We propose a novel, to the best of our knowledge, approach for improving the performance of Rydberg atom sensors by utilizing the repetition frequency of pulsed lasers, which has been validated through experimental testing. Rydberg atoms excited by pulsed lasers are influenced significantly by the repetition frequency of the pulsed laser on the Rydberg state population. As the number of Rydberg atoms increases, the measurement sensitivity of the sensor to external fields also increases, directly enhancing the performance of the sensor. This paper investigates the response of the sensor to the same electric field when the repetition frequency of the pulsed laser is at the MHz level, with a focus on its gain effects on the broadcast communication frequency bands of 66 MHz and 88 MHz. This research substantiates the distinctive benefits of pulsed light for Rydberg atom excitation, thereby enhancing the efficacy of the detection of feeble signals and introducing a new approach for the development of more sensitive atomic sensors.

A high-efficiency and high-beam-quality (18 + 1) × 1 pump-and-signal combiner based on specialty fluorine-doped-silica-cladding fiber is designed and developed. The influences of taper geometry and misalignment error on pump and signal performances are theoretically investigated, and structural parameters enabling balanced performance and tolerance are determined. An improved in-line active splicing method is proposed to maximize fundamental signal mode coupling, achieving a signal efficiency of 96.4% and an M 2 deterioration of 7.8% in the backward direction. The fabricated combiner demonstrates a pump efficiency of 99.4% and supports the validation of a 3.1-kW bidirectionally pumped triple-cladding fiber laser.

Nanomechanical resonators operating at high frequencies are well-suited for demanding applications, particularly in the realm of ultrasensitive mass and force detection. For these applications, a continuous tunable frequency with a linear wide, linear range is highly desired. However, conventional electrically tunable methods have limitations of complex design, nonlinearity, and pull-in instability. The present work demonstrated a fiber-tip nano-optomechanical resonator that can be tuned using an all-optical method. This all-optical tuning method is realized through changing the laser power, which is fast and convenient. The nano-optomechanical resonator fabricated at the fiber tip is further used for mass sensing. Its fabrication process includes transferring multilayer graphene to the end of a hollow-core optical fiber segment that is fusion-spliced to a single-mode fiber, and then processing the suspended graphene membrane using a focused ion beam (FIB) to create a trampoline-type structure. The proposed optically tuned fiber-tip mass sensor has an all-optical-fiber integrated structure and thus is compact. Small masses are detected by monitoring changes in the nanomechanical resonator's resonance frequency. The mass detection of the nano-optomechanical resonator is demonstrated by depositing Au atoms on the surface of the trampoline-type multilayer graphene (MLG) film. This miniature, optically tunable, all-fiber mass sensor exhibited a resolution of 2.381 fg within its linear operating range at room temperature. The results show that the optically tunable trampoline-type MLG resonator has enormous potential in ultrasensitive detection for biosensing and gas sensing.

Fiber Bragg gratings (FBGs) with significantly enhanced reflectivity in ring-core fibers (RCFs) were successfully inscribed by using a high-repetition-rate femtosecond laser and the ring-by-ring (RbR) method. In comparison to FBGs with very low reflectivity produced in RCF through point-by-point or line-by-line methods, those inscribed via the RbR method exhibit an improved reflectivity of up to 80% . This enhancement is attributed to the alignment of the refractive index modulation trajectory with the mode field distribution of the RCF. To further increase the overlap area, a multi-layer RbR method was employed, achieving near-complete coverage of the fiber core and thereby enhancing the reflectivity to 98.8% . Although the signal-to-noise ratio of the FBGs reaches over 30 dB, due to the strong high-frequency components in the frequency domain of the uniform refractive index modulation, the side-mode suppression ratio (SMSR) is less than 10 dB. Therefore, two novel apodization techniques - one involving diameter variation and the other arc-length variation - which are compatible with the RbR method are proposed and demonstrated. By precisely controlling the diameters or arc-lengths of each ring induced by femtosecond laser, diverse apodization modulation profiles can be achieved to inscribe apodized FBGs with a SMSR of more than 25 dB. Four types of FBGs using different apodization functions were compared and analyzed, the experimental results show that the Gaussian function has the optimal apodization effect.

