Light, science & applications最新文献

Ultra-low loss silicon nitride realized using deuterated precursors and low thermal budgets well within backend-of-line CMOS processing may accelerate widespread proliferation of their use.

Highly integrated optoelectronic and photonic systems underpin the development of next-generation advanced optical and quantum communication technologies, which require compact, multiwavelength laser sources at the telecom band. Here, we report on-substrate vertical emitting lasing from ordered InGaAs/InP multi-quantum well core-shell nanowire array epitaxially grown on InP substrate by selective area epitaxy. To reduce optical loss and tailor the cavity mode, a new nanowire facet engineering approach has been developed to achieve controlled quantum well nanowire dimensions with uniform morphology and high crystal quality. Owing to the strong quantum confinement effect of InGaAs quantum wells and the successful formation of a vertical Fabry-Pérot cavity between the top nanowire facet and bottom nanowire/SiO₂ mask interface, stimulated emissions of the EH_11a/b mode from single vertical nanowires from an on-substrate nanowire array have been demonstrated with a lasing threshold of ~28.2 μJ cm^-2 per pulse and a high characteristic temperature of ~128 K. By fine-tuning the In composition of the quantum wells, room temperature, single-mode lasing is achieved in the vertical direction across a broad near-infrared spectral range, spanning from 940 nm to the telecommunication O and C bands. Our research indicates that through a carefully designed facet engineering strategy, highly ordered, uniform nanowire arrays with precise dimension control can be achieved to simultaneously deliver thousands of nanolasers with multiple wavelengths on the same substrate, paving a promising and scalable pathway towards future advanced optoelectronic and photonic systems.

The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave systems. In photonics, because electromagnetic interactions between optical elements generally decay rapidly with spatial distance, most wave phenomena are modeled with neighboring interactions, which account for only a small part of conceptually possible networks. Here, we explore the impact of substantial long-range interactions in topological photonics. We demonstrate that a crystalline structure, characterized by long-range interactions in the absence of neighboring ones, can be interpreted as an overlapped lattice. This overlap model facilitates the realization of higher values of topological invariants while maintaining bandgap width in photonic topological insulators. This breaking of topology-bandgap tradeoff enables topologically protected multichannel signal processing with broad bandwidths. Under practically accessible system parameters, the result paves the way to the extension of topological physics to network science.

Editorial: Professor Juejun Hu was admitted by Tsinghua University as top scorer in the science college entrance examination of Fujian Province. After graduating, he went to MIT to pursue further studies, where he continued to excel and became a faculty member. Each step of his journey has been marked by extraordinary achievements, setting a standard that few can match. Today, Prof. Hu is recognized as a leading expert in integrated photonics and optical materials. His pioneering research has not only advanced the frontiers of academia but also made significant impacts on industrial applications. In this interview, we invite you to delve into Prof. Hu's research world, exploring his unique insights into technological innovation and how he uses the power of science to shape the future.

Recent advancements in wavefront shaping techniques have facilitated the study of complex structured light's propagation with orbital angular momentum (OAM) within various media. The introduction of spiral phase modulation to the Laguerre-Gaussian (LG) beam during its paraxial propagation is facilitated by the negative gradient of the medium's refractive index change over time, leading to a notable increase in the rate of phase twist, effectively observed as phase retardation of the OAM. This approach attains remarkable sensitivity to even the slightest variations in the medium's refractive index (∼10^-6). The phase memory of OAM is revealed as the ability of twisted light to preserve the initial helical phase even propagating through the turbid tissue-like multiple scattering medium. The results confirm fascinating opportunities for exploiting OAM light in biomedical applications, e.g. such as non-invasive trans-cutaneous glucose diagnosis and optical communication through biological tissues and other optically dense media.

Strict requirement of a coherent spectrum in coherent diffractive imaging (CDI) architectures poses a significant obstacle to achieving efficient photon utilization across the full spectrum. To date, nearly all broadband computational imaging experiments have relied on accurate spectroscopic measurements, as broad spectra are incompatible with conventional CDI systems. This paper presents an advanced approach to broaden the scope of CDI to ultra-broadband illumination with unknown probe spectrum, effectively addresses the key challenges encountered by existing state-of-the-art broadband diffractive imaging frameworks. This advancement eliminates the necessity for prior knowledge of probe spectrum and relaxes constraints on non-dispersive samples, resulting in a significant extension in spectral bandwidth, achieving a nearly fourfold improvement in bandlimit compared to the existing benchmark. Our method not only monochromatizes a broadband diffraction pattern from unknown illumination spectrum, but also determines the compressive sampled profile of spectrum of the diffracted radiation. This superiority is experimentally validated using both CDI and ptychography techniques on an ultra-broadband supercontinuum with relative bandwidth exceeding 40%, revealing a significantly enhanced coherence and improved reconstruction with high fidelity under ultra-broadband illumination.

Materials for radiation detection are critically important and urgently demanded in diverse fields, starting from fundamental scientific research to medical diagnostics, homeland security, and environmental monitoring. Low-dimensional halides (LDHs) exhibiting efficient self-trapped exciton (STE) emission with high photoluminescence quantum yield (PLQY) have recently shown a great potential as scintillators. However, an overlooked issue of exciton-exciton interaction in LDHs under ionizing radiation hinders the broadening of its radiation detection applications. Here, we demonstrate an exceptional enhancement of exciton-harvesting efficiency in zero-dimensional (0D) Cs₃Cu₂I₅:Tl halide single crystals by forming strongly localized Tl-bound excitons. Because of the suppression of non-radiative exciton-exciton interaction, an excellent α/β pulse-shape-discrimination (PSD) figure-of-merit (FoM) factor of 2.64, a superior rejection ratio of 10^-9, and a high scintillation yield of 26 000 photons MeV^-1 under 5.49 MeV α-ray are achieved in Cs₃Cu₂I₅:Tl single crystals, outperforming the commercial ZnS:Ag/PVT composites for charged particle detection applications. Furthermore, a radiation detector prototype based on Cs₃Cu₂I₅:Tl single crystal demonstrates the capability of identifying radioactive ²²⁰Rn gas for environmental radiation monitoring applications. We believe that the exciton-harvesting strategy proposed here can greatly boost the applications of LDHs materials.

The surge in interest regarding the next generation of optical fiber transmission has stimulated the development of digital signal processing (DSP) schemes that are highly cost-effective with both high performance and low complexity. As benchmarks for nonlinear compensation methods, however, traditional DSP designed with block-by-block modules for linear compensations, could exhibit residual linear effects after compensation, limiting the nonlinear compensation performance. Here we propose a high-efficient design thought for DSP based on the learnable perspectivity, called learnable DSP (LDSP). LDSP reuses the traditional DSP modules, regarding the whole DSP as a deep learning framework and optimizing the DSP parameters adaptively based on backpropagation algorithm from a global scale. This method not only establishes new standards in linear DSP performance but also serves as a critical benchmark for nonlinear DSP designs. In comparison to traditional DSP with hyperparameter optimization, a notable enhancement of approximately 1.21 dB in the Q factor for 400 Gb/s signal after 1600 km fiber transmission is experimentally demonstrated by combining LDSP and perturbation-based nonlinear compensation algorithm. Benefiting from the learnable model, LDSP can learn the best configuration adaptively with low complexity, reducing dependence on initial parameters. The proposed approach implements a symbol-rate DSP with a small bit error rate (BER) cost in exchange for a 48% complexity reduction compared to the conventional 2 samples/symbol processing. We believe that LDSP represents a new and highly efficient paradigm for DSP design, which is poised to attract considerable attention across various domains of optical communications.