Search Results (3,365)

The millisecond-level volatile fluctuations in workloads in large-scale intelligent computing clusters pose significant challenges to traditional electricity markets. Constrained by optical–electrical–optical conversion bottlenecks, these markets struggle to achieve real-time response and risk substantial social welfare loss. Leveraging existing fiber-optic infrastructure to build All-Optical Networks (AONs) presents a cost-effective evolutionary path. This paper develops a distributed energy trading strategy based on all-optical multicast. By utilizing the physical multicast properties of the underlying light-tree architecture instead of traditional protocols, the proposed strategy bypasses end-to-end latency constraints. This enables rapid transaction synchronization and dynamic tracking of social welfare optima within millisecond-level time-slots. Simulation results demonstrate that the proposed scheme elevates the transaction saturation threshold by two orders of magnitude compared with traditional strategies, effectively breaking the physical locking effect of latency on system throughput. Across various topologies, the social welfare gains exceed those of conventional schemes by more than 20 times. This study validates the engineering value of all-optical architectures for high-frequency trading and provides critical technical support for ultra-dynamic power trading algorithms. Full article

To meet the future demands of high-rate transmission and full-coverage networks, radio frequency–underwater wireless optical communication (RF-UWOC) relaying systems are considered a promising heterogeneous communication architecture. The rate-splitting (RS) scheme, through its power allocation (PA) mechanism, provides a generalized framework for the performance evaluation of such systems. Based on this, this paper analyzes the performance of an RS-based RF-UWOC system under hardware impairments (HIs) and interference. Analytical expressions of the outage probability (OP) and ergodic capacity (EC) for the considered system are formulated within a generalized framework, which encompasses the conventional RF-UWOC system as a special case. The results indicate that the OP and EC are affected by HIs, interference transmit power, the PA coefficients, channel fading, pointing errors (PEs), and detection types of the UWOC link. Furthermore, the asymptotic results for the OP and the diversity gain (DG) are explicitly characterized. For a fixed interference transmit power, the DG is mainly dominated by the channel fading severity, PEs effect, and the detection scheme. When the interference transmit power is comparable to the desired signal power, the system operates in an interference-limited regime, and the DG decreases to zero. It is also revealed that HIs and PA coefficients affect the coding gain but not the DG. Moreover, the existence of an optimal PA scheme improves the reliability of the RS-based system. Full article

With the advent of 6G mobile communication, the demand for ultra-high bandwidth wireless communication has increased rapidly, drawing significant attention to visible light communication (VLC) as a promising emerging technology. GaN-based laser diodes (LDs) are regarded as high-speed light sources for VLC owing to their high modulation bandwidth and high optical power density. Apart from the active region design, the LD’s structure also plays a crucial role in determining their dynamic properties, which have yet to be thoroughly studied in III-nitride LDs. In this work, we systematically investigate InGaN/GaN laser diodes with three ridge waveguide configurations: a conventional single-ridge structure, a dual-ridge large-mesa structure, and a dual-ridge small-mesa structure. The threshold current, small-signal modulation bandwidth of devices with different structures are comparatively analyzed. Experimental results reveal that the double-ridge small mesa laser diode achieves a modulation bandwidth of −3 dB at 6.02 GHz. These results provide valuable insights into the structural optimization of GaN-based high-speed laser diodes and offer practical guidance for the development of high-performance, energy-efficient VLC transmitters. Full article

The design of volume holographic gratings (VHGs) is traditionally based on monochromatic plane waves. However, practical applications often involve light sources with broad wavelength bandwidths and certain emission areas, such as LEDs and MiniLEDs, which cause significant Bragg mismatch and degrade diffraction efficiency. To address this fundamental challenge, this paper proposes a novel, to the best of our knowledge, genetic algorithm (GA)-based optimization method for VHG design. A ray-tracing analysis model that fully incorporates the spectral and spatial characteristics of extended broadband sources is established. The GA optimizes the grating fabrication angles by minimizing a fitness function defined as the residual energy after diffraction, thereby achieving optimal performance under non-ideal illumination conditions. The effectiveness of the proposed method is demonstrated through a case study: suppressing the high-intensity central beam in an ultra-thin MiniLED backlight module (BLM). Simulation and experimental results show that the GA-optimized VHG significantly reduces the peak irradiance from 5.01 W/cm² to 4.14 W/cm² at an optical distance (OD) of 0.5 mm. This work provides a robust and source-adaptive design methodology for VHGs, with potential applications extending beyond backlighting to areas such as augmented reality, holographic displays, and optical communications. Full article

