Zili Cai | Searcharxiv

arXiv2026

Dynamically Reconfigurable Optical Skyrmions Enabled by a Silicon Microring Optical Phased Array for Robust Free-Space Communication

Optical skyrmions offer a robust vectorial information degree of freedom for free-space communication, but practical deployment requires a compact platform capable of active topological reconfiguration. Here, we propose a silicon microring-resonator optical phased array that integrates spin-selective emission and programmable phase control on a single chip. Optimized inner- and outer-grating microring emitters provide decoupled LCP and RCP radiation bases with polarization fractions of 90.27% and 91.40%, enabling active switching between Néel-type and Bloch-type skyrmions, while dynamically tuning the skyrmion number across Nsk =-1.914 to 1.918. Using these programmable topological states, a 4-symbol free-space communication link is constructed and compared with ideal LG-OAM encoding under Kolmogorov turbulence. The skyrmion-encoded link maintains a lower symbol error rate over a broader turbulence range, demonstrating that topological observables are more robust than scalar OAM modes. These results establish actively reconfigurable optical skyrmions as compact, programmable, and turbulence-tolerant information carriers for next-generation free-space optical communication.

physics.optics↗

arXiv2025

RoNo: A novel way in generating reconfigurable on-chip nonlinear activation functions

Due to the limitations of Moore's Law and the increasing demand of computing, optical neural network (ONNs) are gradually coming to the stage as an alternative to electrical neural networks. The control of nonlinear activation functions in optical environments, as an important component of neural networks, has always been a challenge. In this work, firstly, we use inverse design tools to design a optical patterned area in silicon-carbide-on-insulator. This patterned area could generate two different nonlinear responses of the amplitude. Secondly, the patterned region is integrated with a control network to form a reconfigurable on-chip nonlinear activation function generator for wave-based analog computing. Experiment shows that neural network that uses such a system as an activation function performs well in the MNIST handwritten dataset and CIFAR-10, respectively. Compared to previous works, we propose a novel approach to generate on-chip reconfigurable activation functions in optical neural networks, which achieves compact footprint and enables high-quality activation function generation.

physics.optics↗