Search Results (128)

Optical tweezers (OTs) serve as a core contactless manipulation tool at the micro- and nano-scale, with wide applications in physics, biology, colloid science and other fields. However, conventional single-beam gradient force OTs are limited by diffraction, optical damage, low throughput, and system complexity. To meet the demand for large-scale particle manipulation in complex environments, speckle optical tweezers (SOTs) based on random optical fields have emerged as a promising alternative to conventional OTs that transform random speckle patterns into a controllable manipulation resource. Since their formal establishment, SOTs have developed a solid theoretical foundation and diverse implementation platforms with key breakthroughs in micro- and nanoparticle manipulation. This paper systematically reviews the origin and development of SOTs, elaborates their core principles, summarizes the statistical properties of speckle fields, and introduces typical configurations based on random media, multimode fibers, and spatial light modulators. It also highlights the unique value of SOTs in micro- and nanoparticle manipulation, active particle dynamics, and cold atom physics, with advantages of high throughput, low cost, and environmental adaptability. Finally, future development trends are discussed, including intelligent regulation of optical fields, interdisciplinary applications, system miniaturization and multi-technology integration. This review provides a comprehensive reference for the theoretical development, system optimization, and practical application of SOTs in fields such as statistical physics, biomedicine, microfluidics, and quantum science. Full article

Laser fiber-based collimation straightness measurement can eliminate the intrinsic drift of the laser source while offering a simple configuration and simultaneous measurement of straightness in two orthogonal directions. As a high-precision optoelectronic sensing method, it has been widely used for the measurement of straightness, parallelism, perpendicularity, and multi-degree-of-freedom geometric errors. However, two common issues remain in practical applications. One is the nonlinear response of the four-quadrant detector, the core position-sensitive sensor, which is caused by detector nonuniformity and the quasi-Gaussian distribution of the spot. The other is the degradation of measurement performance by atmospheric inhomogeneity and air turbulence along the optical path, particularly in long-distance measurements. To address these issues, a two-dimensional planar calibration method is first proposed to replace conventional one-dimensional linear calibration. A polynomial surface-fitting model is introduced to correct the nonlinear response and inter-axis coupling errors of the four-quadrant photoelectric sensor. Simulation and experimental results show that the proposed method significantly reduces the standard deviation of calibration residuals and improves measurement accuracy. In addition, based on our previously developed common-path beam-drift digital compensation method, comparative experiments were carried out on double-pass common-path and single-pass optical configurations employing corner-cube retroreflectors, and theoretical simulations were performed to analyze the influence of air-turbulence disturbances on measurement stability. Both theoretical and experimental results show that the double-pass common-path configuration exhibits more pronounced temporal drift. Therefore, a real-time digital compensation method for beam drift in long-distance single-pass common-path measurements is proposed. Experimental results demonstrate that the proposed method effectively suppresses drift induced by environmental air turbulence and thereby improving the accuracy and stability of long-travel geometric-error and related straightness measurement for machine-tool linear axes. 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

