The output energy of regenerative amplifiers and its stability are crucial performance indicators. With the rapid advancement of high-power laser technology, there is a growing demand for higher output energy and power in regenerative amplifiers. However, the peak pulse energy in these amplifiers is limited by the damage threshold of the optical elements in the resonator. When the pulse width and peak power are fixed, increasing the output energy requires expanding the beam diameter in the resonator. Consequently, regenerative amplifier resonators are typically designed in the second stability region to achieve a sufficiently large beam diameter. However, resonators in this region are highly sensitive to misalignment, and longer resonator length exacerbates this sensitivity. Therefore, maintaining beam pointing stability in regenerative amplifiers is critical for ensuring stable output power. To achieve a long resonator length within a limited space, mirrors are commonly used to fold the resonator, and their arrangement influences beam pointing stability.

This study analyzed the impact of mirror arrangements on beam pointing stability within the resonator to ensure stable output power. Using modal analysis and microvibration theory, we examined the spatial distribution of disturbances on optical elements. Two mirror arrangement models were developed: a large-mirror configuration (model A) and a mirror-array configuration (model B). We used a regenerative amplifier in a high-power laser system as a case study, conducting Monte Carlo simulations and a over continuous 22-hour energy output experiment to compare the effects of these mirror arrangements on the output energy stability, thereby indirectly characterizing beam pointing stability.

Experimental and simulation results indicate that the mirror-array configuration (model B) significantly outperforms the large-mirror configuration (model A) in terms of beam pointing stability, even under the same vibration amplitude. During a over continuous 22-hour energy output test, model A exhibited a peak-to-valley (PV) value of 60.704% and an RMS (root-mean-square) value of 14.729% in average energy output stability. In contrast, model B achieved a much lower PV value of 2.325% and an RMS value of 0.429%. The mirror-array configuration effectively minimizes the impact of individual mirror disturbances by averaging errors across multiple elements, thereby enhancing the overall system stability. Conversely, the large-mirror configuration amplifies the influence of a single mirror’s stability owing to the multiple reflections required by each large mirror, which can degrade system performance. Although the large-mirror setup theoretically reduces the number of optical elements and potential error sources, it demands higher stability from each mirror. When mirror stability is consistent, the mirror-array configuration demonstrates stronger resistance to disturbances, leading to significantly improved beam pointing and energy output stability compared to the large-mirror configuration.

This study uses structural modal analysis and examines the influence of microvibrations on beam pointing to establish a kinematic model for the microvibration of individual optical elements. Additionally, it analyzes the spatial distribution of disturbances on these elements. By comparing the large-mirror configuration (model A) and mirror-array configuration (model B), the study explores how mirror arrangements affect beam pointing stability. Theoretical analysis shows that the mirror-array configuration (model B) outperforms the large-mirror configuration (model A), regardless of whether the mirrors are correlated or uncorrelated. In tests in which only the mirror arrangement was changed, a over continuous 22-hour energy output experiment showed that model A had an average energy output stability with a PV value of 60.704% and an RMS value of 14.729%. In contrast, model B achieved a PV value of 2.325% and an RMS value of 0.429%. These results highlight the clear advantages of the mirror-array configuration over the large-mirror setup. The experimental results indicate that the mirror arrangement significantly affects the output energy stability of regenerative amplifiers. In summary, the mirror arrangement affects beam pointing stability in laser systems, thereby influencing energy output stability. The study provides theoretical support and practical guidance for the design of precision laser systems.

Interferometric fiber-optic hydrophones (FOHs) have been widely applied in the exploration and geological surveying of marine resources owing to their high sensitivity, wide dynamic range, and long-term stability. The demodulation scheme is key to the distortion-free restoration of the target signal in FOH systems. Currently, the phase-generated carrier (PGC), 3×3 fiber-coupler, and heterodyne schemes are the most commonly used schemes. The PGC scheme offers advantages such as good linearity and excellent stability; however, nonlinear distortion is unavoidable because of its unstable modulation depth and phase delay. The 3×3 fiber-coupler scheme is widely used owing to its large dynamic range and simple architecture; however, its demodulation performance is limited by the coupler manufacturability. Meanwhile, the heterodyne scheme offers advantages such as good sensitivity and excellent stability; however, noise is inevitable owing to dual-pulse transmission. We previously proposed a frequency-shift quadrature demodulation scheme for FOH systems, which involves constructing a pair of interference pulses via frequency shifting and time-delay processing after bisecting a single pulse, in addition to considering the optical path difference (OPD) between the two arms of the FOH. This scheme, which does not present carrier and manufacturability limitations, offers many advantages, such as low noise floor and large dynamic range. The frequency-shift quadrature demodulation scheme adapts to the calibration algorithm to calculate the direct current (DC)/ alternating current (AC) parameters and then uses them as fixed values. However, in practice, AC/DC values typically fluctuate during long-term operation owing to factors such as temperature variations, which introduces harmonic distortions. In this study, a frequency-shift quadrature-fitting demodulation scheme for an FOH system is proposed, which is improved by introducing a least-squares ellipse-fitting algorithm. The improved scheme solves the AC/DC parameters in real time and eliminates harmonic distortions. The frequency-shift quadrature-fitting demodulation scheme demonstrates satisfactory demodulation performance and long-term operational stability. Additionally, we design the field-programmable gate array (FPGA) architecture of the scheme to increase its flexibility and versatility.

A desirable frequency-shift quadrature-fitting demodulation scheme enables the real-time calculation of AC/DC parameters. In this study, an elliptical-fitting algorithm is introduced to improve the previous scheme. Analysis results show that, because the phase difference between two interference signals remains constant and carries the same target signal, the Lissajous figure formed by the two interference signals is an elliptical arc. Therefore, the corresponding ellipse parameters are calculated via a direct least-squares fitting of the ellipse. Subsequently, based on the correspondence between the interference signal and ellipse formula, the expressions for the AC and DC parameters can be further derived using the ellipse parameters. Next, cos φ and sin φ can be obtained using the AC/DC parameters and interference signals, and the value of phase difference φ can be obtained by performing an arctangent operation on tan φ. Finally, the demodulation results of the two schemes under AC/DC parameter drift are compared experimentally to confirm the performance of the frequency-shift quadrature-fitting demodulation scheme. In the FPGA design of the frequency-shift quadrature-fitting demodulation scheme, performing a direct least-squares fitting on the ellipse in the FPGA is challenging owing to the matrix inverse operation. Thus, we perform the Cholesky decomposition to convert the matrix inverse operation into basic arithmetic and square operations that the FPGA can manage to achieve ellipse fitting.

The experimental setup is constructed based on the schematic illustration shown in Fig. 4. Additionally, a dedicated FOH is constructed for the test, with an OPD of 0.225 m between the two arms, and the piezoelectric ceramics (PZT) is internally integrated with the FOH for target-signal injection. A frequency-shift quadrature demodulation scheme and a frequency-shift quadrature-fitting demodulation scheme are applied using this experimental setup for performance comparison. A 1 kHz, 2.5 rad target signal is applied to the FOH. The experimental results indicate that the time-domain waveforms of the demodulation results using the frequency-shift quadrature demodulation scheme distort under fluctuations (Fig. 6), whereas the distortion-free frequency-shift quadrature-fitting demodulation scheme restores the sinusoidal waveform (Fig. 7). Additionally, the power spectral density, signal-to-noise ratio and distortion (SINAD), and total harmonic distortion (THD) of the demodulation results obtained under the two schemes are analyzed (Fig. 8). The SINAD and THD of the frequency-shift quadrature demodulation scheme are 22.4 dB and 0.12%, respectively, and those of the frequency-shift quadrature-fitting demodulation scheme are 50.6 dB and 0.04%, respectively. The improved scheme exhibits a higher SINAD, a lower THD, and effective harmonic elimination, and performs significantly better than the previous scheme. A Vivado simulation system is used to verify the feasibility of the FPGA design. The simulation proves that the frequency-shift quadrature-fitting demodulation scheme successfully completes the ellipse fitting, arctangent, and unwrapping operations within the FPGA and finally demodulates the 1 kHz, 3 rad sinusoidal target signal (Fig. 11), thus validating the FPGA design.

In this study, a frequency-shift quadrature-fitting demodulation scheme for an FOH system is proposed. In this scheme, a pair of interference pulses is constructed via frequency shifting and time-delay processing after bisecting a single pulse, and the OPD between the two arms of the FOH is considered. Subsequently, the pair is further demodulated using an ellipse-fitting algorithm. Additionally, the FPGA design of the scheme is implemented using the Cholesky decomposition, and its feasibility is verified using the Vivado simulation system. The FPGA design allows the system to perform demodulation without a computer, which increases the flexibility and versatility of the application. Experimental results show that the frequency-shift quadrature-fitting demodulation scheme can accurately demodulate the target signal under AC/DC parameter drifts. The SINAD and THD afforded by the scheme are 50.6 dB and 0.04%, respectively, which are 28.2 dB higher and 0.08% lower than those of the previous scheme, respectively. Thus, the proposed frequency-shift quadrature-fitting demodulation scheme is applicable to underwater acoustic target detection and characteristic measurements.

As an important physical parameter, curvature can reflect the structure and shape of the measured object and is a crucial parameter for assessing the degree of deformation of an object. Curvature sensors can be used not only for monitoring the health of bridges and buildings but also play a significant role in aerospace and medical fields. Therefore, curvature sensors have a promising development outlook and significant research importance. Multi-core optical fibers are used for making curvature sensors due to their unique spatial structure advantages. Although some multi-core optical fiber curvature sensors exhibit high sensitivity, most optical fiber curvature sensors have limited measurement ranges due to complex sensor structures or measurement methods. To extend the measurement range of sensors, a Michelson interferometer curvature sensor based on a seven-core optical fiber has been proposed. It is composed of a single-mode fiber spliced with a tapered seven-core optical fiber, featuring a simple structure. The tapered region is primarily used for coupling light between cores, which provides the potential for expanding the bending measurement range. The proposed sensor has the characteristics of a large measurement range and insensitivity to temperature, and is expected to be effective in scenarios requiring large curvature monitoring.

First, the end faces of the single-mode fiber and the seven-core fiber are polished flat. Then, the cores are spliced using a fusion splicer. Finally, the spliced fiber is placed into a CO₂ laser splicer. The transition zone length, waist zone length, and taper diameter are manually set, and the seven-core fiber is subjected to fused tapering using the CO₂ laser. After tapering, when light from the single-mode fiber reaches the taper region of the seven-core fiber, due to the reduction in the diameter of the central core, part of the light couples into the outer cores and cladding. After traveling a certain distance, the light reaches the end face of the seven-core fiber and is reflected back into the taper region due to Fresnel reflection, forming a Michelson interferometer. When the fiber bends, the inner cores are in a compressed state while the outer cores are in a stretched state, causing a change in the optical path length and resulting in a shift in the interference wavelength. Thus, curvature sensing can be achieved by monitoring the shift in the interference wavelength.

A simulation model is established using Rsoft to model the electric field distribution under taper diameters of 60, 50, and 40 μm (Fig. 3). It is observed that as the taper diameter decreases, the intensity of the light field of the outer core gradually increases. Therefore, it is inferred that the sensor has a better extinction ratio when the diameter is 40 μm. Samples with taper diameters of 60, 50, and 40 μm are fabricated, and their reflection spectra are obtained (Fig. 4). When the taper diameter is 40 μm, the interference spectrum had smoother spectral lines and a higher extinction ratio, which are consistent with the simulation analysis. Therefore, the sample with a 40 μm taper diameter is chosen for the experiments. Curvature experiments are conducted on samples with a seven-core fiber length of 15.6 cm, and the measurable curvature range is 0?11.492 m^-1. Within the linear curvature range, the sensitivity is -1.152 nm/m^-1, and the linearity is 0.99 (Fig. 7). Additionally, repeatability tests are performed on the samples (Fig. 8), and the sensor exhibits good repeatability. Experiments on samples with different lengths of seven-core fibers are also conducted (Fig. 9). Within the linear curvature range, the maximum sensitivity of the sensor is -1.683 nm/m^-1. Temperature experiments show that the sensor sensitivity to environmental temperature changes is only -8.64 pm/℃, while the curvature sensitivity is approximately 194 times that of temperature sensitivity, indicating that the sensor is insensitive to temperature.

We design a Michelson interferometer curvature sensor based on a seven-core optical fiber, constructed from splicing a single-mode fiber with a tapered seven-core fiber. The taper region is primarily used for core-to-core light coupling, which provides the possibility of expanding the bending measurement range. Experimental results show that the sensor has a curvature measurement range of 0?11.492 m^-1, with a maximum sensitivity of -1.683 nm/m^-1, and its sensitivity to environmental temperature changes is only in the pm/℃ range. This provides a solution to the problems of limited linear measurement range and cross-sensitivity to bending and temperature found in existing interferometric curvature sensors.

Existing signal detection methods for optical orthogonal frequency division multiplexing (O-OFDM) systems often rely on detailed channel state parameters. However, channel estimation errors prevent traditional algorithms from delivering accurate results. This challenge is particularly pronounced in optical wireless communication (OWC) systems, where atmospheric turbulence’s time-varying and stochastic nature exacerbates channel estimation difficulties and severely reduces system bit error rate (BER) performance. In addition, most deep learning–based channel estimation models neglect the dynamic characteristics of atmospheric turbulence channels, which limits their practical applicability. To address these limitations, we propose a temporal convolutional channel estimation model optimized with external attention (TCN-EA). The proposed model, which is designed to effectively capture time-varying channel characteristics, improves the OWC system’s mean squared error (MSE) and BER performance, while reducing the computational complexity.

To achieve high-precision channel estimation, block pilots are first inserted into the transmitted O-OFDM frames. The received signals at the pilot positions are then extracted, and operations such as separating the real and imaginary components and one-dimensional data restructuring are performed to generate sequence data suitable for model input. The least-squares method estimates the channel at pilot positions and produces labels for network training. The sequence data and corresponding labels are processed using sliding window operations and batching before being input into the TCN-EA network. The TCN employs dilated causal convolution to progressively extract time?frequency features from the input data, providing preliminary estimates. A lightweight external attention mechanism further enhances the model’s ability to focus on key information in the input data, which optimizes feature extraction. Finally, a linear output layer maps the processed features to the dimensions of the channel estimation results, thereby generating the final estimation output.

We comprehensively compared the performance of the proposed TCN-EA model with that of the basic TCN model and two traditional channel estimation methods using BER and MSE metrics. The estimation performances of the four methods were assessed under weak turbulence conditions (Fig. 5). The results demonstrate that the TCN-EA model achieves an order of magnitude improvement in the MSE performance compared with the traditional MMSE and the basic TCN model. In addition, the BER performance of the TCN-EA closely resembles that of an ideal channel. The effect of varying the number of pilots on the estimation performance was then investigated (Fig. 6). It is observed that the TCN-EA model’s performance remains nearly unaffected by the number of pilots, achieving superior results even with fewer pilots, unlike basic TCN and traditional estimation methods, which are more sensitive to the number of pilots, with their performance improving as the number of pilots increased. The generalization performance of the models was further examined under weak, moderate, and strong turbulence conditions (Fig. 7). Under weak or moderate turbulence, the TCN-EA model exhibits excellent performance in terms of both the MSE and the BER. Under strong turbulence, the BER performance (1×10^-3) of TCN-EA degrades by approximately 10 dB compared to weak turbulence; however, it still exceeded the performance of both MMSE and basic TCN. Practical experiments (Figs. 9?10) revealed that compared with TCN, the constellation diagram clustering points after equalization by TCN-EA are more concentrated and exhibit fewer surrounding scatter points. This clustering effect resulted in improved BER performance, which further substantiates the conclusions of the simulations. Finally, complexity analysis (Table 4) indicated that TCN-EA’s instantiated multiplication count increased by less than 0.4% compared to the basic TCN, but decreased by 88.5% compared to the MMSE.

In this study, we address the challenges of low accuracy and high computational complexity in existing channel estimation methods for O-OFDM systems by proposing a TCN-EA model. The simulation and experimental results demonstrate that TCN-EA effectively captures the channel’s time?frequency characteristics, enabling accurate estimation of channel parameters. The model exhibits robustness and generalization ability across varying numbers of pilots and atmospheric turbulence levels. In addition, TCN-EA’s lower complexity substantially enhances the training efficiency, reducing the overall resource consumption, and improving its practicality for real-world applications.