We report the design, epitaxial growth, and room-temperature operation of a high-gain AlInAsSb-based avalanche photodiode (APD) for short-wavelength infrared (SWIR) detection at 1.55 µm. The device employs SAGCM structure to confine the electric field within the multiplication region while suppressing dark current. High-quality AlInAsSb layers were grown on GaSb substrates by molecular beam epitaxy using a digital alloy approach, achieving excellent surface morphology (R_a < 0.2 nm) and uniform superlattice periodicity. Electrical characterization reveals a well-defined breakdown voltage near −17 V and a peak internal multiplication gain of 200 at 300 K under 0.2 mW illumination at 1550 nm—among the highest gains reported to date for antimonide-based APDs operating at room temperature. Variable-temperature dark current analysis indicates a transition from tunneling-dominated to thermally generated dark current as temperature increases from 100 K to 300 K. These results demonstrate the strong potential of AlInAsSb SAGCM APDs for eye-safe, high-sensitivity applications in LIDAR, free-space optical communication, and low-light SWIR imaging. Full article

High-speed photodetectors with extended dynamic ranges are critical for emerging optical systems like LiDAR. This paper presents a design methodology for a modified uni-traveling-carrier photodetector (MUTC-PD) that integrates a physics-based analytical model with numerical simulations. The existing analytical models for MUTC-PDs rely on approximations that may not hold under high injection levels and high frequencies, leading to discrepancies between theoretical predictions and practical observations. To address this limitation, we re-examine the governing equations and derive a corrected frequency response analytical model based on drift–diffusion theory by decomposing the device into distinct transport regions, enabling a physically meaningful optimization of the epitaxial layer structure to maximize theoretical intrinsic bandwidth. The calculated results closely match the simulated bandwidth (maximum error less than 6%), demonstrating consistent peak positions and trends. Subsequently, numerical simulations reveal the dynamic evolution of the device’s bandwidth under varying incident optical intensities. The results demonstrate that the intrinsic bandwidth initially increases to a peak of 325.82 GHz at $7\times {10}^4\mathrm{W}/{\mathrm{cm}}^2$ under −3.5 V, attributed to the drift-enhancement effect driven by the self-induced quasielectric field. Beyond this optimal regime, the space charge effect causes internal field collapse and significant bandwidth degradation. This study establishes bandwidth maintenance capability under high injection as a key metric for linearity, offering a transparent theoretical and practical framework for designing a high-speed MUTC-PD. Full article

As optical access networks continue to evolve toward higher capacity, longer reach, and increased user density, accurately predicting transmission performance has become increasingly complex. Conventional physics-based models often struggle to capture the nonlinear and stochastic behavior of modern passive optical networks (PONs), particularly under diverse operating conditions. In this study, a hybrid deep learning (DL) framework is proposed for the prediction of key performance indicators, including Q-factor, receiver sensitivity, and bit error rate (BER), in asymmetric 160/80 Gbps TWDM-PON systems, which is the target capacity by ITU-T G.989.1 specifications. The proposed approach integrates Gradient Boosting Regression and Multi-Layer Perceptron models within an ensemble learning structure to enhance robustness and predictive accuracy. A synthetic dataset comprising 1000 samples was generated to emulate realistic transmission scenarios with variations in distance, power level, and noise conditions for both upstream and downstream channels. Experimental results demonstrate strong agreement between the proposed DL-based predictions and conventional optical simulation outcomes, while the proposed predictions achieve superior adaptability and reduced computational complexity. High coefficients of determination (R² > 0.94) and low error metrics confirm the effectiveness of the framework, highlighting its potential as a fast and reliable alternative to traditional performance evaluation methods in next-generation optical access networks. Full article

