Photonics

The investigation of topological structures and phases in photonics has created unprecedented opportunities for developing advanced on-chip terahertz waveguide devices. Topological waveguides, which exhibit reduced backscattering and improved turning characteristics, provide a potential route toward more compact and robust on-chip photonic systems. Unlike conventional waveguides, the mode fields in topological waveguides are localized at the domain wall interface and decay into the bulk, making their bending loss sensitive to both the bulk thickness and the photonic band gap. However, a comprehensive analysis that simultaneously considers the bulk thickness, photonic band gap, and bending loss remains lacking. In this paper, we comprehensively studied the relationship between the bending loss in valley Hall photonic crystal waveguides and both the bulk thickness and photonic band gap width, using an all-silicon terahertz platform. The results provide guidance and a reference for the routing and design of terahertz photonic systems.

This paper presents a cascaded imaging method that combines low-light enhancement and visible–long-wavelength infrared (VIS-LWIR) image fusion to mitigate image degradation in dark environments. The framework incorporates a Low-Light Enhancer Network (LLENet) for improving visible image illumination and a heterogeneous information fusion subnetwork (IXNet) for integrating features from enhanced VIS and LWIR images. Using a joint training strategy with a customized loss function, the approach effectively preserves salient targets and texture details. Experimental results on the LLVIP, M³FD, TNO, and MSRS datasets demonstrate that the method produces high-quality fused images with superior performance evaluated by quantitative metrics. It also exhibits excellent generalization ability, maintains a compact model size with low computational complexity, and significantly enhances performance in high-level visual tasks like object detection, particularly in challenging low-light scenarios.

To address the problem of insufficient user fairness in multi-user multiple-input single-output visible light communication systems, this paper proposes a joint design scheme of intelligent reflecting surface configuration and precoding to maximize the minimum signal-to-interference-plus-noise ratio among users. To tackle the constructed non-convex optimization problem, this paper proposes an alternating optimization algorithm, which alternately fixes the intelligent reflecting surface configuration matrix and the precoding matrix, decomposes the original problem into subproblems that can be transformed into convex forms for efficient solution, and iteratively solves them using the bisection search and relaxation–quantization methods. Simulation results show that, compared with the minimum mean square error and zero-forcing precoding schemes based on distance greedy matching, the proposed method improves the minimum signal-to-interference-plus-noise ratio of users by 12 and 16 percent. Furthermore, when user locations are fixed, the minimum signal-to-interference-plus-noise ratio under the optimal deployment position of the intelligent reflecting surface increases by 8 percent compared with the random user distribution scenario.