Thulium-doped fiber lasers (TDFLs) have undergone rapid development in recent years owing to their widespread use in medical treatment, laser radar, laser remote sensing, and military applications. The highest power achieved by TDFLs is in the kilowatt level; however, thermal effects limit their further increase in power. To overcome this challenge, large-mode-area fibers have been proposed. Recently, our group proposed a novel type of Tm³⁺-doped heterogeneous helical cladding fiber with an inner isolation ring (HHCRF) for large-mode-area operation, and the corresponding single mode core diameter is 60 μm. To maintain the single-mode waveguide characteristics of the HHCRF under high-power operating conditions, the effect of temperature on the refractive index should be considered when designing fiber parameters such that the designed fiber parameters are adaptable to high temperatures. Therefore, we herein present relevant design methods that are conducive to promoting the further development of related studies.

In this study, we investigate the three-dimensional laser power and temperature distributions of a novel heterogeneous helical cladding large-mode field fiber under dual-end pumping conditions. We obtain the three-dimensional distribution of refractive-index changes in the fiber and calculate the temperature adaptability of the optical fiber. The specific steps are as follows: First, without considering temperature variables, the fundamental-mode transmission conditions of the fiber were obtained using the COMSOL software. The initial structural parameters of the fiber were obtained, and a theoretical model of the fiber laser amplifier was established to obtain the distribution characteristics of the optical field and temperature field inside the fiber. Subsequently, the thermally induced refractive index change was calculated. Based on the new refractive-index distribution of the optical fibers, the single-mode transmission characteristics of the optical fibers were verified. If the single-mode transmission condition cannot be satisfied at this time, then the initial structural parameters of the fiber are changed and the procedure is repeated from the first step shown in Fig. 3. If the single-mode transmission condition is satisfied, then the fundamental and higher-order mode losses of the fiber under this condition can be obtained. However, the results obtained from the first round of calculations are unstable. This step must be repeated until the mode loss is relatively small compared with the mode loss obtained from the previous round of calculations. This result is assumed to reflect a stable operating state, and suitable fiber structure parameters can be obtained under this high-power operating condition.

In the calculations, bidirectional pumping was adopted, where a pump power of 100 W in the forward and backward directions and a seed optical power of 10 W were utilized. Water was used for cooling. When the fiber length L is set to 4 m, the signal-light output power is similar to the maximum value; thus, the length fiber was set to 4 m. The obtained signal-light output power is 75.02 W. The three-dimensional distribution of temperature inside the optical fiber and the thermally induced refractive index changes are shown in Figs. 7 and 8, respectively. The highest temperature T inside the optical fiber is 172 ℃, and the thermally induced refractive index change Δn is 0.001305. The axial loss distributions of the optical fibers under stable operating conditions are shown in Fig. 9. After five rounds of calculations, as shown in the flowchart in Fig. 3, the fiber appeared to be in a stable operating state. The rate of change in the loss values of the fundamental and higher-order modes in each round compared with that in the previous round is shown in Fig. 11. In the fifth round, the rate of change in the basic mode loss is -6.26959^-5, whereas that in the high-order mode loss is -3.45006^-5, thus indicating that the fiber has entered a stable operating state. At this point, the fundamental-mode loss is 0.159 dB/m and the higher-order mode loss is 6.550 dB/m. The fiber possesses single-mode transmission capability.

This study analyzes the effect of thermally induced refractive-index changes on single-mode transmission characteristics under high-power operation conditions based on a new type of thulium-doped heterogeneous helical cladding (HHC) large-mode area and single-mode fiber. A theoretical solution model was established to provide a solution for investigating the temperature adaptability of large-mode-field single-mode fibers. Using this method, optimized design parameters for a new type of HHC large-mode-field fiber were obtained: the cladding refractive index n₃ is 1.4380, the core refractive index n₀ is 1.4388, the central angle θ′ is 12°, and the isolation ring thickness d is 4 μm. This ensures that the HHC fiber can maintain single-mode operation even at a pump power of 100?300 W. The results of this study provide a theoretical reference for the design of large-mode-field single-mode optical fibers.

The frequency noise and linewidth of a single-frequency continuous-wave semiconductor laser in a coherent detection system are crucial for evaluating the basic performance of a system. The linewidth can be measured directly using delay self-heterodyne interferometers with short or ultralong optical fibers. These measurements show that only the upper limitation capability of coherent detection systems can be directly evaluated from the linewidth or frequency noise of the laser. However, this method lacks detailed information about the entire system, such as the signal-to-noise ratio (SNR) under different detection conditions. Although the linewidth and frequency noise mentioned above can represent the performance of a coherent detection system to some extent, the frequency noise curve of a laser contains more information, including 1/f noise in the low-frequency area, corner frequency, and white noise. According to the Wiener?Khintchine theorem, the autocorrelation function of a coherent detection system can be calculated from the frequency-noise curve, and the SNR can be obtained using the Fourier transform of the autocorrelation function. However, reconstructing coherent detection spectra from frequency-noise curves is difficult. The unconventional frequency noise curves and large amount of computation make it difficult and time consuming to analyze the evolution of the SNR in coherent detection systems from coherent to incoherent.

In this paper, we propose a new method for calculating the SNR of a coherent detection system from the frequency-noise curve of a laser in a coherent detection system. In this method, logarithmic sampling and a fast Fourier transform are adopted instead of regular sampling with even spacing when the SNR is calculated to quantitatively characterize the evolution of the entire system from coherent to incoherent. By analyzing the autocorrelation function, Eq. (1), we observe that the intensity of the sinc function decreases with frequency, so the main contribution to the integral result comes from the main lobe in the low-frequency domain, while the contribution from the side lobes is minimal. Thus, when calculating the autocorrelation function of the coherent detection system, the sampling interval for the frequency noise curve in the frequency domain is no longer constant but varies logarithmically, with denser sampling in the low-frequency range and sparser sampling in the high-frequency range. In addition, the data of the frequency-noise curve can be directly obtained from experimental measurements without fitting. This improvement makes the calculation of the autocorrelation function of the system quick and accurate, and the coherent detection spectrum can be reconstructed using a fast Fourier transform. We can extract the SNR based on the calculated spectrum, such that the evolution of the coherent detection system can be characterized quantitatively by the SNR values under different detection distances or lasers with different coherent characteristics.

We compare the theoretical values of the autocorrelation function for white noise with those obtained by the proposed method. Figure 3 shows that the results of the analytical solution (dotted line) agree the results (straight line) calculated by the logarithmic sampling method for τ/τD less than 10. The integral results remain strictly equal when τ=τD. Although there is considerable noise (owing to undersampling by logarithmic sampling) for τ/τD greater than 10, the trace level is consistent with that of the analytic solution. Fortunately, the noisy result due to undersampling is located in the high-frequency domain of the fast Fourier transform, far from the region where the carrier frequency exists, as shown in Figs. 4 and 6. Therefore, the SNR can be extracted from the spectrum of a coherent detection system. In the experiment, two different frequency-noise curves of the lasers (DFB-LD1 and DFB-LD2) are used to verify the proposed method. Figure 5 demonstrates that the line shape and SNR results between experimental data and calculated values closely match, with SNR differences of 0.84 dB, 0.39 dB, 0.39 dB, 0.48 dB, and 0.08 dB for optical fiber lengths of 20, 50, 100, 200, and 300 m, respectively. Finally, the evolution curves of the SNR versus the detection distances are presented in Fig. 7 according to the frequency noise curves of DFB-LD1, DFB-LD2, and white noise.

In this study, we propose a new method for calculating the SNR evolution of coherent detection systems from coherent to incoherent based on frequency?noise curves. For any arbitrary frequency noise curve of lasers, this method can quickly and accurately reconstruct the spectral information from the coherent detection signal based on logarithmic sampling and fast Fourier transform. In addition, the linewidth and frequency noise of the entire coherent detection system can be obtained using this method, and the SNRs and line shapes versus detection distances can also be obtained from the measured frequency noise curve to reveal the coherence characteristics more directly, dynamically, and comprehensively. Alternatively, the proposed method dynamically characterizes a stable free-running laser and can be applied to frequency-modulated continuous wave (FMCW) optical sources and optical phase-locked loops (OPLL) to characterize dynamic coherences or evaluate the effects of optical phase-locked loops based on their frequency noise curves if they can be measured. By comparing the results of the coherence characteristics of a laser under free-running, modulation, and phase-locked states, we can establish the relationship between the signal-to-noise ratio and the detection distance, which can help us set the optimum driving parameters for the semiconductor laser in the coherent detection system to achieve the best coherent detection performance.

Double-polarization interferometry (DPI) is an emerging technique for the quantitative study of molecular interactions, offering benefits such as high sensitivity, label-free operation, and the ability to acquire real-time data on molecular recognition dynamics and structures. However, during the acquisition of interferometric images, various interferences, such as speckle noise, may occur. DPI relies on phase shifts in interference fringes to calculate key parameters, including intermolecular forces. Therefore, it is essential to denoise the acquired complex interferometric images to minimize noise interference during phase shift extraction. The interferometric images obtained through DPI typically feature pronounced bright and dark fringes, along with clear boundary information. However, traditional denoising methods often result in excessive filtering, leading to blurred boundaries and loss of critical information. Thus, the development of a denoising algorithm tailored for complex interference fringes is crucial for improving the quality of subsequent analyses in DPI and its practical applications.

We propose a denoising algorithm that combines sine-cosine decomposition with the discrete cosine transform (DCT) for processing complex DPI interference fringe images. The algorithm first decomposes the interference image into sine and cosine components, generating the corresponding sine and cosine maps. By exploiting the energy concentration properties of DCT in the frequency domain, noise components in the maps are effectively removed. The denoised image is then restored through an arctangent operation. Comparative experiments are conducted on both simulated and real interference fringe datasets. Various denoising techniques are evaluated, including mean filtering, median filtering, wavelet-based frequency domain denoising, isotropic and anisotropic methods, the fast nonlocal means (FNLM) and weighted nuclear norm minimization (WNNM) algorithms, and N2N training strategies. These methods are compared with the proposed algorithm to assess the performance of each and to validate the effectiveness of the proposed approach. Additionally, phase shift curves are extracted and compared before and after denoising to further demonstrate the reliability of the proposed algorithm.

We use MATLAB software to generate simulated interferogram images, and the simulation results (Fig. 9) demonstrate the superior performance of the proposed algorithm. After processing, the images exhibit higher contrast and finer textures, with edge details fully preserved. Both the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics (Table 1) consistently outperform those of other algorithms. In contrast, traditional filtering methods lack sufficient denoising capability, resulting in blurred edge textures. The results from wavelet, isotropic, and anisotropic algorithms are less satisfactory, as some noise remains in the images. Although the FNLM and WNNM algorithms display some competitiveness, their denoising effects and edge clarity still fall short of those of the proposed algorithm. Furthermore, although the N2N algorithm outperforms the proposed algorithm in terms of PSNR, its SSIM value is lower, and its denoising effect is not significantly better. In experiments with real interferogram images (Fig. 10), the proposed algorithm continues to perform the best, with previously blurred areas becoming clearer and providing more reliable data for subsequent analysis and processing. In contrast, traditional filtering methods perform poorly, leaving significant noise in the images. The results of wavelet, isotropic, and anisotropic filtering are suboptimal, producing blurred edge textures. While FNLM and WNNM algorithms demonstrate relatively good denoising effects, with WNNM slightly outperforming the proposed algorithm in SSIM, its PSNR value is 0.9533 dB lower (Table 2), and both algorithms are inferior to the proposed method in preserving edge details. In real image denoising experiments, the performance of the N2N training strategy does not match that of the simulation experiments. Although its denoising level surpasses other comparison algorithms and preserves edge textures well, some noise remains. Finally, by applying the proposed algorithm to denoise a set of interferogram images, we compare the phase shift curves before and after denoising (Fig. 11). The results confirm that the proposed algorithm effectively eliminates abnormal jumps in the phase shift curve, further validating its reliability.

In DPI, interferometric images often contain complex structures and substantial noise, making denoising a critical step in accurately extracting phase shifts. This paper presents a novel algorithm that combines sine-cosine decomposition with the discrete cosine transform to achieve high-precision denoising of interferogram images. Comparative experiments demonstrate that the proposed algorithm significantly reduces noise levels while preserving edge and texture details to the greatest extent possible, effectively avoiding edge blurring due to over-filtering. The evaluation of different denoising methods indicates that the proposed algorithm achieves higher PSNR and SSIM values, signifying effective noise reduction with minimal loss of information. The processed interferometric image set successfully eliminates abnormal jumps in the phase shift curve, enhancing the accuracy and reliability of phase shift extraction. This contributes to improving the quality of analyses and applications in DPI.

Laser through-window imaging technology, an advanced detection method, can effectively penetrate window glass and visualize indoor targets behind the window, providing many application prospects. In antiterrorism and stability maintenance scenarios, a through-window scope enables the capture of accurate information regarding the number and posture of terrorists outside the window. In traffic monitoring applications, this technology enables the assessment of a driver’s status without requiring the driver to exit the vehicle, thereby improving traffic management efficiency. However, the practical application of laser through-window imaging technology faces several challenges. Image quality and accurate capture of target information behind windows are significantly affected by factors such as natural illumination, object occlusion, and strong reflections from the window glass. Accurately detecting human targets and identifying their poses in complex environments is highly challenging. Conventional image processing techniques often cannot achieve accurate and efficient detection results when faced with disruptions such as changes in illumination or occlusion. Addressing these challenges requires the development of more robust object detection and attitude recognition algorithms that can be effectively implemented on edge computing platforms to meet real-time requirements. This study is highly significant, with the potential to substantially enhance fields such as antiterrorism measures, security operations, military reconnaissance activities, and traffic management.

Currently, laser through-window imaging data are not publicly accessible. Therefore, a new dataset was constructed using a laser range-gating imaging system that covers two types of scenes: natural and man-made. The natural scene includes various simulated human postures for data collection, whereas the man-made scene incorporates diverse types of glass, through-window distances, lighting conditions, and occlusions to enhance data diversity. Existing algorithms for human postural recognition in low-quality laser through-window images typically exhibit suboptimal accuracy, which is characterized by significant missed and false detection. Thus, this study used YOLOv8n-Pose as the base model with a targeted optimization design to address these problems. A novel convolution module was developed to improve the feature extraction ability in low-quality image scenarios with laser through-windows, while cross-level association and a model pruning method were used to reconstruct the feature fusion network. This approach aims to reduce the model size and improve the recognition of small target human poses. Additionally, an enhanced detection integration network that combined image denoising and postural recognition tasks enabled end-to-end integrated training, further enhancing the model detection performance. Finally, a human posture recognition algorithm was implemented by deploying the model on the Jetson NX mobile development platform, creating a fully functional airborne laser through-window imaging human posture recognition system.

This study compared the performance of Faster R-CNN, Alphapose, Openpose, HigherHRNet, YOLOv5s6-pose, and YOLOv8n-Pose algorithms for human pose recognition (Table 2). The results indicate that the YOLOv8n-Pose model outperforms Faster R-CNN, Openpose, and HigherHRNet. Alphapose and YOLOv5s6-pose exhibit slightly better performance indicators than YOLOv8n-Pose. However, they significantly lag behind YOLOv8n-Pose in terms of inference speed and model size. Nevertheless, the proposed YOLO-TCpose algorithm performs exceptionally well across various performance indicators. Additional experiments were conducted using the Openpose, Alphapose, and YOLOv8n-Pose algorithms in artificial and natural scenes to assess the effectiveness of the YOLO-TCpose algorithm. In artificial scenes (Fig. 6), comparative experiments involving single and multiple people with occlusion demonstrate that YOLO-TCpose outperforms Openpose and Alphapose by achieving accurate key point positioning and significantly reducing missed detections during multiperson pose recognition. Notably, YOLO-TCpose exhibits significant advantages, particularly in scenarios involving multiperson occlusion. In natural scenes (Fig. 7), the experimental results indicate that during posture recognition tasks such as crawling during the day, standing at night, or squatting on rainy day; YOLO-TCpose accurately detects human target along with their corresponding key points, outperforming other algorithms by a significant margin. Finally, YOLO-TCpose exhibits superior detection accuracy, stability, and adaptability in various environments compared to current mainstream algorithms.

