Phase unwrapping serves as a critical step in high-precision optical measurement， aiming to recover the absolute phase from its wrapped counterpart. While current deep learning-based approaches for absolute phase extraction have achieved improvements in both accuracy and computational efficiency， critical challenges persist， including excessively large network parameter counts and low accuracy in resolving discontinuous phases. To overcome these limitations， this paper introduces the Attentive Directional Encoder-Decoder Network （ADE-Net） for structured light phase unwrapping applications. The primary objective is to develop a lightweight， efficient， and robust deep learning framework that achieves consistently high unwrapping accuracy under complex conditions such as noise corruption， phase discontinuities， and aliasing artefacts， thereby providing a practical， engineering-ready solution capable for reliable development in real-world optical measurement systems.

The proposed ADE-Net is built upon a concise and efficient encoder-decoder backbone architecture. The encoder consists of four feature extraction stages， each comprising a convolutional block and a Haar Wavelet Down-sampling （HWD） module. The HWD structure preserves high-frequency directional details， such as phase jump edges， during down-sampling， providing a more complete feature foundation for subsequent processing. The decoder employs a symmetric up-sampling structure based on transposed convolutions， with skip connections to fuse multi-scale features from the encoder， ensuring effective detail recovery. To enhance feature representation， two innovative modules are integrated： the Adaptive Clockwork Long Short-Term Memory （AC-LSTM） module and the Depthwise-separable-convolution Efficient Multi-Scale Attention （DEMA） module. The AC-LSTM module is designed to capture multi-scale contextual and direction-sensitive features simultaneously. It consists of two parallel branches： an Atrous Spatial Pyramid Pooling （ASPP） branch for multi-scale context aggregation， and a bidirectional LSTM （Bi-LSTM） branch enhanced with Context Anchor Attention （CAA） to model long-range dependencies along horizontal and vertical directions with spatial awareness. The outputs of both branches are fused to produce rich， direction-aware features. The DEMA module is an improved version of the Efficient Multi-Scale Attention （EMA） mechanism. It introduces depthwise separable convolution to replace standard 3×3 convolutions， significantly reducing computational complexity while maintaining receptive field coverage. Additionally， Batch Matrix Multiply （BMM） is adopted for more efficient parallel processing of batch data. DEMA operates by grouping input features， performing adaptive height and width pooling， and applying depthwise separable convolution in parallel branches， followed by cross-branch fusion via BMM and element-wise multiplication with the original features. This design enhances the model's ability to focus on critical information across scales while optimizing computational efficiency.

To comprehensively evaluate the performance of ADE-Net， systematic experiments were conducted using both simulated and real-world datasets. For simulation， three distinct datasets were constructed， each comprising 2 000 pairs of wrapped and absolute phase images with a size of 256×256. Dataset 1 simulated noise interference by introducing Gaussian noise with signal-to-noise ratios of 0， 5， 20， 40， and 80 dB. Dataset 2 simulated phase discontinuities by randomly generating 1 to 2 rectangular jump regions with random positions， sizes， and phase values. Dataset 3 combined both noise and discontinuities to emulate aliasing effects. Additionally， the public real dataset ‘Single-input dual-output 3D shape reconstruction’ was adopted to assess generalization capability， which contains 1 500 real-scene samples acquired by a structured-light 3D measurement system. The evaluation was performed using three metrics： Normalized Root Mean Square Error （NRMSE）， Mean Absolute Error （MAE）， and Structural Similarity Index Measure （SSIM）. Benchmark comparisons were carried out against mainstream models such as U-Net， Res-UNet， Perera's Net， and TNUNet. In the comparative experiments， ADE-Net achieved the best performance across all three simulated datasets. On the discontinuous dataset， it attained an NRMSE of 4.35%， an MAE of 1.094 5 rad， and an SSIM of 0.871 4. On the random-noise dataset， the results were 4.58% NRMSE， 1.216 5 rad MAE， and 0.838 9 SSIM. On the aliased dataset， ADE-Net reached 4.34% NRMSE， 1.137 7 rad MAE， and 0.834 0 SSIM. Cross-validation on the public dataset demonstrated excellent generalization ability， with a Root Mean Square Error （RMSE） of 0.505 2， an MAE of 0.180 9 rad， and an SSIM of 0.997 1. Ablation studies further confirmed the individual performance contributions of both the AC-LSTM and DEMA modules. Moreover， while maintaining the aforementioned high accuracy， ADE-Net also exhibited remarkable computational efficiency advantages. With only 2.012 M parameters and 2.655 GFLOPs， it is significantly lighter than the compared models. The inference time per single image is only 12.71 ms， meeting real-time processing requirements without compromising accuracy， thereby achieving an effective balance between model complexity and computational performance.

In conclusion， ADE-Net presents a lightweight， efficient， and highly accurate deep learning framework for phase unwrapping in structured light 3D measurement. By integrating the AC-LSTM module for capturing direction-sensitive multiscale features and the DEMA module for computationally streamlined attention-driven feature refinement， the models achieve an ideal balance between performance and computational complexity. It demonstrates superior resilience in challenging conditions involving noise corruption， phase discontinuities， and aliasing artefacts， outperforming leading benchmark models in both accuracy and processing efficiency. Rigorous validation on real-world datasets confirms its robust generalization capability， while its fast inference speed and low resource footprint make it well-suited for high-precision phase reconstruction tasks. By addressing practical constrains in deployment， this work promotes the feasibility of structured light 3D measurement system for real-world， resource-aware applications.

Encapsulation is a critical step in semiconductor manufacturing， providing chips with a stable and protected operational environment through integration into compatible external structures. High-precision and non-destructive surface morphology measurement of transparent encapsulated devices is essential， as it enables early detection of latent defects， supports process optimization， and ensures long-term device reliability. However， conventional white light interferometric microscopy faces inherent limitations when applied to encapsulated samples. Existing optical-path compensation schemes offer only restricted compensation ranges， and even small residual mismatches between the encapsulation layer and the compensation glass can introduce monochromatic aberrations and chromatic dispersion. These residual errors degrade fringe contrast， distort the recovered phase， and can ultimately lead to failure in reconstructing surface morphology.

To address these challenges， we propose a dual-arm differential adjustable compensation strategy for white light interferometric microscopy. The method is designed to address the thickness mismatch and material dispersion when measuring encapsulated microstructures. The system incorporates two independently adjustable compensators： a plate compensator inserted into the test arm and a pair of wedge plates placed in the reference arm. The wedge plates provide a thickness adjustment range from 4.8 mm to 5.2 mm enabling the system to realize a continuously adjustable compensation range. The two compensators form a continuously adjustable configuration capable of correcting up to 400 μm of thickness deviation. This design supports stable compensation for encapsulation thicknesses from 0 mm to 5.2 mm. A 2.5× Michelson-type interferometric objective is employed in order to conveniently separate monochromatic aberrations from chromatic dispersion， thereby enabling a focused investigation of dispersion-induced phase distortions and the effectiveness of the proposed compensation strategy.

Theoretical modelling and numerical simulations were conducted to assess the feasibility and robustness of the proposed compensation strategy. The modelling incorporated the spectral characteristics of the light source， the refractive-index dispersion of the encapsulation materials， and the numerical aperture of the interferometric objective. A detailed quantitative analysis was carried out to evaluate the influence of light-source bandwidth， the intensity ratio between the two interferometric arms， and residual thickness mismatch on the achievable fringe contrast. The results highlight the necessity of incorporating adjustable wedge plates to achieve continuous and precise dispersion compensation. Based on the simulation outcomes， acceptable tolerance ranges for the residual mismatch were derived， providing practical design guidelines for implementing adjustable dispersion compensation in interferometric microscopy platforms.

Experimental validation was conducted using three representative classes of samples to verify the measurement accuracy and system stability. In addition to validating measurement accuracy， these experiments were also designed to evaluate the long-term operational stability of the compensation mechanism， especially under varying encapsulation thicknesses. First， a Bruker RM1722 roughness standard was used to evaluate surface roughness under encapsulation. The dynamic adjustment of the wedge plates in the reference arm effectively preserved high-contrast fringes. The encapsulated sample exhibited an arithmetic average roughness of （0.63 ± 0.003） nm， which closely matched the value of （0.61 ± 0.004） nm for the unpackaged sample. Second， a standard SHS-23008 step height specimen was measured beneath a 1 mm K9 cover plate to simulate the encapsulation condition. The reconstructed step height was （9.272±0.021） μm， demonstrating both the accuracy of the compensation method and the robustness of the phase retrieval process. Finally， the technique was applied to TO-packaged photodiodes to characterize the surface morphology of the encapsulated chip region. The arithmetic mean height and root mean square height of the surface were 3.855 nm and 3.892， respectively， indicating the good fabrication quality. These comprehensive results confirm that the proposed dual-arm differential adjustable interferometric method is feasible， reliable， and highly accurate for characterizing the surface morphology of transparent encapsulated microstructures. The demonstrated performance establishes the method as an effective and practical solution for high-precision， non-contact morphology evaluation of transparent encapsulated devices.

With the rapid development of modern weapon systems， high-precision measurement of explosion timing has become a key factor in evaluating weapon effectiveness and supporting tactical decision-making. To address the limitations of existing detonation timing measurement systems—such as inadequate accuracy， limited detection capability， and high cost，this paper presents the design of a high-precision explosion timing measurement system. The proposed system is capable of accurately capturing the instant of projectile detonation， providing a unified time reference for various test-range measurement and control instruments such as high-speed cameras and theodolites. It further supports the analysis of explosion parameters and damage assessment， enabling rapid localization of explosion timing points within large-scale datasets.

The system consists of five major components　an optical signal acquisition and conversion circuit， an analog signal amplification module， a digital processing core， an analog-to-digital conversion subsystem， and a GPS timing unit. In the optical detection stage， a silicon photodiode BPW20 with a peak sensitivity at 920 nm is selected and paired with an AD825 transimpedance amplifier to perform photoelectric signal acquisition and initial amplification. This configuration offers low dark current and low noise voltage， ensuring stable operation under high signal-to-noise ratio conditions. To further enhance long-range detection capability， a condenser lens optimized using Zemax was incorporated into the optical structure， significantly improving the convergence of incident light. Experimental results show that the addition of the condenser lens increases detection capability by approximately ninefold.

To improve timing accuracy， the system adopts a GPS-disciplined local clock architecture， using the 1 PPS signal as the reference. Through hardware-software co-design， the system obtains and maintains synchronization with the GPS time base. An initial time offset of about 7 μs was observed； to eliminate this error， an All-digital Phase-locked Loop （ADPLL） structure was integrated. By employing phase detection and a PI adaptive regulation mechanism， the local clock is precisely aligned with the 1 PPS signal. Oscilloscope measurements after synchronization indicate that the residual timing error is less than 50 ns， thereby achieving high-precision timekeeping based on a standard crystal oscillator while effectively reducing system cost.