We introduce a class of specular and antispecular radially polarized partially coherent twisted beams by using a wavefront-folding interferometer and then investigate the propagation of such beams blocked by an opaque obstacle. One sees that these optical fields exhibit sharp internal spectral density with a central peak in the specular case and a central dip in the antispecular case. It is also seen that both the spectral density and the polarization feature present a good twist effect and a tendency to self-heal upon propagation. However, unlike the spectral density that can recover its profile perfectly, the self-healing ability of both the degree of polarization and the generalized Stokes parameters is only partial and not complete. While a smaller value of the twist factor enhances the self-healing performance of the beam field, it slows the beam’s rotation and degrades the degree of polarization. Moreover, the polarization distribution in the central area is mainly determined by the phase difference of the interferometer. The results of our work have important applications in the fields of free-space beam communication and particle trapping. Full article

Aerosol optical depth (AOD) is a key indicator for quantifying aerosol radiative effects and evaluating air quality. However, atmospheric chemical transport models often exhibit systematic AOD biases, and model capability for column-integrated optical properties is not always consistent with that for near-surface particulate matter concentrations. Here, we evaluate AOD simulated by the Community Multiscale Air Quality (CMAQ) model over five major urban clusters in China, including the Beijing-Tianjin-Hebei (BTH) region, Fenwei Plain (FWP), Sichuan Basin (SCB), Yangtze River Delta (YRD), and Pearl River Delta (PRD), using satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground-based retrievals from the Aerosol Robotic Network (AERONET), and vertical extinction profiles from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). CMAQ reproduces the major spatial patterns and exhibits relatively small biases in near-surface PM_2.5. However, it persistently underestimates AOD relative to MODIS, with the largest negative bias occurring in April (i.e., a typical spring month). This contrast indicates a pronounced inconsistency between column-integrated aerosol amount and surface mass density. Relative to AERONET, CMAQ shows a negative bias (NMB = −38%), whereas MODIS shows a positive bias (NMB = 56%), suggesting that both model and retrieval uncertainties contribute to the CMAQ–MODIS disagreements. CALIPSO-constrained vertical analysis further suggests that insufficient extinction above the planetary boundary layer (PBL) is an important contributor to the negative AOD bias, although the relative roles of boundary-layer and upper-layer contributions vary across regions, underscoring the importance of accurately representing aerosol vertical transport and optical processes. These results indicate that evaluations based solely on surface observations may fail to fully capture the overall structure of AOD errors, particularly given the clear differences between near-surface mass concentrations and column optical properties, which vary across regions. This also highlights the importance of improving the representation of aerosol vertical transport and optical processes in chemical transport models. Full article

Coherent optical communication serves as the backbone of long-haul, high-capacity optical networks, where polarization-insensitive 90° optical hybrids (OHs) are crucial for system simplification and robustness. This work presents a polarization-insensitive 90° OH based on asymmetric double-strip silicon nitride waveguides, designed for dual-polarization quadrature phase-shift keying (DP-QPSK) systems. The device consists of a cascaded polarization-insensitive structure incorporating one 1 × 2 and three 2 × 2 multimode interference (MMI) couplers, interconnected by four 90° bent waveguides. Optimized via 3D finite-difference time-domain (FDTD) simulations, the 1 × 2 MMI coupler exhibits insertion losses below 0.06 dB (TE) and 0.09 dB (TM), while each 2 × 2 MMI coupler shows insertion losses under 0.2/0.4 dB, amplitude imbalance below 0.05/0.18 dB, and phase error within ±0.5°/±1.5° for the TE/TM modes, respectively. Based on these components, the full device achieves polarization-insensitive operation across a 100 nm bandwidth (1500–1600 nm), with a phase error within ±1°, insertion loss below 0.3 dB (TE) and 0.5 dB (TM), and common-mode rejection ratio better than −40 dB (TE) and −30 dB (TM). Furthermore, the design demonstrates high fabrication tolerance, maintaining performance under manufacturing deviations of ±2 μm in MMI length and ±20 nm in waveguide spacing. This work provides a promising polarization-insensitive OH design and a viable route toward cost-effective mass production of next-generation high-speed coherent systems. Full article