This study introduces YOLO-TCpose, an efficient and lightweight human posture recognition algorithm designed for detecting human poses in low-quality laser through-window images. To address the limitations of traditional convolution, a novel convolutional module was developed to improve feature extraction capabilities. Additionally, the feature fusion network was restructured by eliminating large target detection layers and incorporating small target detection layers. This adjustment facilitates the effective fusion of shallow and deep information through cross-layer connections, thereby improving the recognition performance for small targets. By incorporating an improved ADNet denoising algorithm, an integrated network for image enhancement and pose recognition was developed, which significantly improves the detection accuracy. The experimental results demonstrate that YOLO-TCpose achieves improvements of 19.3 and 26.6 percentage points in the precision and recall rate, respectively, for object detection. The mean average precision (mAP) at 0.5 and mAP at 0.5:0.95 for keypoint detection are enhanced by 16.0 and 10.1 percentage points, respectively. In addition, the inference speed is increased by 5.1 ms, and the model size is reduced by 1.69 MB. Furthermore, algorithms for recognizing three postures—standing, squatting, and crawling—were developed, and the model was successfully deployed on the Jetson NX mobile development platform, establishing a fully functional airborne laser through-window imaging human posture recognition system.

Solid-state lasers are expected to replace CO₂ lasers as the driving source of a new generation of laser-produced plasma (LPP) light sources for extreme ultraviolet (EUV) lithography, owing to their compact size, high wall-plug efficiency, and high power output potential. However, the plasma density and optical depth of 1-μm laser-produced plasma are larger than those of 10-μm CO₂ laser, leading to low energy conversion efficiency (CE) from driving laser to in-band radiation with a center wavelength of 13.5 nm and bandwidth of 2%. Recent research illustrates that the CE of 1-μm laser-produced Sn plasma is expected to meet the engineering requirement of the LPP-EUV source under systematic optimization. In this work, an experimental platform of the LPP-EUV source driven by a 1-μm solid-state laser is established and the EUV radiation characteristics of 1-μm laser-induced solid Sn target plasma are experimentally studied. Under the laser peak power density of 8.24×10¹⁰ W/cm², a maximum CE of 3.42% is achieved, which reaches an advanced level in the world. We hope that the established platform and related research results can provide technical support for domestic research and development of solid-state laser-driven plasma light sources for EUV lithography and inspection.

An experimental platform of the LPP-EUV source driven by a 1-μm solid-state laser is established first, consisting of a vacuum chamber, a 1-μm Nd∶YAG nanosecond pulsed laser, a digital delay generator, an in-band energy meter, and a flat-field spectrometer. An energy meter and a spectrometer are used for in-band EUV radiation energy measurements and 7?23 nm EUV spectra, respectively. To accurately determine the in-band energy, the calibrated sensitivity of the energy meter is calculated by using the EUV spectrum of Sn plasma and the responsivity at 12.5?14.5 nm calibrated by the metrology beamline in the National Synchrotron Radiation Laboratory (NSRL). The wavelength of the spectrometer was calibrated using the absorption edge of Si and the spectral lines of the Sn ion. The total efficiency of the spectrometer system is calculated using the reflectance of the Au mirror, diffraction efficiency of the grating, and quantum efficiency of the X-ray charge coupled device (CCD). Then, the EUV radiation characteristics of 1-μm laser-induced solid Sn target plasma are studied by the measurement of CEs and EUV spectra of Sn plasma under different laser peak intensities, and values of spectral purity (SP) calculated from EUV spectra.

The EUV radiation at 7-23 nm is unresolved transition arrays (UTAs) centered in around 13.5 nm, emitting from multiply excited states of multiply charged Sn ions in the plasma. As the laser peak power density increases, the EUV radiation intensity below 15 nm gradually increases, and that above 15 nm gradually weakens (Fig. 4). The spectral peak position of the UTA moves from the left to the right of the operating center wavelength of the 13.5 nm light source for EUV lithography. Besides, the UTA appears to sag around 13.5 nm, which is self-absorption phenomenon, because 1-μm laser-induced solid Sn target plasma has a large optical depth. As the laser peak power density increases gradually, the SP and CE first increase and then decrease (Fig. 5). The CE reaches a maximum value of 3.42% at the laser peak power density of 8.24×10¹⁰ W/cm², and the corresponding SP is 7.04%, which is close to the CE value of twice. Before the CE reaches its maximum, the increase in the laser peak power density has a significant effect on the SP and CE. When the peak power density is 8.24×10¹⁰ W/cm², the SP is three times higher than that of 9.97×10⁹ W/cm², and the CE is five times higher. When the CE reaches its maximum, the SP and CE decrease gradually with an increase in the peak power density. The above results illustrate that the SP and CE are sensitive to variations in the laser peak power density, and it is necessary to optimize the laser peak power density on the Sn target during the development of the LPP-EUV source. The study of the Sn plasma EUV spectrum SP is also very important, as it can further help estimate the upper limit of the CE and provide relevant information about the out-of-band radiation.

In this work, the 1-μm solid-state laser Sn plasma EUV source is studied. An experimental platform of the LPP-EUV source driven by a 1-μm solid-state laser is established. The responsivity of the in-band energy meter and efficiency curve of the flat-field spectrometer are calibrated. Subsequently, the 7?23 nm EUV spectra of the laser-induced solid Sn target plasma are measured under different laser peak power densities. The dependence of the EUV spectrum of the Sn plasma on the laser peak power density and its mechanism are analyzed. The dependency of conversion efficiency and spectral purity on laser peak power density is studied. The results illustrate that the SP and CE are sensitive to the laser peak power density, and it is necessary to finely optimize the laser peak power density on the Sn target during the development of the LPP-EUV source. Under the laser peak power density of 8.24×10¹⁰ W/cm², a maximum CE of 3.42% is achieved, which reaches an advanced level in the world. The established platform and related research results are important for the domestic independent development of EUV lithography and its key devices and technologies.

The resonant micro-optic gyroscope (RMOG) represents a significant advancement in the miniaturization and integration of high-precision gyroscopes. In RMOGs, the optical waveguide ring resonator constitutes the core component. The resonance-enhanced Sagnac effect provides the theoretical foundation for the miniaturization of resonant optical gyroscopes. The advent of integrated optics and micromachining technologies enables the successful fabrication of various low-loss and high-finesse resonant cavities. However, in addition to backscattering and polarization noise, the optical Kerr effect emerges as a significant source of noise that limits the accuracy of RMOGs. In this study, a method for reducing optical Kerr noise in RMOGs is proposed, and the simulation results are validated using experimental data.

This paper presents a comparative and analytical examination of the optical Kerr effect-induced error coefficients in reflective and transmissive waveguide ring resonators (WRRs). The effects of modulation parameters on optical Kerr effect-induced errors are investigated, and the optical Kerr error coefficient in RMOGs is reduced by optimizing the modulation coefficient. Subsequently, an RMOG system comprising a transmissive silica WRR with a diameter of 5.96 cm and a finesse of 118 is constructed, which serves as the rotation-rate sensing element. The optical Kerr error coefficient and its relationship with the modulation parameters are tested. Subsequently, an RMOG system with an optical-power feedback loop is constructed to improve the stability of the optical power input to the WRR.

The optical Kerr error coefficient is calculated to be 4.7[(°)/h]/μW . After analysis and testing, the optical Kerr error coefficient and its relationship with the modulation parameters are shown to be consistent with theoretical expectations. Following the optimization of the modulation frequencies of the clockwise and counterclockwise beams at 2.6 MHz and 2.7 MHz, respectively, the optical Kerr error coefficient reduces to 1.5[(°)/h]/μW . Finally, an RMOG system with an optical-power feedback loop is constructed to improve the stability of the light intensity incident on the WRR. The measured results show that the optical-power fluctuation reduces from 1.42% prior to the implementation of the power feedback loop to 1.86×10^-5 following its implementation. This reduction in the optical-power fluctuation corresponds to a reduction in the peak-to-peak fluctuation of the gyroscope output caused by the optical Kerr effect from 52.6(°)/h to 0.015(°)/h in the RMOG. The minimum corresponding bias stability is 0.0015(°)/h. The aforementioned results show that the optical Kerr effect in the RMOG is effectively suppressed.

This study shows that a transmissive WRR in an undercoupled state can exhibit a low optical Kerr error coefficient. Additionally, the Kerr error coefficient can be further reduced by optimizing the modulation parameters of the system. Finally, using an optical-power feedback technique based on second-harmonic demodulation can significantly enhance the stability of the optical power input to the WRR. The aforementioned measures allow for the effective suppression of optical Kerr effect-induced errors in RMOGs.

The primary goal of this study is to develop a high-power, low-noise, single-frequency fiber laser system for third-generation ground-based gravitational wave detection. These detectors require continuous, high-power lasers with extremely low-intensity noise, as gravitational wave signals are exceedingly faint and susceptible to interference from laser noise. This study introduces a 1550 nm single-frequency fiber laser system capable of outputting 20 W power with low relative intensity noise (RIN) over the critical frequency range of 10 Hz to 10 kHz. The objective is to establish a reliable light source for gravitational wave detection systems and provide a solid foundation for future advancements in gravitational wave astronomy.

A master oscillator power amplifier (MOPA) configuration is used to amplify an ultralow noise fiber laser seed source. The laser system consists of a three-stage, all-fiber amplification setup that sequentially amplifies a 1550 nm seed laser. In the first stage, a polarization-maintaining erbium-ytterbium-doped fiber (EYDF) boosts initial power by several watts. The second stage, utilizing a larger fiber core, further increases power while managing nonlinear effects. The final stage employs a large mode area (LMA) fiber to achieve a high output power of up to 20 W, minimizing nonlinear effects such as stimulated Brillouin scattering (SBS) and stimulated Raman scattering (SRS). Several noise-reduction techniques are incorporated to achieve stable, low-noise operation. Thermal management, essential due to the heat generated during amplification, is achieved by mounting gain fibers in thermally conductive grooves within water-cooled aluminum plates. A high-precision temperature control system maintains fiber temperature stability within ±0.01 ℃, ensuring uniform heat dissipation, protecting the system, and stabilizing power output. To further reduce noise from sources like mechanical vibrations, air currents, and electromagnetic interference, the laser system is housed in an acrylic wind shield with electromagnetic shielding. A self-developed low-noise photodetector and high-precision voltage reference source are integrated into an optical-electrical feedback control loop. The photodetector monitors laser intensity noise, allowing the feedback system to dynamically adjust the pump current based on real-time signals, thereby minimizing laser intensity noise in the critical frequency range for gravitational wave detection.

The results show that the designed single frequency fiber laser system can meet the requirements for third-generation ground-based gravitational wave detection. The system achieves an output power of 20 W with a highly stable intensity profile. When the output power of fiber laser system is 20 W, the RIN at 10 Hz and 2 kHz are approximately 10^-5/Hz^1/2 and below 4×10^-8/Hz^1/2, respectively. Laser intensity noise is significantly reduced, particularly in the critical 10 Hz to 10 kHz frequency range. The system noise performance is enhanced by the combination of environmental noise isolation and the implementation of a self-developed low-noise photodetector and voltage reference source. The photodetector operates with a noise level as low as 2×10^-9/Hz^1/2 over the 10 Hz to 10 kHz range, ensuring that the system feedback loop can effectively suppress intensity noise without being influenced by the detector electronic noise. The voltage reference source is designed with multi-stage filtering and electromagnetic shielding, which provides a stable baseline for the feedback system and further improves the laser noise suppression capability. The LMA gain fiber in the main amplifier plays a critical role in suppressing nonlinear effects that typically arise at high power levels. The research also highlights the importance of careful thermal management in high-power fiber lasers. The temperature control system ensures that the heat generated during amplification is efficiently dissipated, preventing thermal accumulation that destabilizes the system or damages the gain fiber. This approach ensures stable laser operation over extended periods, which is a key requirement for gravitational wave detection.

This study successfully develops a high-power, low-noise, single-frequency fiber laser system optimized for ground-based gravitational wave detection. The system achieves 20 W output power with exceptionally low-intensity noise across the frequency range of 10 Hz to 10 kHz, making it well-suited for gravitational wave interferometers. The integration of a low-noise photodetector, high-precision voltage reference source, and optical-electrical feedback control effectively suppresses noise, meeting the stringent requirements of third-generation gravitational wave detectors. The findings of this study lay a crucial foundation for future advancements in gravitational wave detection technology. The high power and low-noise performance of the laser system ensures its capability to measure tiny space time distortions caused by gravitational waves, significantly enhancing gravitational wave detector sensitivity. Future work will focus on optimizing the system further by improving the feedback loop gain and bandwidth, and enhancing resistance to environmental noise. With these improvements, the laser system can provide robust support for high-precision gravitational wave detection.

Laser-sustained plasma (LSP) sources have applications in wafer defect detection, near-field imaging, spectroscopic analysis, and endoscopy. A smaller-size and higher-temperature plasma can be generated through LSP to result in high-brightness, incoherent broadband emission. With the development of high-power fiber lasers in the mid-infrared, fiber lasers are widely used in LSP sources. Fiber lasers with excellent beam quality contribute to a lower LSP threshold and thereby further promote the application of LSP sources. Source stability is crucial in LSP source applications. However, LSP is characterized by spatial and temporal instabilities. The results of a study conducted by Yakimov et al. show that LSP first exhibits spatial and temporal instabilities when the f-number of the focusing objective increases to certain values. The spatial instability of the LSP can be avoided by reducing the f-number of the focusing objective. The temporal instability of the LSP is driven by the convective plume pulsation of the plasma. The inhibition of the convective plume pulsation of the plasma is key to solving the temporal instability of the LSP source.

In our study, we use an orthogonal laser to sustain the plasma. The plasma size and temperature of orthogonal LSP are shown in Fig. 4, and orthogonal LSPs can realize plasmas with smaller size and higher temperatures. When the laser power increases, the frequency of the convective plume pulsation of the plasma gradually decreases. When the laser power increases to a specific point, the convective plume pulsation of the plasma suddenly disappears.

This phenomenon is similar to the laminar flame combustion instability during fuel combustion processes. In flame combustion, there are three types of combustion: steady, transition, and pulsation combustion. The research in Refs. [24-25] shows that the laminar flame combustion gradually switches from pulsation combustion to transitional combustion and steady combustion as the Froude number decreases. In LSP, as the Froude number decreases, there should also be a switch between steady convective plume and convective plume pulsation. The Froude number, given by Fr=v2/gr, where v is the velocity of the object motion, g is the acceleration of gravity, and r is the characteristic length of the object, is a dimensionless parameter in hydrodynamics that characterizes the relative magnitudes of the inertial force and the gravitational force of a fluid. The Froude number is inversely proportional to the diameter of the plasma convection plume. An increasing laser power leads to an enlarged diameter of the convective plume. Therefore, the Froude number decreases as the laser power increases, and it can be assumed that the convective plume pulsation of the plasma disappears when the Froude number decreases below the critical point for the steady convective plume. Determining the critical Froude number for the steady convective plume is the key to enhancing LSP temporal stability. According to the Froude number formula, increasing the velocity of the object motion and decreasing the characteristic length of the object increase the Froude number. A high Froude number helps LSP switch from convective plume pulsation to a steady convective plume. Orthogonal laser sustains a hotter plasma, which increases the velocity of the plasma convection plume. Therefore, orthogonal laser-sustained plasma reduces the Froude number, which overcomes the temporal instability of the LSP source.

In this study, a plasma with a smaller size and higher temperature is realized using orthogonal laser-sustained plasma. In the orthogonal laser-sustained plasma, the convective plume pulsation frequency of the plasma gradually decreases and disappears with an increase in the laser power, and the convective plume is converted from a pulsation state to a stable state. A stable plasma convection plume helps improve the time stability of the laser-sustained plasma, which is crucial for the application of laser-sustained plasma light sources. This study is analogous to switching between pulsation combustion and steady combustion in laminar combustion. It is proposed that a reduction in the Froude number is the key to realizing the conversion of a plasma convection plume from a pulsation state to a steady state. The key to reducing the Froude number is to reduce the expansion rate of the convective plume, which can help the plasma convective plume transition from the pulsation state to the steady state. Orthogonal laser-sustained plasma helps increase the plasma temperature and overcome the temporal instability of laser-sustained plasma. However, the critical Froude number of the plasma convective plume in the pulsation and steady states has not been quantitatively described. Therefore, the critical Froude number of the plasma convective plume will be thoroughly investigated in a subsequent study to further clarify the physical connotations of laser-sustained plasma time instability.