In indoor simulation experiments， the system successfully captured transient LED emissions within a range of 5~30 m， verifying its sensitivity and timing accuracy. In outdoor field tests， the system effectively detected the flash produced by firecracker explosions at distances beyond 100 m and accurately recorded the time corresponding to the optical intensity peak. Comprehensive experimental results demonstrate that the proposed system provides precise， real-time， and reliable detection of explosion light and timing， meeting the requirements of modern test-range applications and showing broad engineering potential.

Future research will focus on system miniaturization and low-power design to enable deployment on mobile platforms such as UAVs， thereby extending its applicability within modern test-range systems.

Intraocular Lens （IOL） is a medical device implanted into the eye， commonly utilized in the treatment of ophthalmic conditions such as cataracts. In clinical practice， implanted IOLs frequently exhibit varying degrees of decentration and tilt. These positional deviations from the ideal alignment can significantly compromise the eye's optical performance. Among the widely adopted monofocal IOLs， which are primarily designed to restore distance vision， two main categories exist： spherical and aspherical monofocal IOLs. Aspherical monofocal IOLs can be further subdivided into two types： Aberration-correcting Intraocular Lens （ACIOL） and Aberration-free Intraocular Lens （AFIOL）. ACIOL is specifically designed to neutralize the cornea's inherent positive spherical aberration， thereby enhancing the quality of distance vision. Under perfect centration conditions， these lenses are capable of delivering optimal optical outcomes. In contrast， AFIOL， while not altering the overall spherical aberration of the eye， demonstrate superior performance in the presence of decentration or tilt. Under such non-ideal positional conditions， they are usually superior to ACIOL. However， while numerous studies have evaluated the optical performance of misaligned IOLs， the underlying causes of performance variations among different aspherical monofocal IOL types remain inadequately explored—a challenge that persists in the field. Some investigations have focused on compensating for refractive errors resulting from IOL tilt or axial shift， whereas others have derived analytical expressions to estimate the specific aberration terms that require correction under given decentration conditions. Despite these valuable efforts， a critical gap remains： the absence of a comprehensive theoretical model capable of simultaneously characterizing the aberrations of the human eye's optical system in the presence of both decentration and tilt. This limitation ultimately hinders a systematic analysis of the factors responsible for optical performance differences among misaligned IOLs.

To address these challenges， this study introduces several key improvements. First， the computational model incorporates the thickness of both the cornea and the IOL. Under realistic implantation conditions， the anterior surface of the IOL may not be perfectly aligned with the iris and can exhibit a measurable offset. This misalignment significantly increases the complexity of aberration calculations， requiring repeated application of the pupil-shift law to both optical surfaces. To enable efficient computation and analysis， the wave aberration coefficients corresponding to primary spherical aberration and primary coma in the pseudophakic eye are explicitly derived. Then， based on functional differences， different axial lengths， and functional principles， three types of ACIOL and three types of AFIOL were designed respectively. The validity of both ACIOL and AFIOL is confirmed through a comprehensive analysis of their Modulation Transfer Function （MTF）， spot diagrams， simulated imaging， and aberration characteristics. The accuracy of these aberration coefficients is subsequently verified using numerical software. During the development of the misaligned pseudophakic eye model， we clarify why the primary spherical aberration field remains invariant under lateral misalignments. Subsequently， we establish the relationship between the primary coma field and the aberration field decenter vector. A mathematical formula for determining the coordinates of the primary coma field center is derived， revealing that under misaligned conditions， the pseudophakic eye possesses only one nodal point for primary coma—a position that is demonstrably influenced by lateral misalignments. Moreover， a comparison was made between the designed IOL and a commercial ACIOL， which showed similar MTF， thus demonstrating the universality of the conclusions drawn in this study.

Based on the misaligned pseudophakic eye model， this study investigates the primary coma field centers of both ACIOL and AFIOL under misaligned conditions. Analytical results indicate that a larger shift in the primary coma field center is associated with a lower MTF. Under decentered conditions， the primary coma field center shift of ACIOL is significantly greater than that of AFIOL. Since the posterior surface spherical aberration is consistent between the two types of IOLs， and the absolute value of the anterior surface spherical aberration in ACIOL is significantly higher than that of the posterior surface， reducing the anterior surface spherical aberration becomes necessary to achieve zero overall spherical aberration. However， as both IOL types share the same dioptric power， their spherical contributions to anterior surface spherical aberration are comparable. Consequently， the reduction of anterior surface spherical aberration must be achieved by decreasing its aspherical contribution， specifically by reducing the conic constant of the anterior surface. This adjustment ensures that the total spherical aberration of the IOL is zero for AFIOL. Once the conic constant of the IOL anterior surface is reduced， the aspherical contribution of the primary coma coefficient of the anterior surface decreases. Given that the aspherical contribution of the posterior surface's primary coma coefficient is zero， this reduction leads to a diminished aspherical contribution to the primary coma field center under decentered conditions. Then， the accuracy of calculating the center of the aberration field is verified through numerical software. Furthermore， by discussing the differences in refractive index between corneal and intraocular structures at different wavelengths and their impact on aberration calculation， the rationality of eye model selection can be enhanced. Finally， by discussing the potential impact of a single parameter such as corneal aberration and thickness， the applicability of the conclusions drawn in this study is demonstrated.

By integrating nodal aberration theory with primary aberration theory， we establish a mathematical model that systematically relates IOL misalignments to the primary aberrations of the entire eye. This analytical framework offers a clear advantage over purely numerical approaches， allowing for a principled evaluation of how IOL decentration and tilt influence overall ocular aberrations. Consequently， the model provides a theoretical basis for explaining the performance differences between the two types of aspherical monofocal IOLs under misaligned conditions. The following conclusion can be drawn： 1） Decentration and tilt of an IOL cause displacement of the primary coma field center from the field center. This displacement is collectively influenced by factors such as the magnitude of IOL misalignment， geometry of lens surface， and refractive index. Moreover， the magnitude of the primary coma field center shift demonstrates a negative correlation with the system's MTF； 2） In the design of aspherical monofocal IOLs， appropriately reducing the conic constant can significantly diminish the primary coma field center shift induced by decentration， thereby enhancing optical performance under misaligned conditions. When the primary coma field center shift is sufficiently minimized， the system's MTF can be maintained nearly unchanged. In summary， the misaligned pseudophakic eye model provides a comprehensive framework for understanding how decentration and tilt influence the performance of aspherical IOLs. This approach offers valuable theoretical guidance for future IOL design and evaluation criteria.

In recent years， the development direction of space optical cameras in various countries can be summarized as high resolution， large aperture， and multi-spectral. Compared with single-band visible light imaging optical systems， visible-infrared dual-band optical systems have advantages. Infrared light can penetrate certain objects to obtain information such as their internal structure and heat distribution. At the same time， infrared optical systems have stronger concealment. When combined with visible light systems for imaging and detection of space targets， it can not only acquire rich spectral information across different bands but also achieve all-weather， round-the-clock space remote sensing detection and imaging. Space optical systems can be divided into three design types： refractive， catadioptric， and reflective. Refractive systems have no light obstruction and are easy to assemble， allowing optical design for large fields of view； however， it is difficult to achieve lightweight designs for large-aperture optical systems. Catadioptric systems can achieve large-aperture optical designs， but for systems with large fields of view and infrared detection requirements， the few available infrared refractive materials have low transmittance， poor thermal stability， and high prices. Additionally， lens chromatic aberration is difficult to correct， lens aperture sizes are limited， making it challenging to widely apply in space exploration. Reflective systems combine advantages such as large aperture， wide field of view， long focal length， broad wavelength range， and lightweight design. Currently， most visible-infrared integrated optical systems adopt catadioptric designs， requiring multiple optical elements to correct chromatic aberration， and are unable to meet design requirements for long focal length， large aperture， wide field of view， and lightweight simultaneously.

This paper adopts a reflective system structure. The initial structure of the system is solved based on paraxial aberration theory， and optimized design is carried out using optical design software， with reasonable field-of-view settings to avoid light obstruction. Considering factors such as aperture， volume， weight， and environmental adaptability of space cameras， the optical system adopts an integrated design scheme of shared aperture with separate fields of view. The visible light and mid-wave infrared bands share the front-end coaxial three-mirror primary and secondary mirrors. At the rear end， the fields of view are split and redirected via two fold mirrors into the visible light imaging path and the mid-wave infrared imaging path， achieving simultaneous dual-band imaging. To minimize the aperture size of the primary mirror， the first image plane is located near the center of the primary mirror. For the visible light subsystem， a coaxial three-mirror structure is used for an off-axis field； for the mid-wave infrared subsystem， the front end consists of the primary and secondary mirrors of the visible light subsystem， and the light path enters the rear three-mirror anastigmatic off-axis structure via a fold mirror. Regarding detector selection， the optical system uses a visible light TDI-CMOS with 12 288×128 pixels， 7 μm pixel size， and three identical detectors arranged in a ‘zigzag’ pattern on the image plane， utilizing only a part of the non-vignetting region of the image plane， achieving a 36 000×128 pixel array and 25.2 km swath width. The mid-wave infrared subsystem uses a large-format cooled infrared detector with 3 000×2 500 pixels and 18 μm pixel size. This detector consists of a glass window， filter， cold stop， and focal plane， with a distance of 90 mm between the focal plane and the cold stop.

The working wavelength range of the visible light subsystem is 0.45~0.9 μm， with a focal length of 5 m， an F-number of 10， and a field of view of 0.7°×2.3°. At an orbital position of 500 km， the imaging swath width is greater than 20 km. The working wavelength range of the mid-wave infrared subsystem is 3~5 μm， with a focal length of 1.5 m， a field of view of 0.2°×2°， an F-number of 3， and 100% cold stop efficiency. The two optical systems share the primary and secondary mirrors of a coaxial three-reflector system at the front end， achieving simultaneous dual-band operation through field-of-view segmentation. The entire system uses eight reflective elements. To meet system specifications and correct aberrations， the three mirrors of the front-end three-reflector system use 6th-order aspheric surfaces， while the three mirrors of the mid-wave infrared system adopt freeform surfaces. The imaging quality of the visible and mid-wave infrared subsystems is evaluated using spot diagrams， modulation transfer functions， and distortion assessments. For both subsystems， the spot diagram RMS radii are smaller than the Airy disk radius， the MTF values at the Nyquist frequency are close to their respective diffraction limits， and distortion is controlled within an acceptable range.

A reflective optical system integrating visible and mid-wave infrared light was designed based on paraxial optical theory. This study also verifies the manufacturability of freeform surfaces in engineering practice. The maximum deviation between the freeform surfaces and the optimal aspheric surfaces does not exceed 65 μm， meeting current processing standards. A defocus analysis indicates that the system maintains good imaging quality within the depth of focus. Finally， considering current lens fabrication and assembly conditions， and based on tolerance allocations from previous reflective systems， a tolerance analysis was conducted using the system's rear intercept as a compensating quantity. The results show that the system has good tolerance performance. In summary， the designed optical system meets the initial design specifications， does not require consideration of secondary spectral issues from transmissive elements， affords good imaging quality， and possesses practical engineering feasibility.