The growing demand for high-fidelity, multi-parameter, distributed sensing in critical domains such as structural health monitoring, oil and gas exploration, and secure perimeter surveillance is pushing traditional optical fiber sensors (OFS) to their performance limits. Although conventional multiplexing techniques such as time-division and wavelength-division multiplexing (TDM, WDM) have been commercially successful, they are rapidly approaching fundamental bottlenecks in sensor density, spatial resolution, and data capacity. This review argues that the synergistic convergence of space-division multiplexing (SDM) and artificial intelligence (AI) represents a paradigm shift, enabling a new generation of intelligent, high-dimensional sensing networks. We comprehensively survey the state of the art in SDM-based OFS, detailing the operating principles and applications of multi-core fibers (MCFs) for ultra-dense sensor arrays and 3D shape sensing, as well as few-mode fibers (FMFs) for mode-division multiplexing and enhanced multi-parameter discrimination. However, the unprecedented spatial parallelism provided by SDM introduces significant challenges, including inter-channel crosstalk, complex signal demultiplexing, and massive data volumes. This paper systematically explores how AI, particularly machine learning (ML) and deep learning (DL), is being leveraged not merely as a tool but as an indispensable core technology to mitigate these impairments. We critically analyze AI’s role in digital crosstalk suppression, intelligent mode demultiplexing, signal denoising, and solving complex inverse problems for parameter estimation. Furthermore, we highlight how this AI–SDM synergy enables capabilities beyond the reach of either technology alone, such as super-resolution sensing and predictive analytics. The discussion is extended to include the critical supporting pillars of this ecosystem, such as advanced interrogation techniques and the associated data management challenges. Finally, we provide a forward-looking perspective on the trajectory of the field, outlining a path toward cognitive sensing networks that are self-calibrating, adaptive, and capable of autonomous decision-making. This review is intended to serve as a foundational reference for researchers and engineers at the intersection of photonics and intelligent systems, illuminating the pathway toward tomorrow’s intelligent sensing infrastructure. Full article

Beyond supporting ultra-high-capacity data transmission, metropolitan and access networks are expected to enable real-time infrastructure monitoring, driving the emergence of integrated sensing and communication (ISAC). Distributed acoustic sensing (DAS) has proven to be well-suited to urban sensing application requirements, yet its seamless integration into ISAC remains challenging—conventional high-peak-power sensing pulses in DAS induce nonlinear crosstalk in communication channels. DAS inherently suffers from interference fading due to single-frequency laser sources, which limits sensitivity. Here, we propose an ISAC architecture based on an electro-optic (EO) comb and a 7-core fiber, achieving nonlinearity-suppressed self-homodyne transmission and fading-suppressed DAS. Unmodulated comb lines and sensing pulses are polarization-multiplexed into orthogonal polarization states within the central core to minimize nonlinear crosstalk while delivering local oscillators (LOs) for wavelength division multiplexing (WDM) coherent transmission within six outer cores—achieving 10.56 Tbit/s capacity. In addition to supporting WDM transmission, the EO comb’s wavelength diversity is also exploited to enhance DAS performance. Specifically, a dual-pulse probe loaded onto four comb lines yields a 6 dB signal-to-noise ratio gain and a 64% reduction in fading occurrences, achieving a sensitivity of 1.72 $p\epsilon /\sqrt{\mathrm{Hz}}$ with 8 m spatial resolution. Moreover, our system supports simultaneous multi-wavelength backscatter detection in sensing and simplified digital signal processing in self-homodyne communication, reducing receiver complexity and cost. Our work presents a scalable, energy-efficient ISAC framework that unifies high-capacity communication with high-sensitivity sensing, providing a blueprint for future intelligent optical networks. Full article

The present study introduces a novel design for lensed, chemically etched optical fibers (LEOFs) designed for efficient coupling with multicore fibers (MCFs). Experimental characterization at a wavelength of 1550 nm yielded an average coupling loss of approximately 0.76 dB under direct physical contact and 0.40 dB when the fiber end was positioned at an optimal working distance. Moreover, it was experimentally demonstrated that LEOFs exhibit high tolerance to longitudinal displacement and minimal wavelength-dependent variation in coupling efficiency. Based on this approach, fiber-in–fiber-out (FIFO) multicore couplers were fabricated using bundles of LEOFs that had been aligned to MCF cores. Bidirectional measurements yielded average insertion losses of 3.23–3.30 dB in TX and 3.20–3.27 dB in RX transmission directions at 1550 nm, with core-resolved losses as low as 1.09 dB for well-aligned channels. The results confirm the viability of LEOF-based multicore free-space coupling, with further improvements expected from enhanced fabrication accuracy. Full article