In recent years, 0.9 μm pulsed lasers have shown great potential in various fields such as laser medicine, precision machining, remote sensing, and communications. The second harmonic of 0.9 μm pulsed lasers falls within the seawater transmission window (450?490 nm), making them particularly suitable for applications in ocean lidar. Notably, the Fraunhofer H-β absorption line in the solar radiation spectrum has a central wavelength of 486.1 nm, which allows lasers operating at the H-β line wavelength to effectively improve the signal-to-noise ratio and enhance the detection accuracy. Currently, the main methods for generating high-power 0.9 μm pulsed lasers include quasi-three-level transitions in Nd-doped lasers, second harmonic generation in Tm-doped lasers, and optical parametric oscillators (OPOs). In this paper, a 972 nm nanosecond pulsed laser based on a four-mirror ring-cavity KTiOAsO? (KTA) crystal OPO is proposed. This laser addresses the issue of insufficient single-pulse energy in existing 972 nm pulsed lasers and is expected to improve the detection accuracy of spaceborne ocean lidar.

The laser system consists of four parts (Fig.1): seed laser, small slab double-pass pre-amplifiers, multi-stage large slab single-pass main-amplifiers, external cavity frequency doubling, and single resonant OPO. The seed laser is a passively Q-switched NPRO Nd∶YAG end-pumped laser with a repetition frequency of 100 Hz. Solid-state amplifiers increase the seed laser energy. Both the pre-amplifiers and main-amplifiers are designed with laser diode side-pumped Nd∶YAG slab crystals with a doping atomic fraction of 1%. High-power 808 nm laser diode arrays (LDAs) with a pump pulse width of 150 μs are used for pumping. A type-I phase matching LiB₃O₅ (LBO) crystal with a size of 10 mm×10 mm×15 mm, cutting angles of θ=90° and φ=11.3°, and an effective non-linear coefficient of d_eff=0.832 pm/V is used for the second harmonic generation from the 1064 nm laser to the 532 nm laser. The front and back surfaces have anti-reflection (AR) coatings for 1064 nm and 532 nm. The OPO uses a four-mirror ring cavity design with a cavity length of 290 mm, in which two KTA crystals with size of 8 mm×8 mm×10 mm are placed in a walk-off-compensated placement. The KTA crystals are cut at angles of θ=90° and φ=27.2°, with AR coatings for 532, 972, and 1176 nm on the two end surfaces of the crystals.

At a repetition rate of 100 Hz, the NPRO laser produces 80 μJ pulses at a wavelength of 1064 nm. After multi-stage solid-state laser amplifications, the single-pulse energy of the 1064 nm pulsed laser increases to 224 mJ, with a near-field spot beam size of 6.01 mm×6.40 mm exhibiting a Gaussian distribution (Fig. 2). The LBO crystal is used for frequency doubling to produce a 532 nm pulsed laser with a single-pulse energy of 128 mJ (Fig. 3) and a pulse width of 6.2 ns (Fig. 4). After the beam reduction, the spot size is 1.93 mm×2.34 mm (Fig. 5) with a central wavelength of 532.2 nm (Fig. 6). The 532 nm pulsed laser is used as the pump source for the OPO. To prevent damage to the KTA crystal, the single-pulse energy of the 532 nm pump laser is limited to 40 mJ. The threshold pump energy of the OPO is 15 mJ. When the pump energy reaches 40 mJ (2.67 times of the threshold), the maximum single-pulse energy of the 972 nm pulsed laser reaches 10.2 mJ (Fig. 7), with a pump-to-signal conversion efficiency of 25.5%. The corresponding pulse width is 5.9 ns (Fig. 8), the central wavelength is 972.3 nm, the spectral linewidth is 0.19 nm (Fig. 9), and the near-field spot size is 2.89 mm×2.81 mm (Fig. 10).

A passively Q-switched Nd∶YAG NPRO laser with a repetition frequency of 100 Hz generates a 1064 nm pulsed seed source with a single-pulse energy of 80 μJ, which is amplified to 224 mJ by multi-stage solid-state laser amplifiers. A 532 nm second-harmonic pulse with a single-pulse energy of 128 mJ is generated through frequency-doubling with an LBO crystal. Additionally, a 40 mJ 532 nm pulsed laser is used to pump the four-mirror ring cavity OPO containing two KTA crystals, resulting in a 10.2 mJ 972 nm pulsed laser with a pulse width of 5.9 ns, a peak power of 1.73 MW, a central wavelength of 972.3 nm, a linewidth of 0.19 nm, and a pump-to-signal conversion efficiency of 25.5%. The experiment demonstrates that using the 532 nm pulsed laser generated by extra-cavity frequency doubling as the pump source for the OPO is an effective method for obtaining a 972 nm pulsed laser with high single-pulse energy and high repetition frequency. This results provide a reference for high-energy 486 nm pulsed laser output through frequency doubling.

Wavelength spectra in the near-/mid-infrared range, especially near 2 μm, cover the absorption lines of various atmosphere gases—including the main greenhouse gases (GHGs) like CO₂ and_{CH4. As a result, high-energy lasers emitting at these wavelengths have garnered significant attention as light sources for light detection and ranging (Lidar) systems, especially in applications such as GHG detection. However, it remains a challenging task to develop lasers with compact size, high energy, high efficiency, and high robustness, which are demanded by airborne and spaceborne Lidars. Master oscillator power amplifier (MOPA) based on Tm, Ho co-doped materials is one of the most promising laser concepts. Owing to the absorption of Tm, these co-doped materials can be directly pumped by commercial laser diodes emitting at 793 nm and the high reabsorption loss can also be avoided by lowering the Ho doping concentration. Among the host materials, the birefringent crystal LiYF4 (YLF) stands out in high-energy Q-switched laser development owing to its low phonon energy and long upper laser level lifetime when doped with Tm and Ho. Thus, in this paper, we present a side-pumped high-energy MOPA laser amplifier designed for Lidar applications. The amplifier is based on a (Tm,Ho) ∶YLF crystal and operates at 2051 nm with a pulse width in the hundred-nanosecond range.}

In the MOPA system, we employ laser diode (LD) bars as pump sources, which emit light at 793 nm and have a maximum peak pump power of 100 W for each bar, with a pump duration of 1 ms. The active media used are homemade (Tm,Ho) ∶YLF rods doped with Tm (atomic fraction of 5%) and Ho (atomic fraction of 0.5%). Both the LD bars and laser crystal rod are assembled in a self-designed triple side-pumped laser head module, together with conductive-cooling heat sinks and a wedged lens pump light coupling system. In the master oscillator (MO), an 8-shaped ring cavity with four mirrors and a length of 1.7 m is constructed to achieve pulses with a hundred-nanosecond duration, and Q-switching is realized using an acousto-optic modulators (AOM). In the power amplifier (PA), a 3-stage double pass amplification is employed; thus, the maximum required pump energy/peak power in each stage can be reduced. In addition, the laser beam quality is optimized by mounting the crystal rod of secondary amplifier with an orthogonal axis from the other two amplifiers. This is because the a-cut YLF crystal is birefringent along the light propagation direction in the a- and c-axes with different thermo-optical parameters, which results in the laser beam experiencing different values of the thermal lens in these two axes. By placing the second rod with orthogonal axis, the thermal lens difference between the two directions can be compensated.

In the free-running regime, a maximum output energy of 154.2 mJ and slope efficiency of 19.1% are achieved at 1 Hz under a pump energy of 2.15 J, while 94.2 mJ and 12.7% are achieved at 10 Hz. The laser efficiencies at maximum output reach 7.2% and 4.4%, respectively. The output energy increases with the increasing pump energy and decreases with the increasing of the repetition rate. No thermal rollover is observed. In the Q-switched regime, a maximum output energy of 59.5 mJ is obtained at 10 Hz, with a slope efficiency of 6.1%, a laser efficiency of 2.6%, and a free-running/Q-switching conversion ratio of 0.47. The output pulse duration decreases with pump energy and is measured as 133.8 ns at the maximum output energy. After the first stage amplifier, the pulse energy is increased from 58.5 mJ to 18 mJ under 3.52 J input energy and is further increased to 128 mJ and 201 mJ after the second stage amplifier and three stage amplifier, respectively. The amplification rates are 1.53, 1.43, and 1.57 for the first stage amplifier, second stage amplifier and three stage amplifier , respectively. A total amplification rate of 3.43 is achieved using this 3-stage double-pass PA. Regarding the beam quality, a triangle-shaped near-field beam is observed from the MO output, which is in line with the shape of its pump area in the laser head. After the first stage amplifier, this triangular shape is enhanced, while after the orthogonally mounted second stage amplifier, the beam edge softens. Since the first stage amplifier, second stage amplifier and three stage amplifier provide similar thermal lens values, the final output beam exhibits a near-circular shape with an ellipticity of 0.88.

Aiming at the amplification demands in the area of long-range wind Lidar, a MOPA based on (Tm, Ho) ∶YLF crystal rods is demonstrated to provide 2 μm laser sources with high energy and long pulse duration. In the MO, a maximum output energy of 59.5 mJ with 133.8 ns pulse duration and central wavelength of 2051 nm is achieved at 10 Hz in the Q-switched regime using 8-shaped ring cavity. In the 3-stage two-way PA, the pulse energy is amplified to 201 mJ, while the pulse duration is slightly narrowed to 131.8 ns. This MOPA reduces the required maximum pump energy/peak power in each stage and optimizes the output beam quality with a simplified setup using an orthogonal arrangement of the crystal axes in each stage. Moreover, in both the MO and PA , a self-designed triple side-pumped, conductive-cooled laser head module is employed. This module integrates LD bars, laser crystal rods, conductive-cooling heat sinks, and a wedged lens pump light-coupling system, demonstrating a highly compact and robust design. This study provides a novel laser source for future airborne and spaceborne Lidar systems.

The significance of deep-ultraviolet (DUV) band light is its unique sterilization and disinfection ability, environmental performance, and wide application in other fields. Specifically, deep ultraviolet light can destroy the deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) structure of microorganisms, such as bacteria and viruses, thereby achieving efficient sterilization and disinfection. In addition, DUV technology has been applied in multiple fields such as water purification, air purification, medical treatment, biological research, national defense security, and ultraviolet communication, demonstrating broad application prospects. Therefore, the DUV bands are crucial in improving the quality of human life and promoting technological progress. Deep-ultraviolet vertical-external-cavity surface-emitting laser (VECSEL) can achieve high output power, excellent beam quality, and tunable wavelength by optimizing the resonant cavity structure to meet the urgent demand for DUV laser sources in scientific research and industrial fields. Stable and efficient DUV VECSELs provide advanced analytical tools and technical means in fields such as materials science, biomedicine, and environmental monitoring. In addition, research on DUV VECSEL will promote the development of nonlinear optical frequency conversion and quantum frequency conversion technologies, providing key technical support for cutting-edge fields such as quantum communication and quantum computing. Overall, research on DUV VECSEL aims to expand the application boundaries of laser technology and promote technological progress and industrial development.

First a gain chip with a center wavelength of 980 nm is designed. A high-Al-composition Al_0.6GaAs etch stop layer is grown on a GaAs substrate to block selective corrosion. Subsequently, a GaAs cap layer is grown, and after the etch-stop layer is corroded, this layer becomes the outermost layer of the gain chip, providing protection for the chip. Next, the active region is grown, which is mainly composed of 12 pairs of In_0.2GaAs/GaAsP_0.02 multiple quantum wells (MQWs). The content of In in the In_0.2GaAs quantum-well material corresponds to a design wavelength of 980 nm, but epitaxial growth on the GaAs substrate introduces a compressive strain of approximately 1.4%, which affects the quality of epitaxial growth. To minimize the frequent replacement of material types during epitaxial growth and better ensure the quality of epitaxial growth, this chip design specifically uses the GaAsP layer not only as a stress compensation layer but also as a barrier layer for quantum wells. Therefore, the content of P in GaAsP needs to be finely and reasonably designed to be sufficiently high to compensate for the stress introduced by multiple quantum wells. However, if the content of P is too high, InGaP cannot absorb pump photons. The final growth part of the gain chip is the distributed Bragg reflector (DBR), which is composed of 30 pairs of alternating GaAs/AlAs, with each layer having an optical thickness of 1/4 laser wavelength, which is 980 nm. Next is the performance testing of the gain chips, especially temperature and power testing, which directly affects the quality and efficiency of the final output light. Temperature and power testing are particularly important, because they can intuitively reflect the stability and output power of chips in different working environments. It is particularly noteworthy to observe the redshift phenomenon between the chip design wavelength and the actual output wavelength. Subsequently, the design of optical resonant cavities and the optimization of crystal selection are also key steps in improving optical conversion efficiency. When using a flat concave cavity structure, it is necessary to accurately match the core diameter of the pump with the laser spot inside the resonant cavity and calculate the waist position of the laser inside the cavity through simulation. This is directly related to the placement and length selection of the subsequent crystals. Based on the waist size, the optimal crystal length can be calculated, and the crystal can be accurately placed at the position of the laser waist to achieve high-frequency doubling conversion efficiency and high-power blue light output. Finally, the high-power blue light obtained is further converted into 245 nm deep ultraviolet light through barium metaborate (BBO) crystals.

We use a specially designed semiconductor gain chip (Fig. 1). The characteristics and advantages of the flat concave V-shaped cavity frequency-doubled blue light combined with the generated frequency-doubled blue light for fourth-harmonic generation result in a DUV output at 246.8 nm. The results indicate that the frequency-doubled blue light obtained using this cavity structure has excellent beam quality, close to the diffraction limit, a small beam divergence angle, and a more stable output mode while producing high power. In this study, a type-I phase-matched lithium triborate (LBO) crystal is selected as the frequency-doubling crystal. At an operating temperature of 15 ℃ using thermoelectric cooler (TEC), a 0.5 mm thick birefringent filter is inserted into the cavity. Using a 5 mm long LBO, we obtain a high-power blue light output of 4.5 W at a wavelength of 493 nm (Fig. 4). After passing through the type-I phase-matched BBO crystal, a DUV output of 29.2 mW at a wavelength of 246.8 nm is obtained (Fig. 7). This frequency-quadrupled VECSEL has advantages such as excellent beam quality, easy implementation, and a compact structure.

This paper presents the output of a compact frequency-quadrupled vertical external cavity surface that emits a DUV laser. A V-type laser resonant cavity is constructed using specially designed semiconductor gain chips, folding mirrors, and rear-end mirrors. Under a working temperature of 15 ℃, a high-power blue light output of 4.5 W is obtained by inserting a 5 mm long LBO crystal. A single-pass four-fold structure is formed by combining the rear reflection mirror, ultraviolet folding mirror, and ultraviolet output mirror of the frequency-doubling blue resonant cavity. The obtained blue light passes through a 3 mm long type I phase-matched BBO crystal, resulting in a 246.8 nm DUV laser output with a power of 29.2 mW through an output mirror with a transmittance of 50% at a wavelength of 245 nm. The aforementioned experimental results are limited by the pump power and coating of each optical lens. The DUV laser in this band can play a significant role in sterilization, disinfection, formaldehyde treatment, and other fields.

Coherent combining represents a groundbreaking technology in laser synthesis, which aims to break the limitations of traditional single-link laser systems and significantly improve laser brightness. The technology can be divided into active coherent combining and passive coherent combining according to whether the synthetic optical path contains active phase control elements for intervening detection and correcting phase errors. Active coherent combining systems have complex structures and the phase-locked bandwidths are limited by software algorithms and hardware circuits, so they are primarily utilized in high-energy laser applications. Conversely, passive coherent combining boasts a simple structure, wide phase-locked bandwidth, robust stability, and facile modular integration, thereby exhibiting broader development potential across diverse fields such as ranging, sensing, atmospheric wind data detection, and autonomous driving. Among them, optical feedback ring cavity combining based on fiber structure is one of the more popular passive combining schemes. However, one challenge faced by the ring cavity passive combining technique is that its output beam may contain multiple longitudinal modes or even multi-spectral lasers, which limits its application in remote coherent detection where ultra-long coherence length laser sources are required. To mitigate this issue, this study introduces a novel single-frequency fiber laser passive coherent combining technique, leveraging auxiliary cavity phase-locking. This technique successfully achieves excellent performance of the combined output laser in terms of narrow linewidth and long coherence length through a unique design. This proposed technique will offer robust support for advancing coherent laser lidar, coherent optical communication, and other allied disciplines.