High-magnification beam expansion optical systems are critical components in space-based active optical detection and long-range laser transmission， imposing stringent requirements on beam collimation performance， energy utilization efficiency， and structural compactness. Increasing the beam expansion ratio can effectively suppress laser beam divergence and improve far-field spot quality， but it typically leads to a significant increase in system volume and a sharp rise in the difficulty of aberration control. Traditional transmissive beam expansion systems are limited by their clear aperture and face challenges such as thermal effects and material absorption under high-power laser conditions； coaxial reflective systems inevitably suffer from central obscuration and energy loss. Although off-axis reflective systems can avoid these defects， existing designs generally exhibit limitations in beam expansion ratio， design complexity， and excessive overall volume. To address these issues， this paper proposes a design method for a high-magnification compact off-axis three-mirror afocal optical system， aiming to achieve a high beam expansion ratio while maintaining system compactness and reducing the structural design difficulty of off-axis systems.

Large-aperture planar optical components are key parts of the optical systems in high-end equipment such as photolithography machines and laser fusion experimental devices. Full-aperture polishing， also known as continuous polishing， is an important processing method for large-aperture planar optical components. The surface conditioning of polishing pads has been a research focus for scholars both domestically and internationally. Existing research results indicate that effective conditioning is one of the primary factor to enhance the processing accuracy of optical components. For polishing pads with a meter-scale diameter， such as 1 200 mm， turning or grinding processes are typically employed to achieve surface conditioning. However， these methods are not only time-consuming but also struggle to achieve high-precision finishing on the pad surface. Efficient and high-precision conditioning of meter-scale polishing pad surfaces has long been a challenge in the optical component polishing process.

This paper proposes a method for surface topography conditioning of tin polishing pads through temperature field control. A composite polishing pad consisting of tin-aluminum-cast iron is constructed with three kinds of thin plates. A thermal field control system for the composite polishing pad is designed to investigate the internal temperature field distribution patterns of the pad under the influence of a controlled thermal field， and a gradient model of the internal temperature field within the composite polishing pad is established. Based on the bimetallic thermal deformation effect， five thermal stress distribution equations are established on the neutral surface of the three-layer composite polishing pad. By setting boundary conditions， a differential equation for thermal stress elastic deformation of the composite pad is established， and a mathematical model for surface thermal deformation of the tin polishing pad with parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} as the variable is obtained through solving the equation.

Using finite element simulation software， a simulation analysis was conducted on the thermal deformation of the composite material polishing pad's surface. The ambient temperature field was set to 20 ℃， with constraints and a controlled thermal field applied to the bottom surface of the composite polishing pad. When the parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} of the controlled thermal field was set between 16 and 19 ℃， the thermal deformation of the polishing pad's surface was simulated， and the contour， peak value， and average value of the thermal deformation were analyzed. The simulation results indicated that when the controlled thermal field parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} was set to 20 ℃， there was no temperature gradient change within the composite polishing pad， and no thermal deformation occurred on its surface. However， when t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} was less than 20 ℃， the composite material polishing pad exhibited an overall concave-shaped thermal deformation， and the magnitude of the thermal deformation became more pronounced as t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} decreased. Experiments were conducted to validate the regulation law of the thermal field on the surface of a tin polishing pad. Ensuring an ambient temperature of 20 ℃ in a constant-temperature workshop， measurement tools such as laser displacement sensors were used to measure the surface of the polishing pad. The deformation law of the polishing pad's surface was examined at parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} values ranging from 16 to 19 ℃. Finally， through nine sets of processing experiments on optical components， the impact of the parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} on the processing results was verified. The experimental and simulation results showed consistency in the trend of thermal deformation of the polishing pad's surface. Moreover， by adjusting the thermal field control parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}}， the surface accuracy of the processed optical components was optimized.

Through theoretical analysis， simulation， and experimental verification， the paper draws the following conclusions： 1） A controllable thermal deformation prediction mathematical model for the surface topography of the polishing pad was established based on the multi-metallic thermal deformation effect； 2） A finite element model for thermal field regulation of the polishing pad was developed and experimentally validated. Within the temperature range t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} of 16 ℃ to 19 ℃， the finite element analysis results of thermal deformation of the polishing pad were consistent with the experimental results in terms of their changing trends； 3） The thermal deformation generated by the polishing pad thermal field regulation system is the greatest at t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}}=16 ℃， with a maximum deformation of 16.9 μm and an average deformation of 12.5 μm； it is the smallest at t=19 ℃， with a maximum deformation of 2.2 μm and an average deformation of 2 μm； 4） Adjusting the parameter t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}} can enhance the processing accuracy of the component surface. When t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}}=18 ℃， the polishing accuracy of planar optical components is the highest. Compared to when t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}}=20 ℃ and t_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}}=16 ℃， the surface accuracy PV value improves by an average of 20%， and the RMS value improves by an average of 15%； 5） According to the comparative analysis， the mathematical model of thermal deformation on the polishing pad surface and the simulation analysis cannot accurately predict specific values of the thermal deformation. Precise model analysis will be conducted in subsequent research.

Mid-wave infrared interference spectral imagers possess unique advantages in gas detection and identification due to their wide characteristic spectral coverage， high-throughput detection capability， and multi-channel sampling. Particularly in daily inspection and early warning of chemical gases and rapid emergency response to leakage scenarios， they can provide early warnings of disasters at the initial stage of gas leakage， preventing the situation from escalating. After a gas leak occurs， without requiring personnel to enter the site， they can quickly identify the type of leaking gas and the distribution of its diffusion concentration， providing first-hand on-site data for the evaluation of emergency response plans. However， traditional point-scan and area-scan interference spectral imaging configurations face significant limitations in enhancing lightweight， compact design， and stability. It is of great significance to research and design interference spectral imaging instruments that meet the high demands for mobility， adaptability to complex environments， field of view coverage， and lightweight compactness in specific application scenarios. Additionally， as interference spectral imagers require high precision in detector pixel intensity detection， it is necessary to study the analysis and suppression methods of infrared stray radiation in complex scenarios.

This paper proposes a spectral imaging system based on static interference modulation using a stepped micro-mirror. The optical configuration of the system is shown in Figure 1. The scanning telescope imaging lens assembly achieves wide-field one-time convergence imaging onto the stepped micro-mirror for interference modulation， and the image is then relayed onto the detection focal plane through the relay imaging lens group. A cylindrical design is introduced to compensate for the high-order astigmatism introduced by the interference beam-splitting system. Achromatic broadband design and athermalization across a wide temperature range are achieved through hybrid refractive-diffractive and aspheric designs， resulting in a static Modulation Transfer Function （MTF） better than 0.7 at the cutoff frequency. To analyze infrared stray radiation， a stray radiation model for the interference spectral imaging system was constructed. The materials and surface radiation scattering characteristics of the optomechanical structure were defined， and ray tracing was performed. Based on the tracing results， a stray radiation suppression structure was designed， achieving infrared radiation suppression at the level of 10⁻⁵.

The telescope imaging lens group was optimized with an image-space telecentric design， while the relay imaging lens group adopted an object-space telecentric design， achieving a perfect match in a dual-high telecentric optical system. By employing hybrid refractive-diffractive and aspheric designs， the system demonstrated excellent performance in the mid-wave infrared band of 3 μm-5 μm across a temperature range of -40 ℃ to 60 ℃. The static MTF exceeded 0.7 at 17 lp/mm， distortion was controlled within 0.2%， and the RMS radius of the imaging spot was less than 5.9 μm， meeting all imaging quality requirements. A stray radiation simulation model for the interference spectral imaging optomechanical system， as illustrated in Figure 7， was constructed. Stray radiation tracing was performed for typical field light paths， and based on the analysis results， efficient suppression was achieved through blackbody extinction treatment and dedicated stray radiation suppression structures. This reduced the infrared stray radiation energy ratio from an initial level of 10⁻² to 10⁻⁵. Imaging detection experiments on long-distance target scenes using an engineering prototype demonstrated excellent image quality. The MTF test of the prototype of high-precision alignment principle shows that the actual MTF of the designed imaging system is better than 0.32 at the cut-off frequency.

The infrared spectral imaging system based on static interference modulation with a stepped micro-mirror successfully achieves high-quality remote sensing imaging， identification and analysis of gases. The adoption of achromatic methods using cylindrical lenses and hybrid refractive-diffractive lenses， together with the stray radiation suppression method proposed in this paper， has all yielded the expected effects in optimizing imaging quality， which is proven to be effective and can serve as a reference for research in the same field. In addition， the instrument's volume is reduced by a quarter and its weight by approximately 60%， which also provides a valuable contribution to the miniaturization process of such imaging systems.

Precise micro-displacement measurement technology plays a critical role in real-time defect monitoring during manufacturing processes， ensuring adherence to accuracy standards and significantly reducing scrap loss. Chromatic confocal displacement measurement systems operate based on the principles of optical dispersion and confocal technology. Through chromatic encoding， a wavelength-axial position mapping relationship is established， while confocal imaging decodes the reflected spectrum. This enables real-time displacement measurement with sub-micrometer accuracy within a millimeter range， simultaneously providing nanometer-level resolution and robust environmental adaptability. The measurement range and accuracy are constrained by the axial dispersion and aberrations of the dispersive objective. To expand the measurement range and enhance the accuracy of the chromatic confocal displacement sensing system， a secondary dispersion objective based on Gradient-index （GRIN） fiber was designed in this study. The Physics-Informed Neural Network （PINN） algorithm was leveraged in conjunction with ZEMAX software simulation to broaden the system's chromatic dispersion while achieving comprehensive compensation and correction of aberrations in both the secondary dispersion objective and the pre-dispersion GRIN fiber.

Firstly， based on the working principle of chromatic confocal displacement sensors， a GRIN fiber-based chromatic confocal system was proposed. A pre-dispersion unit employing GRIN fiber was established according to its refractive index distribution and the Cauchy dispersion model. The relationship between wavelength and axial dispersion was derived. The chromatic focal shift of the GRIN fiber at different pitch numbers was simulated and analyzed. It was determined that at a GRIN fiber pitch number of m=5， an axial pre-dispersion of 1.496 mm could be achieved， with a linearity R² of approximately 95%. Subsequently， based on Hamiltonian optics theory， the aberrations introduced by the GRIN fiber were derived. Based on the calculated equivalent object position of the GRIN fiber pre-dispersion unit and aberration theory， the GRIN fiber aberrations were analyzed. A secondary dispersion objective was then specifically designed. Its dispersion performance was analyzed and aberrations were optimized using ZEMAX. Finally， to improve system resolution and correct aberrations， an aberration correction method employing PINN combined with ZEMAX for closed-loop verification was proposed. A dataset correlating “lens parameters” with “Zernike aberrations” was established using ZEMAX. Combined with aberration data from the pre-dispersion GRIN fiber， PINN was utilized to predict feedback and perform iterative optimization. This facilitated comprehensive aberration correction and optimized axial dispersion linearity.