This study presents an investigation of the factors (driven by coupled multi-factor corrosion mechanisms) which contribute to the degradation of the spirally wound armored steel wires used to protect core-structured, unarmored optical-fiber submarine cables. The influences of the physical properties of deep-sea sediments on the durability of unarmored cables, as well as the impact of ionizing radiation on optical fibers, are also assessed. The objective of this paper is to establish a scientific basis for cable longevity by integrating theoretical insights with empirical evidence. Although the steel utilized in armored cables is cost-effective and durable, it remains vulnerable to corrosion. Since the inaugural practical deployment of submarine communication cables between the UK and France in the 1850s, only a small number of studies worldwide have examined the corrosion and durability of cable armor. There is also limited literature examining the physical characteristics of the deep-sea surface sediments that directly affect the service life of the cables’ mechanically fragile polyethylene sheathing. An in-depth analysis of the cable damage and environmental conditions observed during maintenance operations provides valuable insights into the key environmental factors that influence armor corrosion and cable longevity. This research aims to guide future design and support strategies to improve the sustainability and durability of cable systems in marine environments. Full article

Visible light communication (VLC)-based Li-Fi systems suffer from limitations in transmission capacity expansion due to the restricted modulation bandwidth of LEDs. In this study, a latent representation-based NRZ-OOK Li-Fi transmission framework that exploits the statistical feature distribution of the latent space is proposed to improve transmission efficiency without expanding the physical bandwidth. An autoencoder is employed to transform input images into low-dimensional latent vectors, which are then quantized and modulated for transmission. At the receiver, hard decision and inverse quantization are performed, and the image is reconstructed through a trained decoder by leveraging the distribution characteristics of the latent representation. The effective transmission capacity gain $G_{\mathrm{c}\mathrm{a}\mathrm{p}}$ is defined to quantify the amount of representable information relative to the original data under the same physical link resources according to the latent dimension, achieving up to a 49-fold data representation efficiency. The experimental results over practical optical links (0.5–1.5 m) showed that, in short-range conditions, larger latent dimensions maintained higher reconstruction PSNR, whereas under channel degradation conditions, smaller latent dimensions exhibited higher robustness, demonstrating a performance inversion phenomenon. Furthermore, it was confirmed that the dominant factor governing reconstruction performance shifts from the representational capability of the data to error accumulation characteristics depending on the channel condition. These results suggest that the latent representation-based transmission framework is an effective Li-Fi strategy that can simultaneously consider transmission efficiency and channel robustness through information representation optimization in bandwidth-limited environments. Full article

Background/Objectives: Wolfram syndrome type 1 (WS1) is a rare, progressive, multisystem neurodegenerative disorder characterized by diabetes mellitus, optic atrophy, diabetes insipidus, and sensorineural hearing loss. As survival has improved, an increasing number of affected women are reaching reproductive age. However, evidence on pregnancy and peripartum management in WS1 remains scarce, and practical guidance is limited. This case report describes the multidisciplinary management of pregnancy and delivery in a woman with genetically confirmed WS1 and highlights key considerations for peripartum care. Case Presentation: A woman with genetically confirmed WS1 and long-standing multisystem involvement, including diabetes mellitus, diabetes insipidus, neurogenic bladder requiring frequent self-catheterization, progressive neurologic manifestations, and severe sensory impairment, achieved pregnancy through assisted reproduction with oocyte donation and was closely monitored by a multidisciplinary team. Due to persistent breech presentation, a planned external cephalic version was performed at 37 + 5 weeks’ gestation with immediate availability for cesarean delivery. After unsuccessful attempts, cesarean delivery was performed under combined spinal–epidural anesthesia. Peripartum management focused on strict glycemic control, careful monitoring of fluid balance and urine output, neuraxial anesthesia with proactive hemodynamic management, precautions related to the cochlear implant, and tailored communication strategies. Postpartum recovery was favorable, although anemia on postoperative day 1 required transfusion of one unit of packed red blood cells and intravenous iron therapy. Discussion and Conclusions: Pregnancy in WS1 represents a high-risk clinical scenario because of the coexistence of endocrine, urologic, and neurologic comorbidities, while published evidence on peripartum management remains limited. This case supports an individualized, multidisciplinary approach to obstetric and anesthetic planning and the use of a practical framework to optimize peripartum management and enhance maternal–fetal safety in this rare condition. Full article