This study investigates the single-frequency passive combining of single-mode erbium-doped fiber amplifiers. Initially, a 1550 nm single-frequency laser beam is split to serve as input for two single-mode optical amplifiers, facilitating rapid oscillation of the combined laser energy around 1550 nm. Subsequently, a 2×2 coupler is utilized to coupling and generate the open-loop output from the single-mode fiber amplifier system. Thereafter, the main cavity of the fiber ring is closed, and the seed laser is gradually extinguished. This setup produces a passive coherent combining beam output from the multi-longitudinal mode laser while effectively suppresses self-excited spike oscillations within the loop. Closure of the auxiliary ring cavity, aided by the Vernier effect and narrow-band filtering, separates laser longitudinal modes, enabling single longitudinal mode oscillation of the passively combined laser within the ring cavity. Subsequent measurements verify the achievement of a single longitudinal mode laser output. Furthermore, a delayed self-heterodyne optical path with 0.1 ms delay is implemented to analyze linewidth characteristics, providing insights into the synthesized laser properties.

Coherent beam combining of two single-mode amplifiers is investigated. In the open-loop stage, the combined laser power ranges between 0.59 mW and 51.01 mW, averaging 25.8 mW, limited by noise effects such as environmental vibration, amplified pump fluctuations, and thermal effects. Upon closing the main cavity, simultaneous amplification of the seed laser and loop resonance laser increases the closed-loop output power to 27.26?74.17 mW. After closing the seed, the laser power stabilizes within the cavity, forming a multi-longitudinal mode combined beam with phase-locked identical modes and different randomized modes, resulting in a power of 59.97 mW. Ultimately, upon closing the auxiliary cavity, the system achieves a single-longitudinal-mode phase-locked laser power of 66.4 mW, 2.57 times the open-loop average, with a combine efficiency of 89.6% and phase-locked closing time of 0.07 s (Fig. 3). Monochromatic spectra are observed for both amplifier outputs and the combined beam (Fig. 4). The single longitudinal mode capability is verified using a Fabry-Perot interferometer (Fig. 5). The linewidth of the combined laser is measured using a self-heterodyne system with a 0.1 ms delay, revealing a 20 dB linewidth of 20.813 kHz, corresponding to a 3 dB linewidth of 1.2 kHz (Fig. 6). This combined laser satisfies the requirements for laser sources with ultra-long coherent lengths in remote coherent detection applications.

In this study, a single-frequency fiber laser passive coherent combining system with auxiliary cavity phase-locking is designed. The system improves the traditional passive coherent combining technology by utilizing the Vernier effect. It achieves the single longitudinal mode output of the ring cavity passive coherent combining system while enhancing laser brightness. Additionally, a single longitudinal mode coherent combining model is derived based on the theory of ring cavity oscillation. At the experimental design stage, a ring cavity with a main cavity length of 2500 cm and auxiliary cavity lengths of 124.3 cm and 166.2 cm is selected for mode selection. A passive combining system with a total cavity free spectral range (FSR) of 193.56 GHz (significantly larger than the gain bandwidth of 62.4 GHz) is constructed to realize a single longitudinal mode output. At the experimental combining stage, open-loop laser power ranges from 0.59 mW to 51.01 mW, corresponding to an average power of 25.8 mW. After closing the main cavity, multi-longitudinal-mode combining power reaches 59.97 mW. After closing the auxiliary cavity, a single-longitudinal-mode laser output of 66.4 mW is achieved at a wavelength of 1550.445 nm and linewidth of 1.2 kHz with combine efficiency reaching 89%. This combine efficiency is notably higher than that achieved in open-loop conditions. The results indicate that this passive combining scheme has broad application prospects in ultra-long-range coherent lidar and coherent optical communication fields.

The particle size distribution (PSD) of aerosol particles is regarded as an important indicator in fields such as industrial emissions monitoring, global warming research, and medical research. In most aerosol measurement techniques, the dynamic light scattering (DLS) method has advantages under certain measurement conditions because the refractive index of aerosol particles does not need to be determined. When using the autocorrelation function (ACF) of the measured particle intensity to invert the PSD in flowing aerosol DLS, flow velocity is a necessary parameter. However, the measurement error of flow velocity leads to errors in the coefficient matrix of the inversion equation. The Tikhonov regularization (LS-Tik) inversion method based on the classical least squares model only considers errors in the measurement correlation function and does not consider those in the coefficient matrix. Meanwhile, the increase in the flow velocity term exacerbates the ill posedness of the particle size inversion equation, leading to an increase in PSD sensitivity to noise and poorer anti-interference performance, resulting in lower solution accuracy. To address this issue, a Tikhonov?total variation (TV) hybrid regularization (TLS-Tik-TV) inversion method based on total least squares (TLS) is proposed, which considers both the coefficient matrix and measurement correlation function errors, to reduce the ill posedness of the inversion equation, minimize noise sensitivity, and improve inversion accuracy.

First, we established a TLS model that considered both coefficient matrix and measurement correlation function errors. Subsequently, based on the TLS model, the traditional LS-Tik was combined with the noise-resistant TV regularization to establish the TLS-Tik-TV inversion algorithm. To verify the performance of the algorithm, Johnson’s SB function was used to generate simulation data. Different flow rates were selected at noise levels of 10^-2 and 10^-3, and the LS-Tik and TLS-Tik-TV algorithms were used to simulate unimodal and bimodal particles. Two performance indicators, peak error (E_p) and distribution error (E_r), were introduced to evaluate the accuracy of PSD inversion, and the conclusions of the simulation experiment were verified by inverting the measured data.

Compared with the LS-Tik algorithm, the established TLS-Tik-TV algorithm (Fig. 1) has smaller peak and distribution errors, stronger bimodal resolution, and higher inversion accuracy. When simulating particles with a unimodal distribution, at the same particle size, the peak and distribution errors of both the LS-Tik and TLS-Tik-TV methods gradually increase as the flow rate increases, manifesting as a left shift in the peak position and PSD broadening. However, the amplitude of the left shift in the peak position and PSD broadening of TLS-Tik-TV is smaller than those of LS-Tik (Figs. 2?4). At the same particle size and flow rate, TLS-Tik-TV exhibits smaller peak and distribution errors compared to LS-Tik (Table 2). For example, for 601 nm particles, TLS-Tik-TV can reduce the peak and distribution errors by up to 0.033 (Table 2). For particles with a simulated bimodal distribution, under the same set of bimodal distributions, as the flow velocity increases, both methods result in a left shift in the peak position and a decrease in the peak height in the PSD obtained by inversion. However, at a selected flow rate of 0?1.5 m/s, for the 143/584 nm and 234/700 nm particle systems, the TLS-Tik-TV peak position shifts to the left less and the peak height decreases less compared to those of LS-Tik (Figs. 5 and 6). At the same particle size and flow rate, the peak and distribution errors of TLS-Tik-TV are generally lower than those of LS-Tik (Table 3). The inversion results of the measured particles show that TLS-Tik-TV exhibits smaller peak and distribution errors and stronger bimodal resolution (Figs. 8 and 9, Table 4), revealing the same trend as the inversion results of simulated data.

A TLS-Tik-TV inversion algorithm is proposed. This algorithm uses the TLS model to balance the coefficient matrix and correlation function errors and combines Tikhonov and TV regularization to reduce the ill posedness of the inversion equation two-fold and improve the inversion accuracy. Under different flow rates and noise levels, the traditional LS-Tik and TLS-Tik-TV methods were used to invert simulated particles. The results show that compared with LS-Tik, TLS-Tik-TV exhibits smaller peak and distribution errors, stronger bimodal resolution, and stronger noise resistance. The inversion results of 584 nm unimodal and 243/825 nm bimodal measured particles show that compared to LS-Tik, TLS-Tik-TV exhibits smaller peak and distribution errors, stronger bimodal resolution, and can reduce peak errors by up to 0.027 and 0.123/0.091, as well as distribution errors by 0.032 and 0.038, respectively. Therefore, TLS-Tik-TV is superior to LS-Tik, and the inversion of the measured particles also verifies the conclusions of simulated data.

In laser-driven inertial confinement fusion (ICF) experiments, precise observation of dynamic wavefront changes is crucial for understanding fluid instabilities. The CUP-VISAR system, with its high spatiotemporal resolution, is widely used for this purpose. However, existing algorithms face challenges in processing CUP-VISAR data effectively due to high noise levels, particularly under low contrast-to-noise ratio (CNR), resulting in poor image reconstruction and inaccurate shock wave velocity measurements. To address these limitations, we propose a novel data reconstruction algorithm that combines tensor singular value thresholding (TSVT) and stripe phase mapping (SPM) to enhance noise suppression and feature extraction, improving velocity field accuracy under varying noise conditions.

The key innovation of this research is the integration of TSVT and SPM within a unified framework. TSVT transforms noisy data into the frequency domain, leveraging low-rank tensor properties to isolate essential signal components while filtering out noise using singular value decomposition (SVD). Following TSVT, SPM reconstructs phase data by treating deviations from sinusoidal interference patterns as noise, thereby enhancing stripe clarity for accurate velocity field estimation. Finally, total variation (TV) regularization smooths the data to reduce spatial and temporal artifacts. This multi-step approach effectively combines TSVT, SPM, and TV for robust noise suppression. The algorithm’s performance was validated on SG-III prototype data under varying CNR conditions, with comparisons to E-3DTV, ADMM-TV, and TVAL3 using metrics such as peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) (Fig. 6), and relative velocity error.

The results indicate a significant enhancement in reconstruction quality achieved by the TSVT?SPM algorithm, particularly under low CNR conditions. Across the entire tested CNR range (4?10), the proposed algorithm consistently outperformed other methods in terms of both PSNR and SSIM. For instance, at a CNR of 6.56, the TSVT?SPM method achieved a PSNR of 29.15 dB and an SSIM of 0.94, compared to the 9.84 dB PSNR and 0.37 SSIM recorded by the E-3DTV algorithm (Table 2). This demonstrates a substantial improvement in reconstruction accuracy and image quality, demonstrating the robustness of the proposed approach. In addition to PSNR and SSIM comparisons, the relative velocity error between the reconstructed data and the original velocity field was analyzed. Even under challenging noise conditions, the TSVT?SPM algorithm exhibited a maximum relative velocity error of 6.11%, significantly lower than the errors produced by the other algorithms: 138.63% for E-3DTV, 130.98% for ADMM-TV, and 111.64% for TVAL3 (Fig. 12). These findings highlight the superior capability of the proposed method to accurately recover the velocity field despite substantial noise interference. Visual inspections of the reconstructed data further illustrate the strengths of the TSVT?SPM algorithm. As shown in Fig. 9, the proposed method delivers a markedly clearer and more precise representation of the dynamic 2D velocity fields, particularly in the 25th frame, where the stripes are well-defined, and noise is substantially reduced compared to other methods. Moreover, the temporal evolution of the stripes, depicted in Fig. 10, reveals that the algorithm effectively captures smooth transitions and subtle variations in the velocity field over time. In contrast, the E-3DTV and ADMM-TV methods exhibit severe artifacts and poor temporal resolution in noisy environments. The robustness of the TSVT?SPM algorithm is further validated by its performance across varying noise levels. In Table 2, we observe that as the CNR increases from 4 to 10, the proposed algorithm maintains consistent improvements in PSNR and SSIM, confirming its effectiveness across a wide range of noise intensities. This reliability across different experimental conditions underscores the algorithm’s adaptability without significant performance degradation. In addition, the low-rank structure extracted by TSVT enables efficient handling of large-scale datasets, a critical requirement for processing high-dimensional data in real-world ICF experiments.

The TSVT?SPM algorithm represents a significant breakthrough in CUP-VISAR data reconstruction by integrating tensor decomposition, phase mapping, and regularization techniques. This approach effectively addresses the challenges posed by noisy data in dynamic velocity field measurements. Experimental results demonstrate that the algorithm not only surpasses existing methods in reconstruction accuracy but also exhibits superior robustness under varying noise conditions. Its ability to deliver high-quality reconstructions, even at low CNRs, is particularly advantageous for inertial confinement fusion applications, where precision and reliability are paramount. With its effectiveness in noise suppression and feature preservation, the algorithm is well-suited for large-scale data processing. Its capability to handle high-dimensional data while maintaining consistent performance across different noise levels ensures its applicability in complex experimental environments.

Multi-object tracking (MOT) is identified as a critical issue in computer vision, where specific target categories are detected and tracked in every frame of image sequences. These techniques are widely applied in areas such as sky warning, safety monitoring, autonomous driving, and video analysis. Recent MOT research focuses on the track-by-detection (TBD) paradigm, where detection in each frame becomes a data association task. This approach, which often employs appearance and motion embeddings for bipartite graph matching, is preferred by researchers due to the effectiveness of high-performance object detection models.

A multi-object tracking method based on quasi dense similarity learning (QDSL) is proposed to tackle accuracy challenges stemming from clutter, occlusions, and similar object appearances. The improved YOLOv8 framework is utilized for multi-object detection, generating in bounding box outputs. Subsequently, dense sampling of object regions across adjacent frames is performed for contrastive learning to facilitate local data association. Ultimately, the integration of similarity learning with YOLOv8 is implemented, alongside an appearance-free link model, facilitating global association without dependence on appearance features. This approach effectively balances tracking speed and accuracy.

The effectiveness of the proposed algorithm is evaluated through component ablation experiments conducted on the MOT17 dataset video sequences, with results summarized in Table 2. The experiments indicate a significant improvement, with a 0.7% increase in multiple object tracking accuracy (MOTA) and a 0.3% increase in identity F1 score , demonstrating enhanced tracking performance as shown in Fig. 8. Comparative experiments, detailed in Table 4, demonstrate the algorithm notable advantages over three other tracking techniques, underscoring its superior performance. Furthermore, airplane tracking tests showcase the algorithm robustness and ability to handle images with varying sizes and angles effectively, with results presented in Fig. 9.

The proposed multi-object tracking method leverages an improved version of YOLOv8 along with QDSL to tackle challenges related to occlusion and similar object appearances. By using QDSL, the object features are developed with greater accuracy, enhancing both the stability of local correlations and their reliability. Continuous trajectory updates with Gaussian smooth interpolation are achieved, validating the model applicability in complex multi-target tracking scenarios. Extensive comparative experiments and tracking tests demonstrate the model superior adaptability to real-world situations.

Surface plasmon resonance (SPR) in metal nanostructures strongly localizes the optical energy in the near field by coupling photons with free electrons, and the interaction between light and matter near the nanostructures can be significantly enhanced for ultrasensitive molecular transduction and enhanced spectroscopies. SPR modes depend highly on the features of metal nanostructures, and the design and fabrication of SPR-tunable nanostructures present a significant challenge to large-scale metasurface devices. Ultraviolet (UV) laser interference lithography has garnered considerable attention because of its advantages such as low cost, high efficiency, no mask, large scale, and high flexibility. This study proposes angle-twisted interference lithography using dual UV laser beams followed by ion sputtering, by which a large-scale Au nanofilm Moire-grating (AuNF Moire-grating) with tunable SPR and fixed localized surface plasmon resonance (LSPR) with respect to orthogonal excitation polarization can be achieved. The AuNF Moire-grating can be easily designed and fabricated to match a specific wavelength for efficient SPR excitation. It demonstrates the use of polarization-independent surface-enhanced Raman spectroscopy (SERS) for ultrasensitive detection.

The fabrication procedure is shown in Fig. 1. The photoresist film is first obtained via dropwise addition of a photoresist to a clean quartz glass substrate, followed by spin curing. Subsequently, angle-twisted interference lithography is performed using dual laser beams on the photoresist with a single-exposure grating period of 300 nm, by which the period of the Moire grating can be modulated from 439 nm to 864 nm by adjusting the twisted rotation angle between the two exposures from 20° to 40°. Subsequently, AuNF is deposited onto the surface of the Moire grating structure via vacuum ion sputtering, by which a narrow-gap AuNF Moire-grating with a tunable SPR wavelength is obtained. The wavelength of the SPR absorption can be regulated from 540 nm to 875 nm. The surface morphology of the AuNF Moire-grating is examined using scanning electron microscope (SEM). The effect of the AuNF Moire-grating period on the tunability of the SPR wavelength as well as the mechanism of depolarization by the cooperation of the Moire-grating SPR with narrow-gap LSPR are revealed experimentally and theoretically. Finally, an AuNF Moire-grating SERS substrate with an SPR wavelength matching that of the excitation laser is fabricated for polarization-independent Raman sensing.