Within the operating wavelength range， the corrected spherical aberration values were significantly lower than pre-correction levels， with particularly pronounced correction in the short-wavelength region. Post-correction spherical aberration values for all wavelengths were markedly optimized， demonstrating effective spherical aberration correction. The aberration correction model demonstrated strong generalization capability， and the overall model training was effective， confirming successful aberration correction. The effectiveness of the aberration correction methodology using ZEMAX software combined with the PINN algorithm for closed-loop verification was thus validated. Following algorithmic optimization， a new optimized dispersive objective lens group was obtained. Results demonstrate that the maximum system aberration was reduced below 10 μm. Total axial dispersion reached 4.34 mm with a linearity R² of 99.84%. Theoretical resolution was approximately 25 nm. In the optimized system， the RMS spot radius at the focal point for each wavelength across the visible spectrum was smaller than the Airy disk， achieving diffraction-limited performance and meeting high-precision displacement measurement requirements. This study provides novel chromatic confocal system optimization， enhancing displacement measurement performance and advancing practical engineering implementation.

Intense solar activities （such as coronal mass ejections and solar flares） release a large number of high-energy charged particles. When these particles reach Earth， they interact with the magnetosphere and trigger magnetic storms through processes like particle precipitation. The duration of magnetic storms can range from several hours to days. During this period， they cause ionospheric disturbances and drastic changes in the geomagnetic field， leading to disruptions in on-orbit satellite communications and shortwave broadcasting， significant degradation or even loss of lock in the positioning accuracy of global navigation satellite systems， and an increased risk of accelerated orbital decay for low-orbit satellites due to sudden increases in atmospheric drag.

During magnetic storms， precipitating particles collide with the upper atmosphere at the poles along magnetic field lines， exciting the generation of auroras. The radiation characteristics of auroras are directly related to the flux and energy of the incident particles. Therefore， detecting the morphology of auroras in specific wavelength bands has become a key method for studying solar activities.During magnetic storms， precipitating high-energy particles collide with neutral atmospheric components （such as atomic oxygen and nitrogen molecules） above Earth's poles. Through excitation and ionization processes， these collisions produce auroral radiation covering wavelengths from visible light to the far ultraviolet. Among this radiation， the emission intensity of the LBH band of nitrogen molecules （N₂）—located in the far ultraviolet range of 160~180 nm—has a direct and sensitive quantitative relationship with the energy flux of the precipitating particles.

Far ultraviolet radiation is effectively absorbed by the upper atmosphere， enabling its observation even in sunlight. However， achieving high-precision imaging of N₂ LBH band auroral radiation faces two core technical challenges. Firstly， the dynamic range of auroral brightness under natural conditions is extremely wide. Imaging across a range from approximately 100 Rayleigh （R） to over 30 000 Rayleigh （30 kR） during intense activity periods requires the instrument to have an extremely high linear dynamic range. Secondly， in the far ultraviolet band， stray light interference from non-target sources （such as the Sun and geocoronal background） is extremely strong， which can easily overwhelm weak auroral signals. This places extremely stringent requirements on the system's internal stray light suppression capability.

To capture the full dynamic range （100 R~30 kR） of N₂ LBH band （160~180 nm） auroral radiation and overcome the challenges of weak far ultraviolet signals and strong background interference， this study developed an optical system based on a coaxial four-reflection structure. The core of the instrument's performance lies in its large dynamic range detection capability and high stray light suppression level. Through targeted optical design， simulation， and testing， the system ultimately achieved a signal-to-noise ratio （SNR） > 1.5 for extremely weak signals （100 R）， ensuring the reliable extraction and detectability of weak signals. For strong signals （30 kR）， the SNR reached > 30， guaranteeing measurement accuracy and the upper limit of dynamic range during intense auroral activity. Meanwhile， the stray light suppression level reached 10^-3 within the 160~180 nm operating band and exceeded 10^-9 in the non-operating band of 200~1 000 nm， thereby effectively extracting real auroral signals from complex optical backgrounds.

This instrument can continuously monitor the spatiotemporal evolution of the position， morphology， scale， and intensity distribution of the auroral oval. Through inversion and analysis of these high-quality image data， we can quantitatively obtain core parameters such as information on precipitating particles and their energy flux. This deepens the scientific understanding of magnetic storm triggering mechanisms， energy coupling processes， and evolution laws. It provides crucial data support and technical backing for accurate magnetic storm forecasting， space weather modeling， and ensuring the stable operation of on-orbit satellites and ground communication systems， boasting significant scientific value and broad application prospects.

Fiber-optic microphones have emerged as an innovative solution in the field of acoustic sensing due to their compact size， excellent immunity to electromagnetic interference， and superior insulation performance. These attributes make them ideal for use in various challenging environments such as power systems， healthcare， petrochemical industries， and national defense. However， despite these advantages， traditional fiber-optic microphones still face challenges in terms of sensitivity， stability， and insulation， particularly in high-performance or demanding conditions. Some existing designs struggle with low sensitivity in detecting weak acoustic signals or may experience degradation in performance due to material instability and electromagnetic interference under extreme conditions. Additionally， ensuring stable insulation properties in high-temperature or harsh electromagnetic environments remains a challenge for many fiber-optic microphone designs. Therefore， this work proposes and fabricates a novel high-sensitivity fiber-optic microphone featuring a dual-rib diaphragm structure.

The microphone unit consists primarily of a dual-rib diaphragm， a single-mode optical fiber， and a glass sleeve， which work in synergy to convert acoustic signals into optical signals for high-precision measurement. The diaphragm's design was optimized through finite element simulations to achieve the desired resonance characteristics and enhance its acoustic sensitivity. Specifically， the ribbed diaphragm structure was designed to increase its flexibility， thereby improving its response sensitivity to pressure changes. To fabricate the diaphragm， we employed a picosecond laser micro-nano machining system， which allowed us to achieve high precision and fine features in the diaphragm's ribbed structure. This fabrication process ensures that the diaphragm can withstand mechanical stresses during acoustic signal detection while maintaining high sensitivity.

The fabricated fiber-optic microphone exhibits a high sensitivity of 1 418.9 mV/Pa and a signal-to-noise ratio of 60.47 dB at a resonance frequency of 15.58 kHz， demonstrating excellent performance in acoustic signal acquisition. The microphone's high sensitivity makes it suitable for detecting weak acoustic signals， even in environments with significant background noise. Moreover， the microphone displays a strong directional response， which is critical for applications that require precise localization of sound sources. These characteristics make it an excellent candidate for use in a variety of industrial and scientific applications， where accurate and reliable sound detection is required.

The potential applications of this high-sensitivity fiber-optic microphone are vast. It is particularly suited for power sensing， where it can be used to detect weak acoustic signals from power equipment， monitor partial discharges， diagnose faults， and enable online monitoring of power lines. The microphone's immunity to electromagnetic interference and high sensitivity make it ideal for use in environments with high levels of electrical noise. In addition， the microphone's ability to detect low-level acoustic signals makes it a promising tool for applications in healthcare， such as monitoring bodily sounds， as well as in the petrochemical industry for detecting gas leaks and machinery failures. Beyond these initial applications， the fiber-optic microphone holds promise for many other emerging fields. For example， it could be integrated into advanced monitoring systems for industrial automation， where real-time acoustic feedback is used for predictive maintenance and early detection of mechanical failures. In the field of robotics， the microphone's small size and high sensitivity could be leveraged in autonomous systems for environmental sound detection and localization. Additionally， as wireless technology continues to advance， fiber-optic microphones could be used in conjunction with wireless communication systems for remote sensing applications， further extending their potential. Future research will focus on optimizing the diaphragm design to achieve a broader frequency response and enhancing the microphone's robustness in extreme environments. Additionally， efforts will be directed at improving the signal processing capabilities of the fiber-optic microphone to ensure high-performance operation in complex and diverse environments. This work lays a solid foundation for the development of high-sensitivity fiber-optic microphones， which will undoubtedly lead to their widespread application in high-performance acoustic sensing fields， offering substantial benefits for industrial， scientific， and healthcare applications.

The Underwater Wireless Optical Communication （UWOC） system has advantages such as high transmission speed and high reliability. The presence of ocean turbulence can induce fluctuations in light intensity， thereby degrading the communication performance of the system. Quasi-Cyclic Low-Density Parity-Check （QC-LDPC） codes can mitigate the impact of ocean turbulence on Bit Error Rate （BER） and enhance the communication performance of UWOC systems. However， research on QC-LDPC codes in UWOC has primarily focused on theoretical analysis and numerical simulation. The gain effect of QC-LDPC coding may vary under different modulation formats， and specific experimental verification is lacking. In response to the absence of experimental research on the coding gain of different modulation formats in turbulent environments， this paper investigates the influence of QC-LDPC codes on the coding gain of different modulation formats in weak ocean turbulent channels under mixed coding modulation schemes.

A mathematical simulation model for weak turbulent channels in UWOC is established based on the Log-normal distribution. The check matrix H is constructed using the Dayan sequence， and QC-LDPC encoding is carried out based on the minimum row-column product LU decomposition algorithm to obtain the encoded sequence， which exhibits lower computational complexity compared to direct encoding algorithms. At the receiving end， the Minimum Sum Algorithm （MSA） with low computational complexity is selected for decoding， which is convenient for hardware implementation. The coding gain and communication characteristics of QC-LDPC encoding under different modulation formats， scintillation indices， transmission distance， encoding lengths， and other parameters are simulated and analyzed. Subsequently， a blue-green laser communication experimental platform is designed and built based on a simulated ocean turbulence pool， and comparative experimental research is conducted on the communication performance of QC-LDPC-encoded ocean turbulence optical communication with multiple modulation formats at a transmission distance of 1.5 m and a transmission rate of 10 Mbps. Field Programmable logic Gate Array （FPGA） is employed for QC-LDPC encoding， signal modulation and demodulation. Temperature-induced turbulence is simulated by injecting hot water of different temperatures into a transparent water tank， and salt-induced turbulence is simulated by injecting salt water of different concentrations， and normalized scintillation index {\delta }_{\mathrm{I}}^{\mathrm{2}}is introduced to describe the fluctuation of light intensity at the receiving end， in order to measure turbulence intensity. Aiming to research the encoding gain of QC-LDPC for different modulation formats in weak turbulence environments.

The simulation results indicate that the performance improvement brought by adding QC-LDPC encoding in low Signal-to-Noise Ratio （SNR） On-Off Keying （OOK） modulation and Binary Phase-Shift Keying （BPSK） control modulation may be insufficient to offset the increase in decoding complexity， leading to an increase in the BER. Incorporating techniques such as low-pass filtering or probability shaping at the receiving end to improve the waveform can appropriately reduce the BER and increase the encoding gain. The BER of the QC-LDPC coded Differential Phase-Shift Keying （DPSK） modulation system decreases as the code length increases， and the best anti-turbulence effect is achieved when the code length is 2 400. In contrast， the BER of the QC-LDPC coded DPSK modulation system increases with the increase in the scintillation indices， communication distance， and data rate. When the communication distance is 10 m and the scintillation indices is 0.14， the BER of DPSK modulation with QC-LDPC coding is reduced to 4×10⁻⁵. The experimental results show that QC-LDPC encoding can effectively mitigate the impact of weak turbulence on the BER. Compared with the uncoded modulation format， when the BER is 10⁻⁵， the encoding gains of QC-LDPC encoding for OOK modulation in tap water， temperature-induced turbulence （{\delta }_{\mathrm{I}}^{\mathrm{2}}=0.056）， and salt-induced turbulence （{\delta }_{\mathrm{I}}^{\mathrm{2}}=0.034） environments are 0.46 dB， 0.49 dB， and 1.31 dB， respectively； while the encoding gains for DPSK modulation are 0.83 dB， 0.79 dB， and 1.63 dB， respectively. The QC-LDPC encoding gains for OOK modulation and DPSK modulation in salt-induced turbulence are higher than those in temperature-induced turbulence.