A novel method to enhance the coupling efficiency between single-mode fiber (SMF) and anti-resonant hollowcore fiber (ARHCF) by splicing tapered single-mode fiber (TSMF) with tapered no-core fiber (TNCF) is proposed for the first time. The TNCF focuses the output light field from the ARHCF, enabling better mode field matching with the TSMF, which has a smaller mode field diameter (MFD). A coupling model based on the beam propagation method (BPM) is established to analyze the system. The simulation results demonstrate that by approximately matching the MFD of the output light field from the ARHCF to that of the TSMF through the TNCF, the coupling efficiency between the SMF and the ARHCF can be significantly improved from 34.7% to 93.5% at a wavelength of 1550 nm while reducing the loss by 4.28 dB. Experimental measurements confirm a loss reduction of 4.13 dB, which aligns well with the simulation results. Notably, the Fresnel reflection at the ARHCF-TNCF interface still contributes 0.3 dB to the total loss. These findings indicate that the proposed structure effectively overcomes the core diameter mismatch limitation, enabling efficient coupling between large-core ARHCF and SMF. Additionally, the design offers several practical advantages, including standardization, scalability for mass production, compact size for easy integration, and robustness against cutting errors. Compared to conventional fusion splicing techniques, the insert coupling method exhibits substantial potential for high-power laser transmission and low-loss optical coupling. Given these benefits, this approach is well-suited to meet the evolving demands of ARHCF-based applications in future developments.

The thermal stability of high-power Cladding Power Strippers (CPS) is a critical bottleneck for fiber laser systems. The internal scattered light forms a unique, non-uniform interfacial heat source that is difficult to manage using conventional simplified thermal models. Taking the distributed optical scattering characteristics as the driving input, a novel self-adaptive hybrid relaxation algorithm is proposed to establish a multi-level coupled analysis framework. Furthermore, according to the thermal-flow coupling effect, the thermal-fluid behavior of a U-shaped water-cooled package structure is characterized comprehensively. To verify the accuracy of the analytical model, the temperature of the CPS under cladding-coupled input is measured experimentally. The study reveals the direct correlation between optical energy deposition and local temperature peaks. The results indicate that the optimized cooling system effectively controls the maximum package temperature to below 55°C, ensuring the device operates safely below the coating damage threshold under conditions ranging from low power (138.4 W) to high power (2171 W).

We present an innovative frequency comb methodology utilizing pulsed lasers for Rydberg atoms and implement it for electric field measurement. It achieves the Rydberg state population of multi-velocity group atoms through the two-photon resonant excitation of a 509 nm pulsed laser and an 852 nm continuous laser. The frequency comb approach markedly elevates the population of Rydberg atoms and augments the atomic density for sensing, thereby enhancing measurement sensitivity. Our investigations generated high-sensitivity measurements of electric fields across a broad spectrum from 20 kHz to 96 MHz, with a minimum measured electric field sensitivity of 2.9uV/cm/Hz(1/2). Additionally, we have exhibited a high degree of measurement sensitivity in the 66 MHz and 88 MHz broadcast communication frequencies. This research enhances the effective detection of microwave signals over a broad spectrum of frequency bands utilizing Rydberg atoms and introduces an innovative technical methodology for microwave metrology grounded in Rydberg atoms.