As the twisted rotation angle increases from 20° to 40°, the fabricated Moire-grating period modulates from 439 nm to 864 nm. The experimental results are consistent with the theoretical calculations. The width of the narrow gap remains unchanged, as shown in Fig. 2. The reflectance spectra of the AuNF Moire-gratings with different Moire periods are measured under circularly polarized excitation. Clear SPR absorption peaks are observed in the reflectance spectra. The SPR absorption wavelength is tunable between 540 nm and 875 nm, which is consistent with numerical-simulation results (Fig. 3). When the excitation wavelength matches the SPR of the AuNF Moire-grating, a significant electromagnetic enhancement in the near field can be achieved for s- and p-polarization owing to SPR and LSPR, respectively. The corresponding polarization-independent absorption is shown in Fig. 4. Finally, a AuNF Moire-grating SERS substrate is fabricated, which demonstrates polarization-independent Raman detection with a limit of 10^-10 mol/L, as shown in Figs. 5?7.

This study proposes a novel technique of angle-twisted interference lithography using dual UV laser beams followed by ion sputtering to obtain a narrow-gap AuNF Moire-grating with a tunable SPR wavelength. The Moire-grating period can be modulated from 439 nm to 864 nm by adjusting the twisted rotation angle from 20° to 40°, which regulates the wavelength of the SPR absorption from 540 nm to 875 nm. Experiments and numerical simulations indicate that when the SPR of the AuNF Moire-grating structure is matched with the excitation wavelength, the Moire-grating SPR with narrow-gap LSPR enhances the near-field electromagnetic field regardless of the polarization state, by which polarization-independent strong absorption is achieved. The AuNF Moire-grating can be used as a polarization-independent SERS substrate for trace detection with a limit of 10^-10 mol/L. This study provides opportunities for the design and fabrication of polarization-insensitive SERS substrates with tunable excitation wavelengths for practical applications.

Continuous-variable quantum key distribution (CV-QKD) protocols have demonstrated the potential to achieve higher secure key rates in fiber-optic channels. However, the feasibility of satellite-to-ground Gaussian-modulated CV-QKD (GM CV-QKD) remains largely theoretical research and has only undergone preliminary experimental investigation. Practical factors, such as atmospheric attenuation, diffraction, and turbulence, play a significant role in the feasibility of satellite-to-ground CV-QKD protocols. Furthermore, the limited access time between low-Earth orbit satellites and ground stations exacerbates the effects of finite key length on the estimation of protocol parameters.

This study assesses the feasibility of satellite-to-ground GM CV-QKD by developing a dynamic, time-varying orbital model for satellite downlinks, based on realistic performance parameters of satellites and ground stations. This study examines the effects of preparation variance and reverse reconciliation efficiency on key generation and compares the performance of GM CV-QKD with discrete variable QKD (DV-QKD). Considering the rapid motion of the satellite, which limits the access time of the system, this study also examines the influence of the symbol number of parameter estimation and symbol transmission rate on the key generation under the finite key length effect to optimize the system performance.

Based on the theoretical model and specific simulation parameters, the following simulations are conducted: Fig. 4 examines the effects of preparation variance and reverse negotiation efficiency on key generation. For any communication system with different negotiation efficiencies, there is an optimal preparation variance that maximizes the total key generation of the system. Fig. 5 compares optical fiber CV-QKD and free space CV-QKD, revealing that free space CV-QKD decreases the mutual information of the communication parties and reduces the protocol performance due to fluctuating channels. Fig. 6 compares satellite-to-ground DV-QKD and GM CV-QKD, demonstrating that GM CV-QKD significantly outperforms DV-QKD in Earth-to-Earth communication with low-Earth orbit satellites and high noise levels. Fig. 7 explores the influence of the number of symbols used for parameter estimation and the symbol transmission rate on key generation under the finite key length effect and optimizes the number of symbol symbols for parameter estimation under different symbol transmission rates.

This study investigates the influence of preparation variance and reverse negotiation efficiency on key generation using a satellite-Earth orbit model. The findings reveal that compared with fiber CV-QKD, the random fluctuation in the free space channel reduces the mutual information of the two communication parties. In addition, due to the spatial channel is fluctuating, the effect of preparation variance on the key generation rate is not single, and there is an optimal preparation variance. A comparison between GM CV-QKD and DV-QKD shows that GM CV-QKD significantly outperforms DV-QKD in low-Earth orbit satellite communication scenarios with a little excess noise. The effect of finite key length is examined, and the effect of symbol transmission rate and the number of estimated symbols on the system performance is analyzed. The simulation results indicate that the symbol transmission rate must exceed a threshold to generate the positive key. In addition, when the symbol transmission rate is in the nonlinear growth region, increasing the symbol transmission rate can bring more benefits. The optimal number of symbols for parameter estimation at different symbol transmission rates is determined to improve system performance. These findings offer valuable insights for the design and optimization of the satellite-to-ground GM-CV-QKD experiment.

Lithium-ion batteries are the predominant energy storage solutions in various power systems and portable devices owing to their superior energy density, long cycle life, low self-discharge rate, and environmental sustainability. However, aging and performance degradation of lithium-ion batteries during actual use significantly limit their further development. State of charge (SOC) serves as a critical indicator for assessing the remaining capacity and overall health of a battery, making its accurate estimation essential for optimizing battery management systems and enhancing performance. Conventional SOC estimation methods rely primarily on electrical parameters such as voltage and current, which are susceptible to electromagnetic interference and measurement noise, thereby reducing the accuracy of SOC estimation. Therefore, exploring SOC estimation methods based on nonelectrical parameters, particularly optical sensing technologies, has significant practical implications. Fiber Bragg grating (FBG) sensors are a focal point of research in lithium-battery state monitoring owing to their superior measurement accuracy, high resistance to electromagnetic interference, and compact size. The integration of optical sensing technology with deep learning offers a promising avenue for more accurate SOC estimation, presenting significant economic and practical value.

A novel method based on FBG sensors and deep learning models has been proposed to estimate the SOC of lithium-ion batteries. First, a lithium-battery state-monitoring system was established, incorporating FBG sensors and a tunable fiber Fabry?Pérot (FFP) filter. Two FBG sensors were affixed to the surface of the lithium battery to measure changes in the characteristic grating wavelengths resulting from strain and temperature variations during the charge and discharge experiments. Subsequently, a convolutional neural network (CNN) was employed to extract spatial features from the observed wavelength variations. Finally, a gated recurrent unit (GRU) was utilized to establish a deep-learning framework for SOC estimation based on the extracted data features. The accuracy and economic viability of the proposed method were validated by comparing the experimental results with those of conventional methods, demonstrating its advantages in enhancing the SOC estimation accuracy and reducing system costs.

To detail the variations in parameters during the charging and discharging of the battery, we record the voltage, current, and wavelength changes caused by surface strain and temperature, using a battery testing system (BTS) to manage the processes. The current and voltage steps are set, dividing the entire cycle into four distinct stages: constant current discharge, resting, and constant current/constant voltage charging. The changes in the SOC during the charging and discharging of the lithium-ion battery are calculated based on the SOC definition (Fig. 5). Throughout the experiments, the two FBG sensors monitor the changes in the grating wavelength caused by strain and temperature variations. The absolute wavelength drift of the FBG sensors caused by surface strain, and the spectral position of the reference FBG, representing the temperature information, are calculated (Fig. 6). After obtaining the nonelectrical parameters from the FBG, further SOC estimation for the lithium battery is conducted. Using the absolute wavelength drift of the sensing FBG and the spectral position of the reference FBG as input features, a deep learning framework, CNN-GRU, is developed. Accurate SOC estimation for the lithium-ion battery is performed during the charging and discharging cycles, and the evaluation metrics for the estimated results are calculated (Table 1). The experimental results indicate that the prediction model constructed using only nonelectrical input features can accurately predict the SOC of the lithium battery (Fig. 7). Additionally, using the input feature data provided by the FBG sensors, the hybrid model captures the nonlinear relationship between the nonelectrical parameters and the SOC of the lithium battery more effectively, significantly improving SOC estimation.

This study employs two FBG sensors attached to the surface of A123 soft-pack lithium-ion batteries to measure the changes in strain and temperature in real time during charging and discharging. A nonlinear relationship model between optical sensing signals and electrochemical signals is established using deep learning algorithms. Consequently, SOC estimation for the lithium battery is conducted. The results indicate that using only two nonelectrical parameters provided by the FBG sensors yields a relatively accurate estimation of SOC, highlighting the significant potential of nonelectrical parameter features in SOC prediction. Both single and hybrid deep learning models are incorporated into SOC estimation based on FBG sensing. The experimental results show that the hybrid model, CNN-GRU, achieves higher accuracy than the single-model GRU. This provides a more reliable solution for SOC estimation in lithium batteries. The findings address high costs associated with incorporating FBG sensing into lithium-ion battery state estimations. Concurrently, the feasibility of estimating the SOC using pure wavelength signals is validated. This provides valuable insights for extending battery lifespan and improving energy utilization efficiency.

In phase-sensitive optical time-domain reflectometers (Ф?OTDRs), coherent and polarization fading caused by inherent destructive interference and polarization mismatch, affect phase restoration performance. Traditional signal fading suppression methods typically require additional hardware structures, which increases system complexity and cost. Moreover, vibration signals are non-stationary with complex frequency components, which further increases the fading suppression challenge. Therefore, it is of paramount significance to investigate a novel signal fading suppression method to achieve accurate phase reconstruction on the simplest structure in scientific research and engineering applications.

In this study, the random signal fading process in Ф-OTDR is analyzed, and it is confirmed that the fading point phase is a random noise value that follows uniform distribution. Using the empirical mode decomposition (EMD) algorithm, phase noise including phase accumulation noise and laser frequency drift is filtered out and phase information modulated by external vibration is extracted. The extracted phase data are subsequently organized into a two-dimensional space-time map, which are input into a generative adversarial network (GAN) to realize the repair of the fading data. The GAN training dataset, which is generated using software simulation, contains a total of 12000 images including the phase spectra of sinusoidal, square, and triangular wave vibration signals, Gaussian pulse vibration signal, and random vibration signal.

Experiments are designed as follows. The total length of the sensing fiber is 10.12 km, which is connected by three sections of single-mode fibers of 4.17, 1.92, and 3.95 km in length, respectively. A piezoelectric ceramic (PZT) is connected between each section of fiber and driven by the signal generator to produce the required vibration signal. Phase demodulation is performed at two vibration positions (4.186 km and 6.148 km), and a strong noise is observed in the raw space-time spectrum of phase [Figs. 8 (a)?(d)]. Subsequently, using the EMD algorithm, the phase noise (phase accumulation noise and laser frequency drift noise) is suppressed, however, the fading noise remains [Figs. 8 (e)?(h)]. Next, the processed space-time spectrum of phase is segmented and input into the GAN to repair the fading data. The phase information follows the modulation of external vibration signals, which indicates that the fading noise is suppressed after the GAN data repairing [Figs. 8 (m)?(p)]. Further, one-dimensional time and distance slices are performed on the phase space-time spectrum, respectively. It can be observed that, owing to signal fading, the phase correlation in the sensing area is disrupted, resulting in a fading peak appearing at certain positions on the sensing fiber [Figs. 9 (a)?(d)]. Thus, the phase value at the fading point overwhelms the phase information modulated by the external vibration signal, which causes phase distortion [Figs. 9 (e)?(h)]. Subsequently, after applying the EMD-GAN method, signal fading is clearly suppressed [Figs. 9 (i)?(l)] and the phase follows the external vibration signal modulation [Figs. 9 (m)?(p)]. Finally, repetitive tests are conducted on different types of vibration signals and the average probability of signal fading in the Ф?OTDR sensing system decreases from 2.61% to 0.27%. This further validates the effectiveness of the proposed EMD-GAN method.

This study proposes a novel signal fading suppression scheme based on EMD-GAN. By analyzing the random signal fading process in Ф-OTDR, it is proved that the fading point phase is a random noise value that follows uniform distribution. Using the EMD algorithm, phase noise is filtered from the original demodulated data, and the reconstructed space-time spectrum of phase is input into the GAN to repair fading data. Four different vibration signal types, including sinusoidal, square, triangular, and variable-frequency wave vibration signals are used for experimental verification. The experimental results demonstrate that the proposed method reduces the average probability of signal fading from 2.61% to 0.27% over a sensing fiber length of 10.12 km. Finally, this contribution presents a novel solution to address signal fading suppression and accurate phase restoration in Ф-OTDR sensing systems without increasing hardware structural complexity.

The single-photon LiDAR is widely utilized in fields such as biology, geology, remote sensing, robotics, and navigation due to its long-range capability and high imaging resolution. When combined with the time-correlated single-photon counting technology, the system can achieve picosecond-level time resolution, enabling the reconstruction of high-resolution depth images. The system has a pulsed laser that emits periodic short pulses toward a target scene and a single-photon detector that counts the reflected photons. By scanning each pixel over an extended period, a photon count of the order of 10³ can be achieved for each pixel. This process effectively reduces background noise and detector dark counts and minimizes the range uncertainty caused by photon flight time jitter. These beneficial effects make it possible to realize millimeter- to micrometer-level distance accuracy and high-resolution depth image reconstruction. Traditional methods that rely on repeated measurements have long data acquisition times, limiting the applicability of single-photon LiDAR in dynamic target remote sensing, autonomous driving, and non-line-of-sight imaging. When acquisition times are short and echo signals very weak, only a few photons are detected, leading to a low signal-to-noise ratio (SNR). Reconstructing high-precision depth images with minimal echo photon data under these low-SNR conditions is a major challenge for existing single-photon counting LiDAR technology. To address this challenge, a novel depth image reconstruction algorithm is proposed. This algorithm integrates a photon-counting LiDAR detection probability model with a backpropagation neural network. This approach enhances the accuracy of depth image reconstruction under varying SNR conditions and improves the performance of single-photon LiDAR in complex scenarios.

The proposed method improves depth image reconstruction from single-photon LiDAR data under low-SNR conditions. The method comprises three main steps. The first step is filtering based on the photon-counting LiDAR detection theory. This involves windowed processing and adjustments for noise cluster probabilities to enhance the signal by reducing noise. In the second step, a backpropagation neural network fills in the missing pixels, ensuring image continuity. Unlike existing deep-learning approaches, this step eliminates the need for additional datasets. In the final step, total variation regularization is performed to refine the depth image and improve accuracy. This step enhances depth estimation precision and effectively manages the challenges of low SNRs. By combining these techniques, the proposed method significantly improves the depth estimation performance for single-photon LiDAR systems.

Simulations using the Middlebury dataset were performed to evaluate single-photon avalanche diode measurements obtained under different scenes and lighting conditions. The performance of the proposed algorithm was compared with that of the Shin and the Rapp algorithms by measuring the average reconstruction error for the depth images across nine typical noise levels and four test scenarios.

The results indicate that under typical noisy conditions, particularly in environments with very low SNRs, the proposed algorithm significantly outperforms the Shin and Rapp algorithms. A comparison of the average reconstruction errors of the three algorithms for different scenes showed that compared to the Shin and Rapp algorithms, the proposed algorithm achieved improvements of 38.67 times and 56%, respectively, in the Art scene; 62.07 and 1.05 times, respectively, in the Bowling scene; 52.67 and 1.78 times, respectively, in the Laundry scene; and 14.15 times and 42%, respectively, in the Reindeer scene.

The Shin algorithm significantly reduced the estimation error when the SNR exceeded 0.05. This improvement is attributed to the algorithm's binomial estimation approach, which efficiently extracts signals and suppresses noise as the SNR increases. The Rapp method performs well at high SNRs but shows a notable decline in performance when the ratio drops to 0.01. Since the Rapp method relies on neighboring pixel photon data, it can effectively distinguish signals under high SNR conditions but is prone to boundary errors in low-SNR scenarios. In the proposed method, although the error increases with rising noise levels below 0.05, the increase rate is slower than that of the Shin and Rapp algorithms, indicating greater robustness of the proposed method under extremely low-SNR conditions.