The coding gain of QC-LDPC codes for OOK modulation and DPSK modulation in salt-induced turbulence is higher than that in temperature-induced turbulence. Adding the mixed modulation of QC-LDPC coding in the UWOC system is conducive to reducing the underwater turbulence effect and has a better turbulence suppression effect compared with DPSK modulation alone. The combination of the QC-LDPC+DPSK coding modulation system has higher coding gain and better anti-interference ability compared with the QC-LDPC+OOK coding modulation system.

Surface Plasmon Resonance （SPR） sensing technology detects changes in environmental parameters， such as Refractive Index （RI）， by exciting surface plasmon waves through the interaction between incident light and free electrons on a metal surface. Fiber-optic SPR sensors have been widely applied in medical diagnostics， food safety， and environmental monitoring due to their compact size， low cost， and strong resistance to electromagnetic interference. However， conventional single-channel SPR sensors contain only one sensing region， which limits their capability for simultaneous multi-parameter detection in complex environments. Meanwhile， the emerging two-dimensional material Ti₃C₂-MXene （hereafter referred to as MXene）， featuring a high specific surface area and anisotropic electrical properties， has demonstrated great potential for enhancing sensor sensitivity and enabling accurate detection of trace analytes.

Leveraging the properties of MXene， in this study， a dual-channel No-core Fiber （NCF） SPR sensor based on MXene is proposed and optimized to address the demand for high-sensitivity and multi-parameter detection in complex environments. The sensor is constructed by cascading a Multimode Fiber （MMF） with two segments of NCFs. Channel 1 is coated with a gold film， while channel 2 is functionalized with a composite film of gold-cysteamine-MXene. Owing to the different dielectric constants of the two sensing coatings， SPR is excited at distinct spectral regions， enabling dual-channel RI sensing. The optimal structural parameters， including a 50 nm gold layer， NCF lengths of 5 mm （channel 1） and 12 mm （channel 2）， and MXene film thickness， are determined via the commercial finite element method software COMSOL Multiphysics.

In the experiment， a gold film with a thickness of approximately 50 nm is deposited on channel 1 using an ionsputter coater （SBC-12）， with a sputtering time of 310 s and a current of 6 mA. MXene nanosheets are subsequently immobilized onto the gold surface of channel 2 via electrostatic self-assembly. Specifically， channel 2 is immersed in a 4 mg/mL cysteamine solution for 30 minutes， during which the thiol groups of cysteamine formed Au-S bonds with the gold film， while the ammonium ions render the surface positively charged. Thereafter， channel 2 is immersed in a 5 mg/mL monolayer-dispersed MXene solution for 2 hours. The negatively charged —F and —O terminal groups on the MXene surface interacts electrostatically with the positively charged ammonium groups， resulting in the uniform deposition of a monolayer MXene film on the fiber-optic surface. Surface characterization using Scanning Electron Microscope （SEM） and Energy Dispersive Spectroscopy （EDS） confirms the successful immobilization of gold， cysteamine， and MXene. The sensor's RI sensitivity is evaluated by monitoring resonance shifts in NaCl solutions with varying RI. Simulation and experimental results consistently demonstrate that increasing MXene thickness improves RI sensitivity and expands the dual-peak separation. This improvement is attributed to the low carrier concentration and high mobility of MXene， which modulate the SPR resonance from the visible to the near-infrared region and enhance the interfacial electric field.

Within the RI range of 1.333 to 1.366， as the number of MXene layers deposited on the surface of channel 2 increases from 0 to 5， the resonance wavelength of channel 2 exhibits a red shift， which is consistent with the simulation results. When the MXene reaches three layers， the resonance peaks of the two channels become completely separated. The RI sensitivity of channel 1 remains stable between 1 850 and 1 900 nm/RIU， with its Full Width At Half Maximum （FWHM） and Figure Of Merit （FOM） showing minimal variation. In contrast， the resonance wavelength of channel 2 （SPR-2） red-shifts from 604.15 nm to 781.28 nm， and its RI sensitivity increases from 2 016.31 nm/RIU to 4 209.16 nm/RIU， representing an improvement of 108.75%. Meanwhile， the resonance wavelength undergoes a red-shift from 604.15 nm to 781.28 nm. However， excessive MXene thickness results in a deterioration in the FOM. To achieve a balance between sensitivity and FOM， a four-layer MXene structure is selected for channel 2. After cascading with channel 1， the dual-channel SPR sensor exhibits optimal performance， achieving a dual-peak separation of 125.35 nm. The RI sensitivities of channel 1 and channel 2 are 1 894.27 nm/RIU and 4 001.48 nm/RIU， respectively， with corresponding FOM values of 16.86 RIU^-1 and 32.99 RIU^-1. Compared with the pure gold film structure， the RI sensitivity of channel 2 is increased by 98.45%.

The dual-parameter detection capability is validated by immersing the two sensing regions in solutions with different RIs. The results demonstrates that both channels responded independently to external RI changes. In the independent response tests， channel 1 and channel 2 achieve RI sensitivities of 1 826.25 nm/RIU and 4 317.96 nm/RIU， respectively， confirming the sensor's potential for simultaneous detection of different analytes. To evaluate the stability of the sensor， both sensing regions are simultaneously immersed in pure water and monitored continuously for 60 minutes. The maximum resonance wavelength fluctuations are only ±0.17 nm for channel 1 and ±0.21 nm for channel 2， indicating the excellent stability of the sensor. Compared with existing dual-channel SPR sensors， the proposed sensor features a simplified structure， ease of fabrication， and low cost， while delivering significantly enhanced RI sensitivity. These advantages make it a promising candidate for multi-parameter biosensing and environmental monitoring applications.

This study aims to enhance the accuracy， robustness， and training stability of deep-learning-based single-frame fringe projection profilometry. It focuses on two practical limitations commonly encountered in existing methods： the incompatibility between conventional intensity normalization schemes and the highly skewed brightness distribution of fringe images， and the lack of physically consistent data augmentation strategies under limited labeled data conditions. The objective is to develop a preprocessing framework that preserves effective fringe information， improves model adaptability across different neural network architectures， and provides a model-aware optimization strategy without altering network structures or learning objectives.

To achieve this goal， a unified preprocessing framework integrating Range-clipped Piecewise Contrast Normalization （RPCN） and Structured Stripe Occlusion Augmentation （SSOA） is proposed. RPCN is specifically developed to address the intrinsic characteristics of fringe images， which typically exhibit a large proportion of low-intensity pixels and a small number of extreme outliers caused by saturation， specular reflection， or sensor noise. The method combines interval clipping to suppress extreme pixel values， power-law mapping to enhance contrast in dark fringe regions， and piecewise remapping to separate shadow-dominated regions from effective fringe regions. This method redistributes pixel intensities into a range more suitable for neural network learning while maintaining stripe continuity and contrast stability. In parallel， SSOA is introduced to improve data diversity in a physically meaningful manner. Instead of directly masking or zeroing pixels， SSOA generates structured occlusions whose missing regions are reconstructed using neighboring stripe patterns， thereby preserving spatial continuity and phase-related information. This augmentation strategy simulates realistic measurement disturbances such as partial occlusion， surface defects， and local signal loss while maintaining physical consistency. The proposed framework is evaluated on multiple network architectures with varying capacities， including UNet， UNet++， and DeepLabv3+ with a MobileNetV2 backbone， to assess its generality， adaptability， and sensitivity to network complexity.

Extensive experiments demonstrate that single-frame depth estimation performance is significantly improved across different network architectures by the proposed preprocessing strategies， while distinct effects are observed depending on model capacity. On the UNet architecture， the mean absolute error was reduced by 17.9% through the application of RPCN， indicating enhanced feature representation under limited normalization adaptability. When SSOA was applied independently， the root mean square error was reduced by 9.8%， and the peak signal-to-noise ratio was increased from 28.48 dB to 29.38 dB， reflecting improved robustness to structured disturbances. The joint application of RPCN and SSOA further increased the structural similarity index from 0.967 8 to 0.971 8. For the more powerful UNet++ architecture， the combined RPCN-SSOA framework yielded the best overall performance， with the structural similarity index increased from 0.977 2 to 0.979 1 and the peak signal-to-noise ratio improved from 29.73 dB to 30.34 dB. In contrast， for lightweight models such as DeepLabv3+ with a MobileNetV2 backbone， performance gains were constrained when SSOA was introduced， as the increased data complexity hindered effective learning， whereas a more favorable balance between accuracy improvement and training stability was achieved using RPCN alone. Additional evaluations across multiple test scenes further confirm that prediction stability is consistently improved under varying surface reflectance and illumination conditions. These results indicate that preprocessing strategies interact strongly with network capacity and architectural design， and that inappropriate augmentation may limit performance gains in compact models.

The proposed RPCN-SSOA preprocessing framework provides a practical and adaptable solution for improving deep-learning-based single-frame fringe projection profilometry. By aligning intensity normalization with fringe-specific brightness distributions and enforcing physical consistency in data augmentation， the framework enhances depth estimation accuracy and robustness without increasing model complexity. The results highlight the importance of model-aware preprocessing demonstrate that normalization and augmentation strategies should be tailored to network capacity rather than uniformly applied. This work offers a feasible preprocessing paradigm and practical guidance for fringe-based three-dimensional measurement systems in both research and engineering applications.

Infrared small target detection， as the core technology of infrared search and tracking systems， plays a crucial role in military precision guidance， low-altitude economic monitoring， border surveillance， and space situational awareness. Its primary objective is to achieve rapid and accurate localization of small targets with low signal-to-noise ratios and weak contrast under long-distance conditions. In recent years， detection methods based on deep learning have gradually become a research hotspot and have achieved remarkable progress in detection accuracy. Most mainstream approaches adopt mask-to-mask or box-to-box regression training strategies， which can effectively enhance model robustness with the support of large-scale annotated datasets. However， these methods suffer from two major drawbacks. On the one hand， they heavily rely on high-quality， large-scale annotations， which are costly to obtain. On the other hand， in order to further improve accuracy， these methods often increase the depth and width of the network to expand model capacity， leading to massive parameters and complex architectures. To mitigate these issues， some studies have attempted to use weak supervision deep learning as a replacement for traditional mask or bounding-box annotations to reduce annotation costs. However， due to the limited granularity of supervision， the detection accuracy is often significantly constrained， making it difficult to balance practicality and precision.