We introduce a compact metasurface structure that is capable of single-shot dual-wavelength polarization reconstruction. The metasurface is designed as a diffraction grating, where the eight diffraction orders function as eight different polarization analyzers for dual-wavelength polarization reconstruction. Thus, our approach requires only a single measurement for polarization reconstruction, in contrast to other methods that are based on time-division multiplexing. We propose a general method for optimizing the metasurface structure for two given wavelengths. Based on the proposed method, we optimized a metasurface for wavelengths of 532 nm and 671 nm. Simulation has shown that the metasurface structure can reconstruct polarized light independently and simultaneously at two wavelengths, aligning well with the theoretical calculations. Considering each diffraction order as a polarization analyzer, the system achieves an average polarization contrast of 97.9% and an average reconstruction error of 3.16% for the normalized Stokes vector.

The rapid growth of the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) has imposed stricter accuracy requirements on indoor positioning for unmanned ground vehicles (UGVs), where reliable velocity estimation is essential for continuous positioning. This paper presents a robust magnetic–inertial odometry for indoor UGVs using low-cost magnetometer array (RMIO-MA) that integrates a low-cost magnetometer array with inertial measurements to enhance positioning robustness and accuracy in complex indoor environments. First, a Tukey’s biweight-loss-based dynamic time warping (DTW) method is developed to align magnetic field waveforms while mitigating the effects of local magnetic anomalies, sensor noise, and velocity errors. Subsequently, an exponential residual weighted fusion strategy is designed by exploiting the redundancy of the magnetometer array to adaptively assign weights for the estimated velocity among sensors. Finally, for turning maneuvers, a magnetic gradient-based velocity estimation approach is proposed to constrain planar motion and suppress drift using spatial field variations. In the underground loop comprehensive experiment, RMIO-MA achieves an average positioning error of 5.64 m, a 75th-percentile positioning error of 4.83 m, and a closed-loop error of 0.9%. Furthermore, relative to conventional wheel–IMU odometry, RMIO-MA improves positioning accuracy by 2.65 times, thereby delivering accurate and robust indoor positioning performance.

Subject of study. The design concept of fiber metal ion detectors and wind-blast pressure in water flow is studied. Purpose of the work. The purpose is to sensitize a fiber sensor in relation to the concentration of metal ions in a fluid and pressure due to water flow. Method. Through theoretical analyses and computer and physical simulations, the sensitivity of a sensor consisting of a metal ion concentration meter, transitive D-shaped fiber module, and fluid flow pressure meter based on a fiber grating is investigated. Main results. As a result of metal ion concentration measurement experiments, it has been proved that the device reaches a response sensitivity of metal ion concentration of the order of 105 nm & centerdot; ml/mol. In addition, the sensitivity of the metal ion concentration response is ensured to be of the order of 105 nm & centerdot; ml/mol, and the device is experimentally investigated for sensing characteristics of axial strain and bending deformation. Practical significance. The design concept and calculation methods of a metal ion concentration and fluid flow pressure stress sensor have been developed; the sensor can be used for ecological monitoring of natural water environments. (c) 2026 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

Single-cell adhesion studies play a crucial role in cell biology. Cell adhesion measurement methods, such as atomic force microscopy (AFM) technology, can be used to measure the single-cell adhesion force. However, these methods have many limitations, such as complex operations or the need for labeling. In this study, we proposed a miniature fiber-tip shear force probe (FSFP) that can achieve accurate measurement of the single-cell adhesion force under physiological conditions. A shear force probe structure that facilitates lateral manipulation was designed based on the principles of structural mechanics and fabricated integrally at the end face of a single-mode fiber using femtosecond laser two-photon polymerization technology. The relationship between the FSFP spectral output and the applied force was established, and its microforce sensitivity was obtained to be 2.81 nm/μN, a minimal detectable force is 7.1 nN. The achieved overall measurement range of the device is 69 μN. The adhesion force of MCF-7 breast cancer cells was measured under physiological conditions by using the FSFP. Compared to polymer substrates, the average adhesion force of cells was greater on glass substrates with greater stiffness. The average cell adhesion force value decreased by more than two times after trypsin stimulation. In addition, experiments have shown that cells tend to spread into shuttle shapes on glass substrates with greater stiffness and have a denser actin filaments distribution. To the best of our knowledge, this is the first report on the accurate measurement of the single-cell adhesion force using a miniature all-fiber microforce sensor, which is flexible, fast, and label-free, opening new avenues for single-cell analysis.