Transverse mode instability (TMI) in high-power ytterbium-doped double-clad fiber lasers is widely interpreted as being a consequence of a thermo-optic nonlinear phenomenon driven by stimulated thermal Rayleigh scattering. This work presents a coupled optical–thermal model for a continuous-wave forward-pumped (${\lambda }_p=976\mathrm{nm}$) fiber amplifier emitting at ${\lambda }_s=1064\mathrm{nm}$ over an optimal length of 12 m. The formulation explicitly resolves the three radial regions of a double-clad fiber, avoiding single-clad approximations. Modal fields are computed using the weakly guiding approximation (WGA) in the core combined with the semi-WGA at the cladding interfaces, enabling accurate calculation of higher-order modes of penetration into the inner cladding and of the transverse eigenvalues $U_{01}$ and $U_{mn}$ relevant to TMI. Within this framework, the nonlinear stimulated thermal Rayleigh scattering coupling coefficient is evaluated, including gain saturation and the thermal eigenmodes of the multi-layer geometry. The results show that the inner cladding modifies both the optical and thermal mode structures, altering the optical–thermal overlap between ${\mathrm{LP}}_{01}$ and higher-order modes and changing the effective strength of STRS, directly influencing the predicted TMI threshold. The proposed formulation provides a quantitative and physically consistent tool for analyzing thermo–optic dynamics in Yb-double-clad fiber amplifiers and supports the design of next-generation high-power fiber lasers with improved modal stability. Full article

Optical networks constitute the backbone of contemporary communication infrastructures, supporting massive bandwidth, low-latency services, and high levels of scalability across core, metro, and access domains. As these systems evolve toward elastic, software-defined, and multi-domain architectures, their exposure to sophisticated security threats increases significantly. This paper provides a comprehensive survey of vulnerabilities and countermeasures in modern optical networks, spanning the physical, control, and cross-layer dimensions. We analyze major architectures—including WDM, TDM, PON, EON, and IP-over-WDM—and examine how their structural properties shape their security posture. A threat taxonomy is presented covering physical-layer attacks such as fiber tapping, optical jamming, crosstalk exploitation, and signal injection; control-plane risks including spoofing, malicious signaling, and SDN manipulation; and broader cross-layer attack vectors. We review state-of-the-art defense mechanisms, including physical-layer security (PLS), spectrum randomization, chaotic optical coding, device-level authentication, survivability techniques, intelligent monitoring, and quantum-secure solutions such as QKD. By integrating insights from recent experimental and operational studies, the survey highlights emerging challenges and identifies open problems related to secure orchestration, multi-tenant environments, and quantum-era resilience. The objective is to guide researchers, engineers, and network operators toward robust and future-proof security strategies for next-generation optical infrastructures. Full article

In response to the key issues of complex internal structure, significant attenuation of partial discharge (PD) ultrasound signal propagation, and low sensor sensitivity in large oil–immersed power transformers, this paper analyzes the multi–order resonant mode vibration characteristics of the shaft–type fiber optic ultrasound sensor core structure. The displacement distribution patterns of the core structure in both transverse and longitudinal resonant modes are clarified. A strategy using oblique fiber winding rings is proposed to eliminate the problems of strain cancellation and non–accumulation of displacement in transverse and longitudinal resonant modes, which are common in traditional fiber optic ultrasound sensors with parallel fiber windings. Furthermore, design principles are provided to enhance the coverage of the free end and the high–strain regions with semi–high symmetry, as well as the vector–integrated response suitable for multi–order modes. Experimental results show that, in typical PD model detection, the oblique winding sensor exhibits a more prominent response near the high–order resonances of the core, with a detection sensitivity approximately 2.5 times higher than that of the parallel winding structure, and an overall sensitivity at least 7.4 times greater than that of traditional Piezoelectric (PZT) sensors. This demonstrates that the fiber winding method is a key design parameter determining the acoustic–solid coupling efficiency and high sensitivity performance of shaft–type fiber optic interferometric PD sensors, providing a feasible path for high–reliability fiber optic sensing solutions for online monitoring of transformer partial discharges. Full article