To address the above challenges， this paper proposes a lightweight infrared small target detection algorithm based on point-to-point regression. The goal is to achieve high-accuracy detection while significantly reducing annotation and computational costs. The main contributions of this work are as follows. First， an asymmetric full-dimensional dynamic feature extraction module is designed. This module integrates channel shuffle with omni-dimensional dynamic convolution， which effectively models fine-grained dependencies across channel and spatial dimensions while maintaining network lightweightness. As a result， it enhances the discriminative features of the target and suppresses background interference. Second， a high-resolution cross-feature enhancement module is proposed. This module aligns multi-level features via upsampling， downsampling， and convolution mapping， and builds cross-layer interaction branches to dynamically fuse low-level detail features with high-level semantic features. In this way， it strengthens semantic representation while preserving spatial detail information， making it particularly suitable for weak and small target detection scenarios. Finally， an adaptive point regression detection head is introduced. This head models the distribution of target centers using Gaussian heatmaps， and combines local maxima filtering with a scale-adaptive mechanism to achieve precise prediction and sub-pixel localization. In this process， only single-point annotations are required for training， which substantially reduces the cost of data labeling.

Extensive experiments conducted on two public datasets， IRSTD-1K and NUDT-SIRST， demonstrate the effectiveness of the proposed method. With an extremely small number of parameters （only 0.24 M） and low computational complexity （1.53 GFLOPs）， the proposed algorithm achieves outstanding performance： F1 score of 91.79% on IRSTD-1K and 97.44% on NUDT-SIRST， which are significantly superior to existing state-of-the-art methods. In addition， the model reaches an inference speed of 36 FPS on a single GPU， fully demonstrating its potential for real-time infrared small target detection in practical applications.

The broad field of view inherent to remote sensing images offers significant advantages for large-scale monitoring tasks， enabling comprehensive surveillance over vast geographical areas with a single acquisition. However， this advantage is often offset by the presence of complex backgrounds， such as cloud cover， shadows， and varying terrain textures， which frequently introduce channel-level noise that interferes with target features. This interference significantly compromises the robustness and reliability of detection models， particularly in adverse weather conditions or densely cluttered environments. Additionally， the substantial variation in target sizes， ranging from small objects like vehicles and helicopters to large structures such as ports and bridges， poses a significant challenge. Detection models struggle to simultaneously capture high-resolution details necessary for identifying small targets and low-resolution semantic information essential for recognizing larger objects， leading to unbalanced detection performance across different scales.

To address the aforementioned challenges， this paper proposes a remote sensing image object detection algorithm based on adaptive feature weighting， built upon the Oriented R-CNN framework. The method introduces two core modules： the Adaptive Channel Weighting Module （ACWM） and the Adaptive Multi-Scale Fusion Pyramid （AMFP）， aimed at tackling background interference and multi-scale target detection issues. The ACWM module is applied after the STAGE 2 and STAGE 3 phases of the feature extraction network to adaptively adjust channel weights， a critical step for enhancing feature representation. By analyzing statistical correlations between channels using the Correlation-Aware Covariance Weighting （CACW） method， it generates dynamic channel weights to enhance target-related features while suppressing background noise and redundant information， balancing the expression of different channels and thereby improving the feature extraction network's ability to extract features from rotated targets. Subsequently， the AMFP module processes the multi-scale features （C2， C3， C4， and C5） extracted by the feature extraction network， employing a hierarchical approach for feature integration. The Multi-scale Perception and Context Integration Module （MPCIM） fuses global semantic features from deep layers with edge and positional details from shallow layers， effectively addressing the issue of small targets being obscured. The Adaptive Layer Weighting Module （ALWM） optimizes the fusion quality of multi-scale features through adaptive layer-wise weighting， enhancing the model's capability to handle diverse target scales ranging from small vehicles to large ports by dynamically adjusting the contribution of each feature level， thus improving adaptability to various target scales. The optimized features （P2， P3， P4， and P5） are then fed into the Oriented RPN and Oriented RCNN head， which， based on the Oriented R-CNN framework， generates high-precision rotated bounding boxes to complete classification and localization tasks.

To validate the effectiveness of the proposed algorithm， extensive experiments were conducted on the DOTA1.0 and DIOR-R datasets. Ablation studies were performed to assess the contributions of the ACWM and AMFP modules. Results indicate that the ACWM module alone improves the mean Average Precision （mAP） by 0.97% on DOTA1.0 and 1.73% on DIOR-R， while the AMFP module contributes an additional 1.30% and 2.01% improvement， respectively. When both modules are combined， the mAP reaches 78.23% on DOTA1.0 and 68.17% on DIOR-R， representing overall enhancements of 2.36% and 3.87% compared to the baseline Oriented R-CNN model. Visualization comparisons further demonstrate the superiority of the proposed method， showing a significant reduction in missed detections and false positives for small targets， particularly in categories such as Small Vehicle， Swimming Pool， Helicopter， and Storage Tank. The method also exhibits improved localization accuracy and better contour fitting for rotated objects， especially in complex backgrounds with varying angles and dense distributions. The experimental results highlight the robustness and adaptability of the proposed algorithm across diverse remote sensing scenarios.

Compared to state-of-the-art methods such as Faster R-CNN， RoI Transformer， and ARC， the proposed approach achieves superior performance in handling small targets and complex orientations， as evidenced by its higher mAP and enhanced visual detection outcomes. However， limitations remain， including potential performance degradation in extremely cluttered scenes or with ultra-small targets， suggesting avenues for future optimization.

Electrowetting Display （EWD）， as a novel reflective display technology， offers high reflectivity， wide viewing angles， fast response， and full-color display， making them highly promising for applications in portable terminals， wearable devices， and outdoor information displays. However， as display panels evolve toward larger sizes and higher resolutions， the scale of driving circuits and refresh rates increases significantly， leading to growing power consumption issues that directly affect device battery life and application scope. Existing low-power studies rarely fully integrate the reflective imaging characteristics and optoelectronic properties of EWD， and power optimization under complex ambient lighting conditions still has considerable room for improvement.

To address these challenges， this paper proposes a low-power algorithm based on ambient light compensation， designed to reduce power consumption and improve display quality by leveraging the reflective characteristics of EWD. In addition， an adaptive voltage adjustment technique is introduced， which dynamically adjusts the driving voltage according to ambient light intensity， further reducing driving power consumption. The proposed low-power algorithm consists of four main components： 1） voltage–reflective luminance curve calibration， ensuring that the luminance differences between adjacent gray levels under various ambient light conditions are closer to those under standard ambient light； 2） extraction of the original grayscale information of the image， followed by grayscale correction using a mapping table generated during the calibration process； 3） detail enhancement to improve edge and texture representation in the image after calibration， compensating for potential detail loss； and 4） calculation of the driving voltage corresponding to the highest pixel value after processing， based on the Pulse Amplitude Modulation （PAM） driving method， and setting it as the maximum driving voltage for the given ambient light condition to achieve adaptive voltage adjustment.

The proposed ambient light dynamic compensation calibration method was applied to an EWD system. Test points were set at the positive and negative power supply terminals of the source driver， and an EKA1080M power consumption tester was used to measure the power consumption before and after algorithm processing. The test video sequence consisted of black screen-original image-black screen-processed image-black screen， enabling comparison of power consumption differences before and after processing. Results show that， in the source driver voltage section， the processed images consumed significantly less power than the original images. Further measurements of current and voltage at the test points under different ambient light conditions， combined with the power calculation formula， revealed that the overall power consumption under standard ambient light was 18.93 mW/in²， and decreased to 14.21 mW/in²， 12.06 mW/in²， and 11.72 mW/in² under ambient light intensities of 483 cd/m²， 970 cd/m²， and 1 730 cd/m²， respectively—representing reductions of 24.9%， 36.3%， and 38.1% compared to the unoptimized case.

In terms of image quality， the objective evaluation metric Average Gradient （AG） increased by 4.9%， 3.9%， and 2.3% under the three ambient light conditions， respectively， indicating that the processed images exhibited higher clarity， more prominent edges， and richer details. Moreover， the brightness of the processed images was closer to that of the standard ambient light display， providing a more comfortable and stable viewing experience under varying lighting conditions. In summary， the proposed method significantly reduces the power consumption of EWD while effectively maintaining and even enhancing display quality.

The primary objective of this study is to design and experimentally validate a low-loss edge coupler based on a bi-level taper structure on the thin-film lithium niobate platform， specifically targeting efficient coupling with standard single-mode fibers having a mode field diameter of 6 μm at the 1 310 nm wavelength， to address the critical challenge of high coupling losses between Thin-film lithium niobate waveguides and optical fibers that hinder practical applications in integrated photonic systems such as fiber optic gyroscopes， aiming for a solution compatible with mass production via deep ultraviolet lithography while maintaining low optical loss and high alignment tolerance.

To achieve this， the coupler design incorporates two sequentially fabricated inverted tapers—a fully etched lower taper and a partially etched upper taper—within a silicon dioxide cladding， and the structural parameters were rigorously optimized using three-dimensional finite-difference time-domain simulations to maximize the mode field overlap integral between the waveguide and fiber， where key geometric variables including the taper lengths L₁ and L₂ （both set equal to L for simplicity）， the lower taper tip width W₁， the upper taper tip width W₂， the lower taper output width W₃， and the straight waveguide width W₄ were systematically varied to assess their impact on coupling efficiency， with initial simulations determining an optimal taper length L of 300 μm to satisfy adiabatic conditions and avoid excessive transmission loss or fabrication-induced defects， followed by width optimizations revealing optimal values of W₁ at 0.2 μm， W₂ at 0.2 μm， W₃ at 3.5 μm， and W₄ at 1.2 μm for single-mode operation， while additional analysis of the silicon dioxide upper cladding thickness indicated that a minimum thickness of 3 μm is essential to confine the mode effectively and prevent vertical leakage， with negligible efficiency variation between 3 and 6 μm.

Fabrication involved electron beam lithography for rapid prototyping and validation， where X-cut Thin-film lithium niobate with a 300 nm thick lithium niobate layer on a 4.7 μm silicon dioxide substrate was patterned using two Electron beam lithography steps followed by inductively coupled plasma-reactive ion etching to define the upper and lower tapers sequentially， and a 6-micrometer silicon dioxide cladding was deposited via a combination of low-pressure chemical vapor deposition and plasma-enhanced chemical vapor deposition to ensure density and minimize hydrogen-related losses. Experimental characterization employed a 1 310 nm superluminescent diode source and single-mode fibers in a cut-back method setup to measure total insertion loss， yielding a coupling loss of approximately 2.3 dB per facet for the optimized design， with the straight waveguide propagation loss separately quantified as 0.47 dB per centimeter， and scanning electron microscopy imaging confirmed the fabricated structure but indicated an approximate 110-nanometer lateral misalignment between the upper and lower tapers， though subsequent Finite-difference time-domain simulations demonstrated that such misalignments up to ±300 nm introduce negligible additional loss below 0.03 dB， affirming high fabrication tolerance. Further experimental sweeps of parameters W₁ and L showed consistent trends with simulations， where coupling loss decreased with increasing L up to 300 μm and increased with W₁ above 0.2 μm， and comparative analysis with existing coupler designs highlighted that this bi-level taper structure achieves a favorable balance between performance and process complexity， requiring only two etching steps and avoiding reliance on costly ultra-high numerical aperture or lensed fibers， thus enabling practical， low-cost deployment in fiber gyroscope applications.

