in both classical and quantum optics. The manipulation of light's OAM has evolved from the generation of a single OAM mode to the simultaneous generation of multiple OAM modes. As a typical kind of multiple OAM superposition mode, an OAM comb features a discrete, equispaced OAM spectrum. Similar to how optical frequency combs promoted many technical revolutions in optics, such an OAM comb may likewise pave the way for OAM-related applications. Here, we propose an approach to versatilely manipulating OAM combs based on a two-layer fully connected diffractive neural network (DNN). We achieve four kinds of manipulation and transformations on OAM combs, including four arithmetic operations, square and square root operations, high-pass/low-pass/band-pass filtering, and arbitrary transformation between two OAM combs, etc. All four kinds of manipulation reach an average accuracy of 99.65% and the lowest accuracy of over 99%. Our work may advance the research on OAM combs and open new prospects for applications based on OAM comb sources.