Orbital angular momentum holographic multicasting for switchable and secure wireless optical communication links

Achromatic CMOS-Integrated Four-Bit Orbital Angular Momentum Mode Detector at Three Wavelengths

The simultaneous detection of the orbital angular momentum (OAM) and wavelength offers new opportunities for optical multiplexing. However, because of the dispersion of lens functions for Fourier transformation, the mode conversions at distinct wavelengths cannot be achieved in the same plane. Here we propose an ultracompact achromatic complementary metal oxide semiconductor (CMOS)-integrated OAM mode detector. Specifically, a spatial multiplexed scheme, randomly interleaving the phase distributions for distributing the superposed OAM modes into preset positions at distinct wavelengths, is presented. In addition, such a nanoprinted achromatic OAM detector featuring a microscale size and a short focal length can be integrated onto a CMOS chip. Consequently, the four-bit incident light beams at three discrete wavelengths (633, 532, and 488 nm) can be distinguished with a high degree of accuracy evaluated by the average standardized Euclidean distance of ∼0.75 between the analytical and target results. Our results showcase a miniaturized platform for achieving high-capacity information processing.

Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed, ultrawide bandwidths and low energy consumption because the optical dimensions (time, space, wavelength, and polarization) could be utilized to increase the degree of freedom. However, due to the lack of the capability to extract the information features in the orbital angular momentum (OAM) domain, the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model. Here, we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network (CNN) based on Laguerre-Gaussian (LG) beam modes with diverse diffraction losses. The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction, and deep-learning diffractive layers as a classifier. The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding, leading to an accuracy as high as 97.2% for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes, as well as a resistance to eavesdropping in point-to-point free-space transmission. Moreover, through extending the target encoded modes into multiplexed OAM states, we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%. Our work provides a deep insight to the mechanism of machine learning with spatial modes basis, which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

Nanoprinted Diffractive Layer Integrated Vertical-Cavity Surface-Emitting Vortex Lasers with Scalable Topological Charge

Vertical-cavity surface-emitting lasers (VCSELs) represent an attractive light source to integrate with OAM structures to realize chip-scale vortex lasers. Although pioneering endeavors of VCSEL-based vortex lasers have been reported, they cannot achieve large topological charges (less than l = 5) due to the insufficient space-bandwidth product (SBP) caused by the inherent limited device size. Here, by integrating a nanoprinted OAM phase structure on the VCSELs, we demonstrate a vortex microlaser with a low threshold and simple structure. A monolithic microlaser array with addressable control of vortex beams with different topological charges (l = 1 to l = 5) was achieved. Nanoprinting offers high degrees of freedom for the manipulation of spatial structures. To address the challenge of insufficient SBP, two-layer cascaded spiral phase plates were designed. Thereby, a vortex beam with l = 15 and mode purity of 83.7% was obtained. Our work paves the way for future chip-scale OAM-based information multiplexing with more channels.