In conclusion， the proposed bi-level taper edge coupler successfully demonstrates low coupling loss， robust manufacturability with substantial alignment tolerances， and full compatibility with standard single-mode fibers and deep ultraviolet lithography mass production， thereby providing a viable pathway for scalable integration of Thin-film lithium niobate based photonic devices.

In recent years， visible-light integrated photonics has undergone rapid development， demonstrating significant applications across various fields. In biosensing， integrated optical waveguide sensors based on the evanescent wave effect enable high-sensitivity real-time monitoring of analytes by detecting optical parameter variations induced by changes in analyte properties. For consumer electronics， miniaturized on-chip spectrometers provide real-time spectral analysis capabilities for smart devices， supporting applications such as food safety testing and health monitoring. In optical computing， metasurfaces and diffractive neural network technologies have facilitated the development of low-power intelligent sensing chips with ultra-fast parallel processing capabilities， capable of performing tasks such as image recognition and object tracking.

Extending the operational wavelength range of these devices to cover the entire visible spectrum holds considerable importance， as it can enhance the detection accuracy and applicability of miniaturized spectrometers， broaden the bandwidth of visible-light communication systems， and enable biosensors to simultaneously detect multiple biomolecules in complex samples. As fundamental components of integrated photonic devices， waveguides serve as the core elements for directional photon transport and device interconnections in most on-chip systems. However， current research on full-visible-spectrum waveguides remains incomplete， with most studies focusing on waveguide dimension design for specific narrow bands. The investigation of low-loss transmission across the entire visible spectrum in single waveguide structures remains insufficient， which may limit their applications in on-chip full-visible-spectrum devices. Therefore， this study proposes a waveguide design that supports the entire visible spectrum （435~760 nm）.

Generally， single-mode waveguides exhibit superior performance compared to multimode waveguides. However， research has revealed conflicting requirements for single-mode operation across different wavelengths： shorter wavelengths require smaller dimensions to suppress higher-order modes， while longer wavelengths necessitate larger dimensions to prevent energy leakage. Consequently， none of the three commonly used waveguide structures （rectangular waveguides， rib waveguides， and slab waveguides） can achieve single-mode operation across the entire visible spectrum. As an alternative approach， this study systematically investigates key parameters for minimizing propagation loss under multimode transmission conditions.

Considering the respective advantages and research value of polarization-sensitive and polarization-insensitive waveguide platforms， dimension designs were completed for both TE-polarized thin waveguides and polarization-insensitive thick waveguides based on silicon nitride platforms with thicknesses of 500 nm and 1 μm， respectively： For thin waveguides， the thickness was optimized at 0.5 μm after comprehensive consideration of loss and fabrication challenges， while thick waveguides were designed with 1 μm thickness to achieve polarization-insensitive low-loss transmission. The width of thin strip waveguides was selected as 1.5 μm for lower loss， whereas thick waveguides were designed with 2 μm width to mitigate scattering loss induced by sidewall roughness. Regarding spatial configuration， thin waveguides require minimum waveguide spacing of 0.6 μm and minimum bending radius of 15 μm， while thick waveguides permit tighter configurations with 0.4 μm spacing and 10 μm bending radius. For both waveguide types， fabrication dimensional tolerances exhibit negligible impact on optical transmission. Additionally， thin waveguides demonstrate high sensitivity to sidewall roughness， whereas thick waveguides maintain relatively low transmission loss when the root-mean-square roughness is ≤10 nm.

Comparative analysis of the two waveguide configurations reveals distinct advantages　thin waveguides offer easier fabrication and higher integration density， though they are limited to TE-mode operation； thick waveguides feature comparable effective refractive indices for TE and TM modes， making them suitable for polarization-insensitive applications in systems employing broadband LED sources （e.g.， biosensors and color imaging）， despite requiring specialized stress-control processes during fabrication. Both configurations present unique advantages that can be selected based on specific device requirements.

In summary， this study analyzes propagation loss and mode distribution in waveguides to determine optimal parameters for low-loss transmission， including waveguide dimensions， bending radii， and spacing. Furthermore， it evaluates the impact of fabrication tolerances on waveguide performance， providing valuable references for the design and manufacturing of on-chip photonic devices operating across the full visible spectrum.

Quasi-phase matching technology overcomes the limitations of photonic crystal materials and their transmission bands by artificially designing nonlinear photonic structures. Through periodic ferroelectric domain inversion achieved by electric field poling， this approach compensates for phase mismatch while enhancing the efficiency and flexibility of nonlinear frequency conversion. Quasi-periodic structures， with their aperiodic yet ordered arrangements， provide abundant reciprocal lattice vectors. An increasing variety of superlattice structures have been implemented in optical materials to explore their advantages for generating harmonics across diverse wavelengths.

In this study， we incorporated the aperiodic hat-tiling monotile structure into nonlinear optical superlattices， successfully designing and fabricating a two-dimensional planar hat-tiling superlattice. The attainable harmonic wavelengths and their characteristics were systematically investigated. Experimental results demonstrate that the reciprocal space of the aperiodic hat-tiling superlattice exhibits pronounced sixfold rotational symmetry while maintaining periodic intense diffraction points. The diffraction pattern of the hat-tiling superlattice structure exhibits not only hexagonal symmetry but also additional bisecting points between every two vertices of the hexagon. Comparative analysis with conventional periodic structures reveals that the hat-tiling pattern demonstrates more pronounced intensity variations among diffraction spots. Furthermore， the reciprocal vectors in this configuration include additional orientations deviated by 30° from the horizontal axis as well as vertical directions. Under collinear conditions， the structure successfully achieved second-harmonic generation at fundamental wavelengths of 858 nm， 895 nm， 932 nm， 1 055 nm， and 1 100 nm， while under non-collinear conditions， the hat-tiling structure enabled efficient SHG at multiple fundamental wavelengths including 892 nm， 971 nm， 1 089 nm， 1 103 nm， and 1 389 nm. Comparative analysis with periodic hexagonal structures confirmed that the aperiodic hat-tiling offers richer reciprocal vectors. Moreover， the periodicity in reciprocal space significantly enhances the conversion efficiency of nonlinear photonic crystals.

In conclusion， the hat-tiling structure offers reciprocal vectors of varying magnitudes along multiple directions. While preserving the high conversion efficiency characteristic of regular hexagonal structures， it overcomes the limitation of single reciprocal vectors in hexagonal lattices. The hat-tiling structure can provide reciprocal vectors of varying magnitudes along multiple directions to compensate for phase mismatch， thereby extending the achievable frequency bandwidth of fundamental waves. Based on the experimental results， we propose an optimized design by scaling the hexagonal edge length of the hat-tiling superlattice structure to 32.2 μm. This modification enables the strongest diffraction point to correspond to a reciprocal lattice vector that achieves second-harmonic generation for a fundamental wavelength of 1 550 nm， which is particularly significant for optical communication applications. The experimental data provide crucial references for further optimization to fully exploit the high-efficiency diffraction points. These findings advance the development of multi-channel nonlinear optical devices with enhanced spectral flexibility.

Surface waves propagating along the interface of two distinct media have garnered significant attention in recent years， owing to their promising applications in fields such as optical sensing， optical switching， and surface characterization. Extensive research has been conducted on surface solitons based on the standard Schrödinger equation， and many novel characteristics have been found.

Recently， an extended version of the standard Schrödinger equation has been introduced into the system， where the diffraction term is described by a fractional-order derivative rather than the second-order derivative in the conventional form. This extended equation is referred to as the fractional Schrödinger equation. Promptly thereafter， an optical realization of the equation was proposed based on the transverse light dynamics in an aspherical optical resonator， alongside a scheme for generating dual-Airy states. Notably， this marked the first introduction of the fractional Schrödinger equation into the field of optics， which opened up a novel research direction in optics. Since then， numerous studies on solitons with fractional diffraction have been reported. However， relevant research on surface solitons supported by the fractional nonlinear Schrödinger equation remains relatively scarce. Focusing on the propagation of two-dimensional surface gap solitons under fractional diffraction， this study investigates the existence， stability， and propagation properties of fundamental and in-phase dipole solitons at the interface between bulk media and an optical lattice in self-defocusing Kerr nonlinear media via numerical methods.

The band structure of the optical lattice was calculated via the plane-wave expansion method. Subsequently， the existence region of surface gap solitons was obtained by modified squared operator iteration method， while their stability was analyzed through the Fourier collocation method and further verified via the split-step Fourier method.

The results show that　the first bandgap and the semi-infinite bandgap gradually broaden with an increase in the Lévy index， while the other bandgaps progressively narrow as the Lévy index increases. Both fundamental and in-phase dipole solitons can exist within the first gap of the Bloch bands， and both fundamental and in-phase dipole solitons at the interface exhibit an asymmetric morphology. As the Lévy index increases， the peak intensity of the soliton decreases. Similarly， the peak intensity also declines with an increase in the propagation constant. Combined verification through propagation simulations and linear stability analysis reveals that： except for the in-phase dipole solitons away from the interface， which exhibit instability in a small region near the lower edge of the first Bloch band， all other surface gap solitons maintain stability throughout their entire existence range. Additionally， it also indicates that as the Lévy index increases， both the existence interval and stability interval of surface gap solitons gradually broaden. When a phase tilt factor is introduced to the surface gap solitons， applying the phase tilt in a single direction yields distinct behaviors： a small phase tilt causes the soliton center to oscillate periodically only along the direction of the applied phase tilt. A large phase tilt in the y-direction not only induces irregular oscillations of the soliton center along the y-direction but also elicits such oscillations along the x-direction. However， a large phase tilt in the x-direction solely results in irregular oscillations of the soliton center along the x-direction. If the same phase tilt is introduced in both directions， a small phase tilt causes the soliton center to undergo periodic oscillations in both directions， while a large phase tilt leads the soliton center to exhibit irregular oscillations in both directions. The results indicate that a small phase tilt induces slight periodic oscillations in the soliton's mass center， while the soliton shape remains nearly unchanged. In contrast， a large phase tilt leads to irregular oscillations in the mass center， accompanied by gradual distortion of the soliton.

Optical lattice solitons， as key entities at the intersection of nonlinear optics and photonics， not only provide an ideal model for uncovering fundamental physical principles of nonlinearity and periodicity coupling， but also break through technical bottlenecks in conventional optical transmission， manipulation， and storage. A considerable number of studies have been reported on the existence and stability of defect solitons under both normal and fractional diffraction mechanisms. However， the properties of defect solitons in optical lattices under the combined influence of fractional effects and PT-symmetric potentials have not been thoroughly investigated. This paper focuses on studying the existence， stability， and propagation dynamics of defect solitons in PT-symmetric optical lattices with fractional diffraction， examining the impact of fractional effects and defect types on the bandgap structure， analyzing the existence domain of defect solitons， elucidating their linear stability， and discussing the influence of system parameters on the characteristics of defect solitons.