This study presents a robust deep learning-based approach for temperature sensing using Fiber Specklegram Sensors (FSS), leveraging an extended experimental framework to evaluate model generalization. A convolutional neural network (CNN), specifically a customized MobileNet architecture (MNet-reg), was trained on multiple experimental datasets to assess the impact of increasing data availability on sensing accuracy. Generalization is evaluated as cross-dataset performance under unseen experimental realizations, rather than under controlled intra-dataset splits. The experimental setup utilized a multi-mode optical fiber (MMF) (core diameter 62.5 µm) subjected to controlled thermal cycles via a PID-regulated heating system. The curated dataset comprises 24,528 specklegram images captured over a temperature range of 25.00 °C to 200.00 °C with increments of ~0.20 °C. The experimental results demonstrate that models trained with an increasing number of datasets (from 1 to 13) significantly improve accuracy, reducing Mean Absolute Error (MAE) from 13.39 to 0.69 °C, and achieving a Root Mean Square Error (RMSE) of 0.90 °C with an R² score of 0.99. Our systematic analysis establishes that scaling experimental data diversity—through training on multiple independent realizations—is the foundational strategy to overcome domain shift and enable robust cross-dataset generalization. Full article

We propose a vector bending sensor based on a tapered few-mode multi-core fiber (FM-MCF). A seven-core six-mode fiber is tapered with an optimized taper ratio, enabling bending sensing through power monitoring. When the tapered FM-MCF bends, coupling occurs between the central core and side cores in the tapered region. By monitoring the power of all cores and employing a power differential method, the bending direction and curvature can be reconstructed. The results show that within a curvature range of 2.5 m⁻¹ to 10 m⁻¹, the sensitivity of the ratio of the side core’s power to the middle core’s power with respect to curvature is not less than 0.14/m⁻¹. A deep fully connected feedforward neural network (DNN) is used to demodulate all power information and predict the bending shape of the optical fiber. The algorithm predicts the bending radius and rotation angle with mean absolute errors less than 0.038 m and 3.087°, respectively. This method is expected to achieve low-cost, high-sensitivity bending measurement applications with vector direction perception, providing an effective solution for scenarios with small curvatures that are challenging to detect using conventional sensing methods. Full article

The explosive growth of optical interconnection service traffic urgently necessitates the evolution of optical transponders and fibers. The core-division-multiplexed (CDM) transmission technique using weakly coupled multi-core fibers (MCFs) and beyond-1T optical transport network (OTN) transponders has emerged as an attractive solution to meet the bandwidth demands of future networks. In this paper, we demonstrate an ultra-high-speed OTN system using C+L-band 1.2 Tb/s OTN transponders with a weakly coupled seven-core fiber. The OTN transponders support two configurable modulation rates of 135 Gbaud and 155 Gbaud, along with a probability constellation-shaping 64-ary quadrature amplitude modulation (PCS-64QAM) format. The MCF exhibits characteristics comparable to those of SMFs and negligible inter-core crosstalk, providing a superior physical channel for ultra-high-speed CDM transmission. Fiber length and low-noise EDFAs are also chosen to enhance the transmission distance under the limited optical signal-to-noise ratio (OSNR) budget when using 1.2 Tb/s OTN transponders. Benefiting from the high-performance OTN transponders and MCF, we achieve real-time 0.672 Pb/s and 0.571 Pb/s 4 × 89 km CDM transmissions using 135 Gbaud and 155 Gbaud modulation rates, respectively. The performance of the two modulation configurations is also compared and discussed. This work demonstrates the feasibility of implementing 1.2 Tb/s OTN transponders with weakly coupled MCFs to achieve ultra-high-speed metro–regional transmission, presenting a promising solution for next-generation inter-city data center interconnections. Full article