We present the simulation-guided design and experimental demonstration of high-speed 940 nm vertical-cavity surface-emitting lasers (VCSELs). Utilizing established device optimization principles, a simulation study was conducted focusing on the number of oxide layers and the aperture size, which predicted a maximum modulation bandwidth of over 35 GHz. To validate the simulation, a device with a 4-μm double-oxide aperture was fabricated and characterized. Additionally, a Zn-diffusion process was incorporated during fabrication to reduce p-DBR resistance and suppress higher-order transverse modes. The fabricated device achieved an experimental modulation bandwidth of 34 GHz and demonstrated successful 100 Gbit/s PAM-4 data transmission. The close agreement between the simulated and measured performance highlights the successful practical integration of these techniques for developing high-speed optical interconnects. Full article

Non-convex stochastic optimization presents fundamental mathematical challenges across machine learning, wireless networks, data center resource allocation, and optical wireless communication systems, where complex loss landscapes with multiple local minima and saddle points impede classical variational inference methods. This paper introduces the Quantum-Inspired Variational Inference (QIVI) framework, which systematically integrates quantum mechanical principles (superposition, entanglement, and measurement operators) into classical variational inference through rigorous mathematical formulations grounded in Hilbert space theory and operator algebras. We develop a unified optimization framework that encodes classical parameters as quantum-inspired states within finite-dimensional complex Hilbert spaces, employing unitary evolution operators and adaptive basis selection governed by gradient covariance eigendecomposition. The core mathematical contribution establishes that QIVI achieves a convergence rate of $\mathit{O}({log}^{2}T/T^{1/2})$ for $\sigma$-strongly non-convex functions, provably improving upon the classical $\mathit{O}\left(T^{-1/4}\right)$ rate, yielding a theoretical speedup factor of $1.85$–$1.96\times$. Comprehensive experiments across synthetic benchmarks, Bayesian neural networks, and real-world applications in network optimization and financial portfolio management demonstrate 23–$47\%$ faster convergence, 15–$35\%$ superior objective values, and 28–$46\%$ improved uncertainty calibration. The principal contributions include: (i) a rigorous Hilbert space-based mathematical framework for quantum-inspired variational inference grounded in operator algebras, (ii) a novel hybrid quantum–classical algorithm (QIVI) with adaptive basis selection via gradient covariance eigendecomposition, (iii) formal convergence proofs establishing provable improvement over classical methods, (iv) comprehensive empirical validation across diverse problem domains relevant to machine learning and network optimization, and (v) demonstration of the framework’s applicability to optimization problems arising in wireless networks, data center resource allocation, and network system design. Statistical validation using the Friedman test (${\chi }^2=847.3$, $p<0.001$) and post hoc Wilcoxon signed-rank tests with Holm–Bonferroni correction confirm that QIVI’s improvements over all baseline methods are statistically significant at the $\alpha =0.05$ level across all benchmark categories. The framework discovers $18.1$ out of 20 true modes in multimodal distributions versus $9.1$ for classical methods, demonstrating the potential of quantum-inspired optimization approaches for challenging stochastic problems arising in machine learning, wireless communication, and network optimization. Full article