From the perspective of computational efficiency, the average running time of the proposed algorithm is slightly lower than that of the Rapp algorithm but higher than that of the Shin algorithm. Although the Shin algorithm has the shortest run time, it suffers from high reconstruction errors. Thus, the proposed algorithm achieves a better balance of performance and efficiency, making it more suitable for environments with low SNRs.

Traditional methods work well for reconstructing depth images under high SNRs. However, in low-SNR environments, background noise often hides details of the target objects, making it hard to distinguish them from their surroundings. To tackle this problem, a new depth image reconstruction algorithm is proposed. It combines photon-counting LiDAR models with deep-learning techniques. This algorithm is specifically designed for low-SNR conditions, effectively smoothing depth images while preserving edge details. A comparison with other methods showed that the proposed algorithm greatly reduces the reconstruction errors compared to the existing methods, especially under very low-SNR conditions.

The proposed method is expected to enhance the application of photon imaging in challenging scenarios, such as non-line-of-sight and ghost imaging. It can also refine modules in the photon-counting LiDAR image reconstruction, offering potential for future upgrades and customization.

Optoelectronic tracking systems enable the precise positioning, continuous tracking, and accurate measurement of targets in fields such as aeronautics, defense, and scientific exploration. Owing to their ability to perform high-precision tracking, these systems can adapt to complex electromagnetic environments and demonstrate remarkable efficacy in scenarios involving advanced aircraft. Owing to the development of new detectors and signal-processing technologies, optoelectronic tracking systems have incorporated higher performance detectors, utilized artificial intelligence (AI) algorithms, and transitioned from single-sensor to multimodal detections. Meanwhile, the demand for managing tasks involving multiple, high-speed, and weak targets in complex environments has increased. Therefore, the existing studies must be summarized to guide the future development of this field.

The technological solutions for optoelectronic tracking systems have evolved continually, with system structures changing from single-function to integrated designs (Fig. 1). Conventional optoelectronic tracking systems can be categorized into imaging and non-imaging types. Imaging systems, such as optical theodolites, infrared search and track systems (IRST), and electro-optical targeting systems (EOST), provide abundant image information, whereas non-imaging systems, such as Lidar for distance measurement and positioning and quadrant detectors for location determination, focus on high sensitivity and rapid tracking. In recent years, multimodal optoelectronic tracking systems have emerged. These systems, particularly those integrating optical and radar functionalities, offer advanced capabilities (Fig. 12). By combining infrared imagers, visible-light cameras, and radars, these systems afford higher measurement accuracies and enhanced capabilities, thus overcoming the limitations posed by single sensors under certain environmental conditions.

Photodetectors, as core components of optoelectronic tracking systems, directly affect the overall performance of the system. Owing to technological advancements, photodetectors are being developed to achieve higher sensitivities, larger pixel scales, and better signal-to-noise ratios (Table 1). Single-photon detectors, particularly single-photon avalanche diodes (SPAD) and superconducting nanowire single-photon detectors (SNSPDs), are preferred in optoelectronic tracking systems owing to their high sensitivity and long detection range. Additionally, infrared focal plane array (IR-FPA) detectors are crucial in optoelectronic tracking systems, particularly in scenarios requiring high resolutions and multisensor fusion.

Advancements in signal-processing technology are key to enhancing the performance of optoelectronic tracking systems. Conventional signal-processing methods, such as Kalman filtering and particle filtering, remain widely used. However, owing to the development of deep-learning technology, signal-processing methods based on the convolutional neural network (CNN) have emerged, e.g., the YOLO series, Siamese network, and Transformer plus CNN (Fig. 23). These methods can learn features from large datasets, thereby improving the accuracy of target recognition and enabling systems to perform autonomous search, identification, and tracking in complex environments.

Optoelectronic tracking systems are fundamental in the precise detection, positioning, and tracking of targets. Their performance is affected by the pixel scale, characteristics, and sensitivity of the detectors; the signal characteristics of detectors further determine the choice of appropriate signal-processing methods. Future advancements shall focus on multimodal detection, the innovation of detectors, and the development of intelligent signal-processing technologies. Through these advancements, optoelectronic tracking systems will be able to precisely detect, position, and track high-speed, long-range, and weak targets in complex environments.

Linearly polarized fiber lasers have a wide range of applications in areas such as beam combination and nonlinear frequency conversion. Mode instability, nonlinear effects, and other polarization-dependent factors, however, limit the enhancement in the fiber laser output power and thereby hinder the increase in the output power of linearly polarized lasers. In recent years, theoretical breakthroughs and technological advances in the laser fiber fabrication process alongside nonlinear effect/mode instability effect mitigation methods, and laser cavity design have prompted a rapid progress for high power linearly polarized fiber lasers, resulting in a continuous improvement in their overall performance. This paper aims to present the research results and development of linearly polarized fiber lasers globally from the aspects of laser linewidth, operation waveband, operation regime, and emerging power-scaling methods. An outlook on the development trend of linearly polarized fiber lasers is also discussed.

First, general progress in linearly polarized fiber lasers with different linewidths, that is, single-frequency, narrow-linewidth, and conventional fiber lasers, alongside superfluorescent fiber sources, and supercontinuum fiber sources, is summarized and reviewed. Second, linearly polarized fiber lasers operating at other wavebands are reviewed, including the Er-doped fiber laser at ~1.5 μm, Tm-doped fiber laser at ~2 μm, Yb-doped fiber laser at the long waveband (1.1?1.2 μm), Nd-doped fiber laser at ~0.9 μm, Raman fiber laser at 1.1?1.2 μm, and fiber lasers with manipulated output wavelength (central wavelength tunability, multiwavelength operation, and sweeping wavelength). Third, the research progress in pulsed linearly polarized fiber lasers with pulse durations ranging from nanosecond, picosecond to femtosecond is introduced. Then, the polarization dependence of nonlinear effects and mode instability is summarized, and mitigation methods of these two effects are briefly introduced. Finally, based on the aforementioned progress, some emerging techniques for further power scaling of linearly polarized fiber lasers are discussed, including, but not limited to, employment of low-quantum-defect fiber lasers schemes, exploitation of new laser materials such as single-crystal fibers, and adaptation of the coherent beam combination method.

Linearly polarized fiber lasers have made rapid progress in multiple types of linewidths, multiwaveband operation, and pulsed laser outputs with different durations, thus opening up the potential to not only further improve the performance in laser processing, coherent detection, and other fields, but also enable new application fields in the generation of mid-infrared lasers, visible/ultraviolet light, and structured light generation. However, compared with their randomly polarized fiber laser counterparts, linearly polarized fiber lasers still present a large gap in spectral coverage range and output power. Therefore, one of the future directions for linearly polarized fiber laser research is the development of high-performance polarization-maintaining fibers and high-quality multi-waveband fiber devices. Another potential focus is the continuous improvement in the output power and performance of the laser, including the employment of low-quantum defect schemes, new gain media, and coherent beam combination technology, to meet the application requirements. Lastly, new laser bands can be explored to broaden the spectral range of linearly polarized lasers, such as the direct generation of linearly polarized visible lasers in an oscillator scheme and the generation of a wider range of tunable linearly polarized lasers based on nonlinear effects, to meet diversified application requirements. A series of scientific and engineering problems must be addressed, including the comprehensive suppression of mode instability and nonlinear effects, polarization state evolution, control and compensation, and broad-spectrum polarizability measurements. Addressing the relevant physical and technical problems will not only promote the performance of linearly polarized fiber lasers to a new level but also has great significance for the development of laser science and is expected to be promoted to other new applications.

Environmental perception and localization technologies are crucial for the stable operation of autonomous systems, which are increasingly prevalent in society. Of the various localization methods, simultaneous localization and mapping (SLAM) and the global navigation satellite system (GNSS) are two prominent approaches. Unlike GNSS, which relies on external position inputs, SLAM achieves localization solely through onboard sensors. In addition, SLAM can be integrated with GNSS and inertial measurement units (IMUs) to enhance overall performance.

Visual SLAM, which utilizes 2D images, initially experienced significant advancements due to improvements in camera technology. However, the susceptibility of these images to environmental factors, such as lighting variations, can compromise the accuracy of visual SLAM systems. By contrast, light detection and ranging (LiDAR) provides a more stable sensing mechanism by capturing 3D points, resulting in greater accuracy and robustness for LiDAR-based SLAM systems across varying conditions.

In recent years, LiDAR-based SLAM has gained widespread adoption in fields such as unmanned aerial vehicles and autonomous driving. This has led to the development of numerous LiDAR SLAM frameworks that significantly enhance both accuracy and efficiency. In LiDAR SLAM, pose estimation is achieved by aligning incoming scans with the existing map. This process involves associating scan points with the map and optimizing the pose by minimizing the overall distance between the points and geometric elements. Data association relies on the similarity of local geometric information, with the distance metric being weighted according to the corresponding uncertainty. Therefore, the accurate representation and management of local geometric information, along with effective point cloud uncertainty analysis methods, are essential for improving the precision and reliability of pose estimation. This study begins with an overview of recent advancements in LiDAR SLAM and then explores these two critical factors that influence the accuracy and efficiency of system state estimation.

Early research in LiDAR SLAM primarily focused on developing effective constraints to improve the accuracy of point cloud registration, where odometry estimation is essentially equivalent to continuous point cloud registration. LiDAR SLAM systems can be categorized into non-feature- and feature-based methods, depending on whether they extract geometric features. Both approaches emphasize the crucial role of accurately representing local geometric information to ensure the effectiveness of these constraints. Feature-based methods focus on extracting local geometric elements from the input point cloud for precise registration, while also adopting efficient strategies to maintain and update the parameters of these geometric elements within the map.

In representing and managing local geometric information within point cloud, balancing accuracy and efficiency remains a major concern in LiDAR SLAM research. Current trends include representing input scans using single-point coordinates and characterizing map local regions through geometric statistics. For map management, incremental and scale-adaptive data structures have garnered significant attention due to their efficiency and accuracy, becoming central topics of ongoing research.

As research has advanced, developing an odometry estimation system that balances accuracy and efficiency has become a priority. Tightly coupled LiDAR-inertial odometry (LIO) systems optimize the system state by integrating pose and IMU biases on the manifold, enhancing the fusion of LiDAR and IMU data and resulting in superior performance in practical applications.

Recently, some studies have introduced point cloud uncertainty analysis methods into the registration process by examining the sources of errors within the LiDAR SLAM systems, thereby achieving a reasonable weighting of the distance metric. This review explores existing LiDAR SLAM systems that utilize point-wise uncertainty models, which enhance the system's reliability and robustness compared to simply applying white Gaussian noise in the observation function, particularly in complex environments. Current research is focused on developing point-wise uncertainty models based on LiDAR measurements, the characteristics of target surfaces, and the properties of the SLAM system. In addition, some studies have investigated the mechanisms of uncertainty propagation within LiDAR SLAM systems to further improve efficiency.

To assess the effects of representing and managing geometric information and determine the impact of point cloud uncertainty analysis methods on the accuracy and efficiency of LiDAR SLAM systems, we evaluated open-source LIO systems using public datasets such as NTU VIRAL, M2DGR, and Newer College. Our comparative experiments revealed significant insights. Notably, maps that utilize statistical methods to represent local geometric information demonstrate superior accuracy. However, this improved accuracy is accompanied by increased computational complexity. In addition, integrating a well-constructed uncertainty model further enhances the accuracy of trajectory estimation.

Balancing the precision and efficiency of local geometric information representation and management within LiDAR SLAM systems remains a central focus of research efforts. The development and implementation of uncertainty models are critical, as they influence the weighting of the loss function and have thus drawn increasing attention from the research community. However, few representative achievements have emerged in the SLAM community. Thus, designing an efficient uncertainty propagation method combined with a comprehensive uncertainty model remains a major challenge in LiDAR SLAM.

With the acceleration of industrial modernization and urbanization, soil heavy metal pollution caused by human activities has become an increasingly severe environmental challenge that cannot be ignored around the world. Under normal circumstances, heavy metals are not easily dissolved in water in soil and are not easily degraded by microorganisms in the soil. Excessive accumulation of heavy metals in the soil will produce toxicity to plants and affect their normal growth and development. At the same time, heavy metal pollution may also pollute groundwater, affect the quality of drinking water and the health of aquatic ecosystems, and pose a threat to biodiversity, soil health and human health. National standards for soil Cu element analysis include flame atomic absorption spectrophotometry and wavelength dispersive X-ray fluorescence spectrometry. Although these methods offer high detection accuracy, they involve complex sample preparation and require advanced equipment, which limits the ability to analyze different metal elements anytime and anywhere. The aim of this study is to develop an efficient and sensitive method for detecting Cu in soil. By using chelating resin as enrichment matrix, the interference of other elements in soil can be reduced. The sensitivity of heavy metal detection is improved by using spatially constrained enhancement mechanism. This study hopes to significantly improve the detection ability of laser-induced breakdown spectroscopy (LIBS) to Cu in soil by combining spatially constrained LIBS with resin enrichment pretreatment technology, and provide an effective method for the treatment of soil heavy metal pollution.

In this study, resin enrichment technique and spatially constrained LIBS analysis method are combined. First, a specific type of chelating resin with high selectivity and strong adsorption capacity for Cu element is screened to maximize the enrichment of Cu ions in soil samples and effectively eliminate the interference of other elements. Second, the key experimental parameters are optimized by LIBS to determine the optimal experimental conditions and reduce the impact of unknown factors on the accuracy and detection sensitivity of the calibration model. Then, the influence mechanism of spatial constraint on the formation, expansion and spectral characteristics of LIBS plasma is deeply analyzed, and a customized spatial constraint device suitable for soil Cu element detection is designed and manufactured. Through comparative testing of different design schemes, the optimal device that can significantly improve the strength and stability of LIBS signal is selected. In the next step, the optimized LIBS experimental conditions and space constraint device are used to conduct quantitative analysis of Cu elements in enriched soil samples, and a stable and reliable calibration model is established to ensure the accuracy and repeatability of measurement results. In addition, the optimized method is applied to real soil samples to evaluate its stability and applicability under complex environmental conditions.

The spatially constrained LIBS technique combined with the resin enrichment method achieves remarkable results in improving the detection performance of Cu elements in soil. This method reduces the potential interference of other unknown elements on the detection results (Fig.3), and also realizes a double leap in detection sensitivity and quantitative analysis accuracy by introducing a spatial constraint mechanism. When no spatial constraint is applied, the linear correlation coefficients of Cu I 324.75 nm and 327.39 nm lines are 0.977 and 0.981, respectively, showing a good linear relationship. However, after the introduction of spatial constraint optimization, the linear correlation coefficients of these two key spectral lines jump to 0.986 (Fig.11), marking a significant improvement in detection accuracy. At the same time, the detection limit (LOD) of Cu element also decreases significantly, from the original 1.368 mg/kg and 1.062 mg/kg to the optimized 0.807 mg/kg and 0.617 mg/kg, respectively (Table 1). In addition, in the practical application verification, the recovery rates of GBW7451 and GBW7456 standard samples are tested, and the results show that the recovery rates are stable in the range of 96.43% to 98.66% and 93.40% to 104.58%, respectively, which proves the high accuracy and repeatability of the technology in the actual soil sample detection (Table 2).

In this paper, chelating resin is used as the matrix material and the LIBS combined with space constraint is used to realize the high-precision quantitative analysis of Cu in soil. By optimizing experimental parameters and data processing, an accurate relationship model between Cu mass fraction and LIBS signal intensity is established. The LOD values of Cu element in soil samples are 0.807 mg/kg and 0.617 mg/kg (far less than the predicted value of soil risk), and the determination coefficients are 0.986. It has a lower detection limit and a higher correlation coefficient. In this study, the detection sensitivity of Cu in soil and the accuracy of quantitative analysis are effectively improved through the method of spatially constrained LIBS combined with resin enrichment, which provides a new and effective way for soil heavy metal pollution monitoring. Future studies can further explore the application potential of this method in other heavy metal elements and different types of soil, further promoting the widespread use and development of LIBS technology in environmental science.

Deep mineral resource exploration technology is affected by problems such as complex geological conditions and difficulties in remote detection, thus rendering it impossible to perform conventional mineral exploration in inaccessible areas. Therefore, remote detection methods must be developed urgently. Laser-induced breakdown spectroscopy (LIBS) offers the advantages of in-situ, noncontact, and multi-element simultaneous detection and can be applied broadly in remote material detection. However, the effects of the system parameters have not been comprehensively investigated, and most studies have focused on classification instead of quantitative analysis. The experimental parameters must be further optimized during remote detection to improve the remote detection capability. A remote LIBS detection system with variable focus based on a Galileo-type telescope is proposed to understand the effects of detection distance, delay time, and laser energy on plasma emission intensity. Subsequently, a parameter-optimization scheme is proposed. The quantitative performance of the remote LIBS system at different detection distances is evaluated using standard-curve and multivariate linear fitting methods. The results indicate improvement in the detection accuracy of remote LIBS measurements, which benefits field applications.