In indoor environments where satellite signals are obstructed, inertial navigation technology demonstrates a high level of autonomy and interference resistance. Compared to other pedestrian inertial positioning systems, foot-mounted inertial navigation systems exhibit distinct gait characteristics and periods of stasis, offering favorable conditions for error correction in low-cost micro-electro-mechanical system inertial positioning systems, which suggests a broad range of applications. However, current gait detection thresholds are static, the determination methods are singular, interval division is ambiguous, and there are significant issues with missed and false detections. Moreover, inertial navigation algorithms lack positional information observation, and without external information assistance, the positioning results tend to diverge over time. Existing step length models that constrain position have fixed parameters, leading to poor adaptability. To address these challenges, this paper introduces a foot-mounted inertial navigation algorithm that is based on dynamic threshold gait detection and adaptive step length estimation. Initially, a dynamic threshold gait detection method is proposed, which integrates multi-condition detection based on the transformation rules of foot motion information. Subsequently, leveraging the high short-term precision of inertial navigation algorithms, the linear step length estimation model is refined to establish an adaptive step length estimation model with self-regulating parameters. Ultimately, the estimated single-step displacement of the foot is utilized to estimate positional information as an observation, thereby correcting the positional errors of the foot-mounted system. In multiple 1000 m open-loop tests, the algorithm presented in this paper achieved a maximum endpoint error of 12.54 m, a mean error of 11.68 m, and a root mean square error of 11.70 m.

In recent years, more researchers in the field of multi-modal tracking have focused on various algorithms for RGB-T tracking, leveraging the complementary nature of RGB and TIR imaging to achieve good application results. However, their performance tends to degrade in specific scenarios where the target is color-camouflaged and TIR modality is ineffective. Our experiments reveal that ultraviolet (UV) sensors can effectively image certain camouflage materials. Therefore, in extreme scenarios where the target is color-camouflaged and TIR modality is ineffective, UV modality can serve as a supplementary means to RGB and TIR modalities, enhancing tracking performance. In this paper, we propose the first multi-modal object tracking network for visible light, thermal infrared, and ultraviolet, namely VTUTrack, which achieves better tracking performance in complex scenarios. Furthermore, to meet the needs of real-time tracking applications, we introduce an adaptive candidate elimination mechanism based on modality reliability within the ViT (Vision Transformer) backbone network, reducing the computational burden of multi-modal feature extraction and improving tracking inference speed. Extensive experiments further demonstrate the effectiveness of our proposed RGB-T-UV multi-modal object tracking method.

The utilization of pedestrian positioning technology has become increasingly prevalent in emergency and rescue operations, in contexts such as fires, earthquakes, and mining accidents. However, the navigation infrastructures, including radio frequency (RF), audio, and fingerprint, may be either inaccessible or unable to be established expeditiously in these scenarios. In order to address the problem of pedestrian localization in scenarios with an absence of navigation infrastructures, this article presents a navigation infrastructure-free cooperative pedestrian navigation (CPN) approach based on the fusion of pedestrian dead reckoning (PDR) and ad hoc networks. PDR employs an inertial measurement unit (IMU) to facilitate individual autonomous localization. Ad hoc networks are established through the utilization of ultrawide-band (UWB) technology for the purposes of facilitating interpedestrian communication and ranging. This article investigates two cooperative strategies: centralized and decentralized CPNs (dcpns). The cooperative received signal strength (RSS) pair with separated covariance Kalman filtering method is proposed for decentralized CPN in order to circumvent substantial computation and loss of relevance. The field experimental results demonstrate that the centralized and decentralized CPNs enhance the positioning accuracy by 53% and 37% in comparison to the PDR. The primary benefit of CPN is that it obviates the necessity for on-site infrastructure deployment since both IMU and UWB devices are worn on the human body. In particular, the decentralized CPN has been shown to achieve a superior balance between the computational burden on individuals, system survivability in complex scenarios, and the localization performance of the whole team. And it would be quite promising in group navigation scenarios involving pedestrians, drones, robots, and submarines.