The global expansion of 5G and the approaching 6G era are pushing conventional single-mode fibers toward their fundamental capacity limits, necessitating a paradigm shift in optical network infrastructure. This study introduces a novel, AI-optimized tri-concentric-core fiber with an optimized grading profile (TCC-OGP) to overcome this capacity crunch through spatial-division multiplexing (SDM). The fiber design was realized through an integrated artificial intelligence framework, combining a neural network surrogate model with particle swarm optimization to efficiently navigate a complex multi-objective design space. The resultant TCC-OGP fiber supports six spatial-division-multiplexed LP modes, achieving a breakthrough in the traditional capacity–nonlinearity trade-off. A comprehensive numerical analysis demonstrates that the proposed structure achieves 92% of the theoretical Shannon capacity while simultaneously suppressing nonlinear impairments by 65% compared to the standard single-core fiber. Furthermore, the fiber exhibits low differential mode delay, a flattened dispersion of approximately 16 ps/(nm·km) at 1550 nm, strong bend tolerance (<0.01 dB/m at a 30 mm radius), and excellent inter-modal crosstalk below −25 dB over 20 km. These performance metrics confirm the TCC-OGP fiber’s suitability for terabit-scale transmission in metro networks, dense 5G back-haul, and future 6G infrastructures, establishing a scalable and intelligent platform for next-generation optical networks. Full article

As optical networks continue to evolve toward higher speed and larger capacity, conventional security mechanisms relying on optoelectronic conversion are facing increasing limitations. The optical photonic firewall, as an emerging optical-layer security device, enables direct inspection in the optical domain, making its core technology—All-Optical Pattern Matching (AOPM)—a focal point of current research. This review provides a comprehensive survey of AOPM systems. It first introduces the main components of AOPM, namely symbol matching and system architectures, and analyzes their representative implementations. For low-order modulation formats such as OOK and BPSK, the review highlights matching schemes enabled by semiconductor optical amplifier (SOA) and highly nonlinear fiber (HNLF) logic gates, as well as their potential for reconfigurable extension. Building upon this foundation, the paper focuses on systems for high-order modulation formats including QPSK, 8PSK, and 16QAM, covering dimensionality-reduction-based approaches (e.g., PSA-based phase compression, squarer-based phase multiplication, constellation-mapping-based format conversion), direct symbol matching methods (e.g., phase interference, generalized XNOR, real-time Fourier transform correlation), and reconfigurable designs for multi-format adaptability. Furthermore, the review discusses optimization challenges under non-ideal conditions, such as noise accumulation, phase misalignment, and phase-locking-free operation. Finally, it outlines future directions in robust high-order modulation handling, photonic integration, and AI-driven intelligent matching, offering guidance for the development of optical-layer security technologies. Full article

Achieving controllable wavelength tuning in optofluidic whispering gallery mode microcavity lasers is crucial for high-throughput, multi-sample, multiplexed biochemical sensing and multifunctional integrated photonic devices. This paper develops a bidirectionally wavelength-tunable optofluidic fiber whispering gallery mode microcavity laser driven by Rhodamine 6G co-doped with different acceptor dyes. Experimentally, a thin-walled silica ring inside a hollow-core anti-resonant fiber served as the optical microcavity, with a fixed 2.5 mM Rhodamine 6G co-doped with other dyes as the gain medium. The results revealed that when co-doped with Rhodamine B or Cy3, the single-longitudinal-mode laser emission wavelength exhibited a red shift with increasing co-dopant concentration. Conversely, when co-doped with Cy5, the laser output wavelength showed a distinct blue shift. This unique bidirectional tuning characteristic originates from the different fluorescence resonance energy transfer efficiencies between the co-dopants and Rhodamine 6G, and their competitive modulation of the system’s effective gain spectrum. The study offers a novel and flexible strategy for achieving wide-range, controllable wavelength tuning on a single laser platform, with significant potential for applications in biochemical sensing and multifunctional integrated photonic devices. Full article