A remote LIBS detection system based on a Galileo-type telescope is designed. A coaxial optical path, in which laser focusing and signal acquisition share the same optical path, is utilized to render the system more compact. The focusing performance of the system is simulated using the Zemax software. The Nd∶YAG all-solid-state laser with a fundamental wavelength of 1064 nm and a pulse width of 10 ns is used as the excitation light source. The outgoing pulsed laser beam passes through a dichroic mirror into the Galileo-type telescope and is then focused onto the surface of the target to generate plasmas. The focus position of the laser is adjusted by varying the distance between the concave and convex lenses, thus enabling a detection range from 0.5 m to 5.0 m. The plasma emission obtained by the Galileo-type telescope, followed by the reflection through the dichroic mirror, is coupled to the transmission fiber through a convex lens with a focal length of 38.1 mm. Plasma spectra are obtained using a spectrometer with a wavelength range of 180?900 nm and a spectral resolution of 0.3 nm. The laser is operated in the internal trigger mode, and the spectrometer is triggered by the laser-pump synchronization signal, thus achieving timing control of the detection system. Aluminum alloy targets are selected for this experiment. Quantitative analyses are performed using the standard-curve method and multivariate linear fitting method; subsequently, the results are compared to determine the detection accuracy of the system.

Zemax simulations show that the laser-focusing spot size increases with the focusing distance (Table 1). Abundant spectral information is acquired from the typical LIBS spectral lines of copper?nickel?magnesium?aluminum alloy targets (Fig. 4). Time-resolved emission spectra of Ni I 352.45 nm, Al I 396.15 nm, Mg I 518.32 nm, and Cu I 521.82 nm at different detection distances are observed (Fig. 5). Although the line intensities are weak at a detection distance of 5.0 m, the characteristic emission spectra are clearly displayed (Fig. 6). Both the continuum background emission and characteristic emission of the spectra decrease with plasma evolution, resulting in a decreasing trend of plasma emission with a detection delay from 0 ns to 5000 ns (Fig. 7). An optimal detection delay of 200 ns is selected to obtain characteristic spectra with a high line intensity and favorable signal-to-noise ratio. The line intensity of each element increases with the laser energy. When the laser energy exceeds 80 mJ at a distance of 0.5 m, the line intensities saturate owing to the plasma shielding effect (Fig. 8). The spectral line intensity shows an approximate exponential attenuation as the detection distance increases from 0.5 m to 5.0 m at the laser energy of 80 mJ (Fig. 9). This is primarily because the focusing spot size increases with distance, which reduces the power density and degrades the laser ablation, thus weakening the obtained plasma signal intensity. Quantitative analyses are performed using the standard-curve method and multivariate linear fitting method, followed by a comparison of the prediction accuracy (Fig. 10). A mass fraction of 9% is selected for prediction and validation, and other mass fractions are used for training to establish calibration curves. The coefficients of determination (R²) of the calibration models at different distances exceed 0.989, and the average relative errors (AREs) of the predictions range from 5% to 8%. The AREs calculated using multivariate linear fitting method are less than 4%. This indicates that the prediction results obtained using multivariate linear fitting method are more similar to the reference values compared with those obtained using the standard-curve method. This study demonstrates the excellent qualitative and quantitative performances of a remote LIBS system, even at a detection distance of 5.0 m.

In this study, we investigate the qualitative and quantitative performances of metals using remote LIBS. A remote LIBS detection system using a coaxial optical path based on a Galileo-type telescope that can achieve substance component analysis within a distance of 0.5?5.0 m is designed. Zemax simulations of the focusing performance show that the laser-focusing spot increases with the focusing distance. The copper?nickel?magnesium?aluminum alloy target is selected to investigate the effects of the detection distance, delay time, and laser energy on the plasma emission intensity and the quantitative analytical capability of remote LIBS. The results show that the plasma emission decreases under a detection delay from 0 ns to 5000 ns, and that the line intensity of each element increases as the laser energy increases from 20 mJ to 250 mJ. The line intensities exhibit an approximately exponential attenuation with increasing detection distance. More importantly, the quantitative analytical performance of the LIBS system at different distances is evaluated based on six aluminum alloy targets using the standard-curve method and multivariate linear fitting method. A mass fraction of 9% is selected for prediction and validation, and other mass fractions are used for training to establish calibration curves. The R^{2values of the calibration models obtained at different distances exceed 0.989, and the AREs range between 5% and 8%. The AREs calculated using multivariate linear fitting method are less than 4%, thus proving that the system offers excellent qualitative and quantitative analytical capabilities within the detection range of 5.0 m. This study provides an experimental basis and data support for the optimization of remote LIBS equipment and demonstrates the significant potential of LIBS technology for remote qualitative and quantitative measurements.}

Fluorescence detection technology plays an indispensable role in biomedical analysis owing to its rapid speed and high accuracy. With the continuous advancement of fluorescence detection technology towards a broader range of types, faster speeds, higher accuracy, and greater integration capabilities, the number of channels for fluorescence detection equipment has gradually increased from 2?3 to 4?6. The utilization of multiple detection channels allows the simultaneous monitoring of various targets using different fluorescent dyes or viruses, thereby enhancing efficiency and reliability while ensuring precise results and significantly reducing overall detection time. The incorporation of multi-passband filters effectively reduces the optical path volume, minimizes the need for numerous individual filters, and enables seamless integration of equipment, which is an effective approach for achieving multi-channel fluorescence detection.

The working band of the quad-passband filter investigated in this study spans from 300 nm to 1100 nm; therefore, the fused quartz material is meticulously chosen as the substrate. When selecting materials with a high or low refractive index, their optical and chemical properties must be carefully considered. In the visible region, TiO₂, Nb₂O₅, and Ta₂O₅ are commonly employed materials with high refractive index, whereas SiO₂ remains the prevalent choice for materials with a low refractive index. Given that the passband range includes the 390 nm band, it is imperative to select materials that exhibit no absorption within this range. Consequently, Ta₂O₅ is utilized as a material with high refractive index, and SiO₂ serves as an optimal choice for a low-refractive-index material. After thorough analysis of the preceding data, it becomes apparent that precisely regulating and positioning the central wavelength and full width at half-maximum of the optical coating structure presents a primary challenge in designing the quad-passband filter. When employing cyclic nesting theory, the full width at half-maximum of the multi-passband expands as the central wavelength of the passband increases. In this study, it is observed that at longer wavelengths, the full width at half-maximum of the third passband is smaller than those of both the first and second passbands at shorter wavelengths. Consequently, formulas (13) and (14) are inapplicable for optical coating system design in this work. Therefore, we propose an innovative double-combination cyclic nesting model to address the aforementioned issues, which introduces a new array of film system structures into the existing single-cycle nested film system structure. This enables the simultaneous adjustment of parameters for both groups of film systems and simplifies the determination of the multi-passband position and full width at half-maximum. By adjusting the parameters in formula (13), the spectral curve of the proposed initial quad-passband filter is shown in Fig. 7. The design results exhibit an astonishing resemblance between the initial structure and our target spectrum. After optimization with the Macleod software, we obtain the design result of a quad-passband filter with a reasonable film structure and spectral performance. Figure 8 illustrates the transmission spectrum and blocking curve, where the spectral transmittance curve exhibits negligible variation at an error of 0.2%. Based on these results, the final structure of the quad-passband filter is determined as follows: 1.34H1.5L1.5H0.97L1.18H……0.54H0.28L2.91H0.2L0.22H0.45L, comprising a total of 174 layers with a cumulative thickness of 15.7 μm. The selection of magnetron sputtering technology for film preparation is based on the desired total thickness and number of layers in the designed structure. In this study, we utilize the sputtering coating equipment, employing tantalum and silicon as experimental targets. The parameters used for the preparation of Ta₂O₅ and SiO₂ are listed in Table 1. An optical control system is used to monitor and achieve a precise film thickness, thereby facilitating the preparation of a quad-passband filter.

We propose a process method that combines optical and time control. During the deposition of highly sensitive layers, the growth rate is determined based on the average rate of the previous layers, aiming to mitigate the thickness errors of highly sensitive layers, which can optimize the spectral curve. Figure 8 presents spectral curves of the filter prepared after implementing these improvements. The test spectrum of the quad-passband filter demonstrates exceptional conformity with the design. To suppress optical signals beyond the passband range effectively, an extended blocking film should be applied on the opposite side of the filter. However, further elaboration is omitted because of the straightforward structure. Based on our calculations, the passbands possess central wavelengths of 391.2, 479.5, 553.3, and 637.7 nm, accompanied by corresponding full widths at half-maximum of 31.8, 31.5, 24.2, and 31.7 nm, respectively; these values all satisfy the spectral requirements of this work.

In summary, we develop a double-combination cyclic nesting method to design a quad-passband filter that enables precise control over the passband position and bandwidth of the quad-passband filter by simultaneously adjusting the parameters of two Fabry-Perot multi-cavity structures. The integration of optical and rate control enhances the deposition accuracy of the sensitive layer in film production. Furthermore, by applying ion bombardment and preheating techniques to the substrate, the aggregation density and refractive index consistency are improved, thereby optimizing the spectral performance. The resulting quad-passband filter exhibits exceptional characteristics, including super-high peak transmittance (≥96%) for each passband within the range of 300?1100 nm, as well as an excellent blocking ability. It is successfully subjected to rigorous environmental testing, demonstrating its strong adaptability to various environments. This remarkable quad-passband filter has significant potential for applications in fluorescence detection.

Optical films are crucial in integrated optics, optical instruments, and laser systems; they offer functions such as high reflection, anti-reflection, and polarization control. To realize these functional optical films, materials with varying refractive indices must be used; however, the availability of natural materials with a specific refractive index is limited. A promising approach to modulate the refractive index is by using material mixtures. Silicon dioxide (SiO₂) and hafnium dioxide (HfO₂) are widely recognized as low and high refractive index materials, respectively. In the domain of laser thin films, the laser damage threshold can be significantly enhanced by optimizing the mixing ratio of HfO₂ and SiO₂ in HfO₂-SiO₂ hybrid films. This study aims to establish a comprehensive correlation among the microscopic properties—such as chemical composition, binding energy, and porosity—and the macroscopic properties, including density, hardness, crystallization temperature, and mixing ratio. By analyzing these relationships, we seek to elucidate the effect of material composition on the performance characteristics of HfO₂-SiO₂ hybrid thin films.

Hafnia-silica (HfO₂-SiO₂) mixed coatings with various ratios are fabricated on fused silica substrates via electron beam co-evaporation. The density, hardness, chemical composition, and crystalline state of the HfO₂-SiO₂ mixed coatings are analyzed via X-ray diffraction (XRD), nanoindentation, X-ray photoelectron spectroscopy (XPS), and time-of-flight secondary ion mass spectrometry (TOF-SIMS).

The results show that a SiO₂ atomic fraction of 13% in the HfO₂-SiO₂ mixed coatings yields the highest hardness and density among the seven samples measured (Table 2, Fig. 2, and Fig. 3). At this atomic fraction, only physical mixing is observed in the mixed coatings. However, when the SiO₂ atomic fraction exceeds 13%, the hardness and density decrease with increasing SiO₂ atomic fraction. Analysis reveals the presence of physical mixing and the formation of the HfSiO₄ compound in the mixed coating (Figs. 3, 6, and 7). Furthermore, minimal silicon doping does not significantly elevate the crystallization temperature of the samples, although the crystallization temperature increases gradually with the SiO₂ atomic fraction (Fig. 5).

The hardness and density of HfO₂-SiO₂ hybrid films are intricately linked to the microscopic columnar structure of HfO₂. When the atomic fraction of SiO₂ is 13%, smaller SiO₂ particles infiltrate the pores of HfO₂, thus increasing the film density and achieving the maximum hardness and density for the hybrid films. However, beyond this atomic fraction threshold of 13% , the hardness decreases as the SiO₂ content continues to increase.

Furthermore, the crystallization temperature of pure SiO₂ exceeds that of pure HfO₂, thereby indicating that incorporating SiO₂ can elevate the crystallization temperature of the hybrid films. Notably, a small proportion of SiO₂ does not significantly affect the crystallization temperature. At 13% (SiO₂ atomic fraction), the mixed film exhibits a physical amalgamation of HfO₂ and SiO₂. However, when the SiO₂ content surpasses a certain percentage, the mixed film transitions from being merely a physical mixture to one that incorporates the silicate compound HfSiO₄.

The binding energy peaks for hafnium (Hf), silicon (Si), and oxygen (O) in the HfO₂-SiO₂ hybrid films vary depending on the proportions of the constituent materials. This phenomenon is due to changes in the electron cloud density surrounding each element, which is reflected in the shifts of the binding-energy peak positions. As the Si content decreases and the Hf content increases, the binding energies of Hf, Si, and O diminish, which suggests an increase in the electron cloud density around these elements, thereby indicating a greater number of electrons.

SiO₂ antireflective films prepared using a Sol-gel method are an important feature of high-power laser facilities, and a significant demand exists for third-harmonic porous SiO₂ antireflective films in terminal optical components. Due to the porous nature of SiO₂ antireflective films, their properties are easily affected by organic pollutants and moisture water molecules during facility operations. To ensure the basic properties of third-harmonic SiO₂ antireflective films, further improving the stability of the films to reduce the replacement frequency of the third-harmonic components and increasing the overall operational efficiency of the facilities are necessary.

SiO₂ Sol was prepared using tetraethyl orthosilicate as a precursor, ethanol as a solvent, and ammonia as a catalyst. SiO₂ antireflective films with enhanced transmittance at the third harmonic were then obtained by dip-coating following SiO₂ Sol dilution (Fig. 1). An optimized third-harmonic porous SiO₂ antireflective film (3AR+5MR) was prepared by surface cladding with a small-particle silica Sol containing methyl groups, and its properties were compared with those of a third-harmonic SiO₂ antireflective film (3AR) prepared by traditional chemical atmospheric treatment using ammonia and hexamethyldisilazane. The films were analyzed based on their optical performance, laser damage threshold performance, and environmental stability.

Results and discussions The initial optical performance of the 3AR+5MR film shows that the peak transmittance is greater than 99.5% at 370 nm, which is close to that of the 3AR film (Fig. 2), and the uniformity of the films is good (Fig. 4). Although a thin layer is present on the surface of the 3AR+5MR film, it still maintains the characteristics of high porosity and achieves efficient antireflection, whereas the surface pore size tends to be more uniform (Fig. 3). The water contact angle of the 3AR+5MR film reaches nearly 120°, and the change trend affected by water vapor is relatively slow because the interface layer of the 3AR+5MR film protects the porous film from the effects of water vapor better than that of the 3AR film (Fig. 5). The 3AR+5MR film is more stable than the 3AR film in terms of antipollution and moisture resistance, and the degradation of the various properties is slower (Figs. 6 and 7). The surface cladding layer can reduce the effects of organic gas molecules and water vapor molecule intrusion on the optical properties of the film. The surface roughness of the 3AR+5MR film is approximately 9 nm, which is comparable to that of the 3AR film (Figs. 8 and 9). Analysis of the laser damage performance shows that the initial zero probability laser-induced damage threshold measured by a 1-on-1 method is 18.9 J/cm² (3AR+5MR, 355 nm, 8.8 ns) and 19 J/cm² (3AR, 355 nm, 8.8 ns) (Fig. 10). Simultaneously, the preparation process time of the 3AR+5MR film is shorter than that of the 3AR film, which can effectively improve the production capacity of SiO₂ antireflective films for large optical components.

A high demand exists for third-harmonic SiO₂ antireflective films applied to large-aperture optical elements in high-power laser facilities. In this study, a modified third-harmonic SiO₂ antireflective film with excellent properties and environmental stability was fabricated using a surface-cladding process. Results show that the preparation efficiency of the SiO₂ antireflective films is significantly improved, which helps to increase the batch production capacity of SiO₂ antireflective films for large optical components whenever a new large high-power laser facility is constructed.