A theoretical model for optical wave propagation in Kerr nonlinear optical lattices with PT-symmetric potentials under fractional-order effects is established based on the fractional nonlinear Schrödinger equation. The plane wave expansion method is used to analyze the effects of defect strength and fractional-order characteristics on the bandgaps of defect solitons. The modified squared-operator iteration method is employed to numerically solve the model and obtain steady-state solutions of the defect solitons. Additionally， perturbations are introduced to the steady-state solutions， and linear stability analysis is performed using the Fourier collocation method. Finally， the propagation properties of the solitons are verified by means of the symmetrized split-step Fourier method.

The bandgap range of the optical lattice narrows as the Lévy index decreases. As the defect strength increases from negative to positive， the semi-infinite gap gradually narrows， while the other bandgaps progressively widen. Under negative defect conditions， the power of solitons in both the semi-infinite gap and the first gap generally decreases with increasing propagation constant， except for an initial increase followed by a decrease in the low-power region of the semi-infinite gap and the medium-power region of the first gap. As the Lévy index varies， the stable region of solitons in the semi-infinite gap gradually shrinks， while solitons in the first gap remain unstable. Under zero defect conditions， the soliton power in both the semi-infinite and first gaps decreases monotonically with the propagation constant. The influence of the Lévy index on soliton stability is similar to that under negative defects. Under positive defect conditions， the soliton power in both gaps decreases with increasing propagation constant， but a cutoff point exists where the power reaches zero. Moreover， a smaller α results in a smaller propagation constant at the cutoff point. Similarly， a decrease in α reduces the stable region of solitons in the semi-infinite gap， although stable solitons exist in the first gap. Additionally， for all three defect types， the width of the defect soliton envelope narrows slowly as α decreases， while the peak intensity increases gradually. The power decreases with reduced α， and the peak intensity of the soliton envelope decreases as the defect strength changes from negative to positive.

This study investigates the existence， stability， and propagation dynamics of defect solitons in PT-symmetric optical lattices with fractional diffraction. Under fractional diffraction， as the Lévy index increases， the power of defect solitons in the semi-infinite bandgap and the first bandgap gradually increases for all defect lattices， while the stability of solitons improves. In cases of negative defects and zero defects， defect solitons only have stable intervals in the semi-infinite bandgap and are completely unstable in the first bandgap. In cases of positive defects， defect solitons have stable intervals in both the semi-infinite bandgap and the first bandgap. Additionally， within the semi-infinite bandgap， as the Lévy index decreases， the peak of the defect soliton envelope increases while its width narrows； as the propagation constant increases， the peak of the defect soliton envelope decreases rapidly. Within the first bandgap， the peak of the soliton envelope decreases as the Lévy index decreases and decreases as the propagation constant increases under positive defect conditions. In summary， the envelope， power， and stability of defect solitons are significantly influenced by the defect strength， Lévy index， and propagation constant.

Orbital Angular Momentum （OAM） beams， featuring spiral phase wavefronts， act as critical new information carriers in optical communication， manipulation， imaging and quantum information. However， ocean turbulence， driven by temperature and salinity fluctuations， induces intensity scintillation， phase distortion and mode crosstalk in OAM beams， hindering their marine application. Traditional identification methods relying on optical components are complex and environment-sensitive， while current machine learning-based static models fail to satisfy marine real-time response requirements due to high retraining costs.

To address these challenges， this study proposes an online OAM identification method based on the Online Sequential Extreme Learning Machine （OS-ELM）. This efficient online sequential learning algorithm has a three-layer structure. The input layer receives feature vectors of OAM beams， with the number of nodes matching the feature dimension. The hidden layer has a fixed number of nodes and supports two activation modes： additive mode and RBF-type mode. Additive mode uses random weights and biases， while RBF-type mode uses random centers and influence factors. The parameters of the hidden layer are fixed after random initialization， eliminating the need for time-consuming gradient iterations. The output layer generates One-Hot encoded labels for OAM modes， and the output weights are solved through Moore-Penrose generalized inverse to ensure fast model training. The implementation of the method in this study consists of two key components： data generation and model construction. In the data generation phase， a numerical simulation model is built using MATLAB to generate an OAM spot dataset affected by oceanic turbulence. Key parameters include the specific inner and outer scales of oceanic turbulence， an appropriate waist radius of Laguerre-Gaussian beams， a wavelength commonly used in optical communications， and fixed spacing of random phase screens. The dataset covers LG modes with topological charges ranging from 1 to 10 and generates intensity images. For data preprocessing， 200 turbulence-affected images are generated for each topological charge， forming a training set of 2 000 images and a test set of 600 images. After adjusting the image size via bicubic interpolation， performing grayscale conversion， double-precision conversion， and normalization to the range of ［-1， 1］， the 2D image matrices are flattened into 1D feature vectors， which are combined with labels to form a feature matrix. In the model construction phase， the dataset is divided into an initial training block with 1 000 samples and 20 online training blocks with 50 samples each. The initial training block is used to calculate the hidden layer output matrix， solve the initial weights by combining the label matrix and Moore-Penrose generalized inverse， and define an intermediate matrix. During online learning， the hidden layer output matrix of the new data block is first computed； the intermediate matrix is then updated using the Woodbury identity without retraining historical data. Finally， the output weights are incrementally updated using the new labels and prediction residuals， ensuring the model dynamically adapts to OAM beam feature drift while maintaining real-time performance.

Based on the same dataset， comprehensive experimental comparisons are conducted between the Online Sequential Extreme Learning Machine OS-ELM and other models， including Support Vector Machine （SVM）， Incremental Naive Bayes classifier （IncNB）， and Naive Bayes classifier （NB）， with performance evaluated using multiple metrics. In weak turbulence scenarios， the Accuracy of OS-ELM reaches 92.33% higher than SVM's 85.33%， IncNB's 87.00%， and NB's 88.67%， with simultaneous leadership in Precision， Recall， and F1-Score. In moderate turbulence， its Accuracy is 71.17% far exceeding SVM's 49.50%， IncNB's 51.83%， and NB's 62.00%. Even in strong turbulence， it maintains an Accuracy of 54.33% higher than SVM's 37.33%， IncNB's 38.83%， and NB's 50.67%. The ROC （Rate of Change） curve of OS-ELM clusters near the top-left corner of the coordinate plane， with AUC （Area Under Curve） values of 0.992， 0.946， and 0.890 under weak， moderate， and strong turbulence respectively， significantly outperforming the comparison models.

The advantages of OS-ELM stem from two core mechanisms： first， the random initialization of hidden layer parameters and analytical solution of output weights avoid the risk of falling into local optima and eliminate the need for complex kernel function calculations required by SVM， enabling efficient approximation of the global optimal solution； second， the online sequential learning mechanism supports real-time incremental updates， accurately adapting to OAM beam feature drift caused by oceanic turbulence and overcoming the inherent limitation of traditional static models with fixed parameters. Looking ahead， the dynamic adaptability， high robustness， and real-time performance of the online sequential extreme learning machine make it highly compatible with complex interference and high-frequency dynamic changes in marine environments. With further engineering development， this method holds significant potential to drive technological upgrades in intelligent manufacturing and industrial communication.

Femtosecond laser filamentation has drawn much attention from researchers recently， which contains fruitful physical processes， such as the self-focusing induced by the optical Kerr effect， plasma defocusing， self-phase modulation and so on. It has shown great potential for many applications in the atmospheric field， such as remote sensing， lightning control， rain making. When propagating in the atmosphere， the influence of the turbulence on the filament spatial distribution has to be taken into consideration. Many studies have been dedicated to the filamentation distance， filament survival rate， transverse wandering， multiple filaments formation induced by turbulence.

Interestingly， it has been demonstrated that the air turbulence can have opposite effects of either increasing or decreasing the filamentation probability and either decreasing or increasing the filament onset distance depending on the initial experiment conditions. However， few studies have been dedicated to explore the mechanism of this phenomenon based on numerical simulation method， which would be significant for understanding the mechanism of the interaction between turbulence and laser filamentation.In this paper， the propagation of a single laser filament was simulated based on the laser filament nonlinear propagation model and the turbulent phase screen model.

The filamentation probability as a function of initial laser beam power was investigated in the turbulent air with turbulence structure constant C_n^{\mathrm{2}} of 10^-13 cm^-2/3， 10^-12 cm^-2/3 and 10^-11 cm^-2/3. The corresponding minimum initial laser powers for the formation of the laser filament with the filamentation probability larger than 0 under the above three turbulent conditions are 0.96 P_cr，0.68 P_cr and 0.14 P_cr， respectively. Moreover， the filamentation probability increases with the turbulence intensity C_n^{\mathrm{2}} when the initial laser beam power is less than P_cr. Thus， the air turbulence can trigger the laser filamentation for an initial laser power below the filamentation threshold. In the next step， the effect of a lens as a focusing optics on the filamentation probability in the turbulent air with C_n^{\mathrm{2}} of 10^-12 cm^-2/3 has been studied. By using a lens with focal length of 5 m as the focusing optics， the laser filamentation probability is always larger than that without any focusing optics in the turbulent air when the initial laser power is less than the filamenting threshold. However， for a lens with focal length of 2 m， the laser filamentation probability is less than that without any focusing optics in the turbulent air. Thus， using a lens with a relative large focal length could promotes the filamentation probability effectively in the turbulent air. Further， the filament onset distances in the turbulent air with different turbulent intensities have been investigated. The initial laser power is chosen to be 1.4 P_cr. The filament onset distance is 354 cm in the calm air. When C_n^{\mathrm{2}} is 10^-14 cm^-2/3， the filament onset distance varies between 349 cm and 358 cm. The average filament onset distance is 353.3 cm. When C_n^{\mathrm{2}} is 10^-11 cm^-2/3， the filament onset distance varies between 107 cm and 290 cm. The average filament onset distance is 149.1 cm. The relationship between the average deviation of the filament onset position 〈\mathrm{\Delta }r〉 and \sqrt[]{C_n^{\mathrm{2}}} has been obtained. For 4×10^-13 cm^-2/3≤C_n^{\mathrm{2}}≤4×10^-12 cm^-2/3， the relationship between 〈\mathrm{\Delta }r〉 and \sqrt[]{C_n^{\mathrm{2}}} can be fitted linearly well.

The interaction mechanism between the air turbulence and the laser beam can be determined by the parameter Q， which is defined by the ratio of the coherent area in the beam and the power it contains over the critical laser power for self-focusing. When C_n^{\mathrm{2}} is larger than 2.25×10^-12 cm^-2/3， Q is larger than 1. Under this condition， the air turbulence is relative strong， leading to the modulation instability of the beam phase， which can promote the filament formation finally. Thus the filament onset distance is always shorter than that without any turbulence. When C_n^{\mathrm{2}} is less than 2.25×10^-12 cm^-2/3， Q is much larger than 1. Under this condition， the air turbulence is relative weak， which will act as a noise and suppress the whole beam self-focusing effect. The filamentation probability will decrease and the filament onset distance will be lengthened. This study will pave the way to understand the mechanism of the influence of air turbulence on the filamentation probability and filament onset distance and would be valuable for many applications of the laser filament in the atmosphere.