We present a scheme to enhance two different magnon modes entanglement in cavity magnomechanics via nonlinear effect. The scheme demonstrated that nonlinear effects enhance entanglement of the two magnon modes. Moreover, the entanglement of the two magnon modes is also significantly enhanced by microwave parametric amplification (PA) and magnon self-Kerr nonlinearity. Not only dose nonlinear effect enhances the strength of entanglement, but it also increases the robustness of entanglement against temperature. Our proposed scheme plays an important role in the research of fundamental theories of quantum physics and quantum information processing theory.

We investigate the absorption and transmission properties of a weak probe field in an atom opto-magnomechanics system. The system comprises an assembly of two-level atoms and a magnon mode within a ferrimagnetic crystal, which directly interacts with an optical cavity mode through the crystal's deformation displacement. We observe optomechanically induced transparency (OMIT) via radiation pressure and a magnomechanically induced transparency (MMIT) due to the nonlinear magnon-phonon interaction. In addition, due to the coupling of the atom to the detected and signal light, the system's width transparency window is divided into two narrow windows. Additionally, we demonstrate that the group delay is contingent upon the tunability of the magnon-phonon coupling strength. Our solution possesses significant in the field of quantum precision measurement.

In order to provide a method for accurately detecting the concentration and types of heavy metal ions in water, a fluid ion detection system is designed. It consists of a side-polished fiber-assisted fluid structure and a long-period fiber grating (LPFG) coated with a metal chelating agent membrane. In this study, both theoretical and experimental investigations are conducted to examine the sensing characteristics of the system towards copper ion and iron ion solutions. The results demonstrate that under the premise of ensuring solution flow, the system can achieve specific identification of different types of heavy metal ions. Furthermore, it exhibits concentration sensing sensitivities of 9.23×104 mL·nm/mol and 7.13×104 mL·nm/mol for copper sulfate (CuSO4) and ferric chloride (FeCl3) solutions, respectively. Therefore, this sensing system offers the potential for real-time detection of metal ions.

Seamless positioning ability has become an essential requirement in large-scale smart city scenes with the development of Artificial Intelligence of Things technology. The performance of seamless positioning is limited by the inaccurate crowdsourced navigation database, cumulative error of built-in sensors, and changeable measurement errors of different location sources. In order to solve these problems, this paper presents the CrowdLOC-S framework, which provides a concrete and accurate indoor/outdoor localization performance using the combination of crowdsourced Wi-Fi fingerprinting, Global Navigation Satellite System (GNSS), and low-cost sensors. A data and model dual-driven based trajectory estimator is developed for improving the long-term positioning performance of built-in sensors, and a hybrid one-dimensional convolutional neural network (1D-CNN), Bi-directional Long Short-Term Memory (Bi-LSTM), and Multilayer Perceptron (MLP) enhanced quality indicator is proposed for quality evaluation of crowdsourced trajectories and further Wi-Fi fingerprinting database construction. Besides, the transfer learning approach is applied in the quality indicator for autonomously predicting the location errors towards different indoor and outdoor location sources and realizing seamless scenes switching. Finally, a unified extended Kalman filter is developed to realize multi-source integration-based seamless localization using the positioning information provided by indoor and outdoor location sources and corresponding quality indicator results. Comprehensive experiments demonstrate that the presented CrowdLOC-S system is proven to realize precise and efficient indoor and outdoor positioning performance in complex and large-scale urban environments.