Integrated optical phased arrays (OPAs) are pivotal for next-generation solid-state light detection and ranging (LiDAR), offering high-speed, inertia-free beam steering in a compact form factor. However, achieving high angular resolution alongside multi-watt emission power remains a formidable challenge. In this work, we present a 3D-integrated silicon-silicon nitride (Si-SiN) hybrid OPA comprising 4096 (4 × 1024) elements, packaged with a CMOS driver chip via flip-chip bonding. The proposed heterogeneous Si-SiN architecture leverages PN carrier-depletion phase shifting with sub-nanosecond response capability, currently demonstrating a 2 μs CMOS-driven beam switching time and ultra-low-power (1.5 μW/π), while delivering an angular resolution of 0.038° × 0.017° (FWHM) and a total main-lobe CW emission power of 1.5 W at a 20 W high-power injection. This approach effectively circumvents silicon's nonlinear limitations while maintaining high-density integration. System-level validations include indoor coherent detection and a four-channel phase-locked synthetic aperture scheme that successfully compresses the beam divergence to 300 μrad. This architecture provides a scalable roadmap for the development of high-performance, long-range solid-state LiDAR systems.

Terahertz imaging, operating within the 0.1–10 THz frequency range, leverages unique properties such as non-ionizing radiation, sensitivity to polar molecules, and material-specific spectral fingerprints. This review comprehensively surveys major terahertz imaging modalities, highlighting significant progress and applications. Key methodologies, including continuous-wave holography, lensless ptychography, and computed tomography, provide quantitative phase contrast and three-dimensional structural information. Notably, terahertz pulse time-domain holography leverages the broadband nature of pulsed sources to achieve depth-resolved imaging through time-gated analysis. The development of focal-plane and single-pixel imaging addresses challenges related to detector availability, enabling high-speed and cost-effective systems. A major breakthrough is observed in near-field imaging, which surpasses the diffraction limit to achieve nanoscale resolution for probing materials, biomolecules, and plasmonic phenomena. While challenges in signal-to-noise ratio, hardware integration, and imaging speed persist, ongoing innovations in laser sources, algorithms, and system design are driving adoption in security, biomedicine, and industrial inspection.

Conventional interferometric angle of arrival (AOA) estimation faces a fundamental limitation: high-precision angle measurement relies on long baselines, which easily introduce phase ambiguity. This issue is particularly pronounced in ultra-wideband (UWB) systems, where traditional ambiguity resolution methods lack robustness. To overcome this challenge, this paper introduces a microwave photonic (MWP) AOA estimation algorithm enhanced by a multi-scale attention residual deep convolutional dealiasing network (MSAR-DCDN). The proposed method employs the MSAR-DCDN to directly learn the nonlinear relationship between the intermediate frequency (IF) phase and the signal's angle of arrival, thereby bypassing conventional ambiguity resolution and relaxing the traditional trade-off between baseline length and operational bandwidth. Simulations demonstrate that the algorithm maintains strong robustness across a wide signal-to-noise ratio (SNR) range from −10 dB to 25 dB, and achieves an angle estimation accuracy exceeding 93% even at a high baseline-to-wavelength ratio of 2. Outdoor experiments with an 821 mm ultra-long baseline (the baseline-to-wavelength ratio reaches 21.9) further validate the approach, yielding a root mean square error (RMSE) below 0.42°. These results demonstrate a significant performance improvement over both standard interferometric techniques and their ambiguity-resolved variants. By integrating the UWB capability of MWP with the advanced MSAR-DCDN-based deep learning mechanism, this work presents a novel and effective framework for high-precision AOA estimation in intelligent photonics sensing, which mitigates the baseline length constraint of traditional methods and realizes flexible baseline configuration.

Integrated photodetectors capable of decoding multi-dimensional optical information are essential for modern information technologies and are widely applicable in areas such as autonomous driving, optical communications, and remote sensing. Recent progress in this field has been driven by the synergy among advances in low-dimensional materials, micro/nanofabrication technologies, and computational algorithms, which have enabled notable developments in integrable multidimensional optical-field detectors. In this review, we first introduce some basic principles of multi-dimensional light detection and outline the critical strategies for frontend optical encoding and backend computational decoding. Subsequently, we discuss detection schemes based on the intrinsic optical properties of low-dimensional materials. We then move to metasurface architectures that use subwavelength structural engineering to enable multi-dimensional light field detection. Furthermore, we summarize recent research on silicon-photonic integrated multidimensional photodetection that combines sensing and computing units. To conclude, we summarize key challenges, such as wafer-scale synthesis and interface engineering, and envision a future in which photodetectors evolve from simple signal converters into programmable, intelligent systems capable of comprehensive light-field perception.

Halide perovskites, recognized for efficient upconversion photoluminescence and high quantum yields, present a promising platform for laser refrigeration. Their high refractive index further enables the design of nanostructures that support strong Mie-type resonances, leading to subwavelength light confinement and enhanced laser cooling performance. In this work, we theoretically propose and numerically demonstrate a metasurface composed of nanostructured halide perovskite with tailored asymmetry, supporting dual-band quasi-bound states in the continuum (q-BICs) that simultaneously enhance optical excitation and upconversion photoluminescence. The perovskite metasurface exhibits a significant enhancement in optical absorption compared with the unpatterned perovskite film, along with a pronounced Purcell effect at the emission wavelength. Thermodynamic modelling further indicates net cooling down to –201 °C from room temperature under continuous laser illumination, exceeding the liquid-nitrogen cooling threshold. These findings establish design principles for mechanically refrigerant-free thermal management and open a pathway toward integrated cryogenic photonic platforms.

The sixth generation (6G) of mobile communications aims to establish high-speed, large-capacity space-air-ground-sea integrated networks (SAGSINs) to support the rapidly growing data traffic driven by big data and large-scale artificial intelligence. Visible light communication (VLC), operating in the 380–780 nm spectrum, has emerged as a promising optical wireless technology owing to its abundant spectral resources, high achievable data rates, and immunity to electromagnetic interference. These advantages make VLC a strong candidate for three-dimensional integrated communication networks. This review summarizes recent advances in visible light communication, focusing on key enabling technologies including transmitter and receiver devices, advanced signal processing algorithms, multi-aperture reception, and beamforming techniques. Representative demonstrations of large-capacity VLC systems based on multi-dimensional multiplexing are reviewed. Finally, the challenges and future research directions of VLC are discussed.