The projection sequence of Hadamard speckle patterns directly influences the image reconstruction quality and efficiency of computational ghost imaging under undersampled conditions. Optimizing the speckle sorting strategy is an effective approach to achieving high-quality imaging at low sampling rates.

This study aims to address the oscillation of quality metrics observed during the sampling process of traditional sorting strategies and to further enhance the signal-to-noise ratio and convergence stability within the low-sampling-rate regime.

A recursive cross (RC) sorting strategy based on the Hadamard basis is proposed. By inversely deconstructing hierarchical subspaces and utilizing an even-index mapping mechanism, this method interleaves and reorganizes speckles with orthogonal texture features, thereby disrupting the continuous accumulation of unidirectional features in the sampling sequence. Numerical simulations under both ideal and Gaussian noise environments, along with optical experiments, were conducted to validate the proposed method.

Simulation results demonstrate that the RC strategy effectively eliminates the oscillation of evaluation metrics observed in Russian Dolls sorting as the sampling rate increases across the full 0–100% range, achieving a smooth evolution and robust convergence of imaging quality. Particularly in the low-sampling-rate range of 0–10%, the peak signal-to-noise ratio of the reconstructed images shows a maximum improvement of approximately 101.7% compared to Hadamard natural sorting and 11.4% compared to laser model speckle sorting, with a maximum gain of about 3.4 dB.

By optimizing the sampling path of spectral energy, the RC sorting strategy improves the data acquisition efficiency of ghost imaging, potentially offering an effective technical pathway for realizing rapid and real-time ghost imaging applications.

The W-band constitutes a critical atmospheric window in the millimeter-wave spectrum, with significant importance for advanced applications such as high-capacity communications, high-resolution imaging, and high-precision sensing. As essential components within core millimeter-wave transmitter and receiver systems, filters fundamentally determine transceiver performance. However, conventional designs frequently face challenges in simultaneously achieving high electrical performance and favorable manufacturability, representing a key obstacle in contemporary W-band filter development.

This work aims to develop a low-loss, low-order, and readily fabricable waveguide quasi-elliptic bandpass filter for the W-band. The goal is to maximize structural simplicity while maintaining high performance, thereby addressing the requirements of next-generation highly integrated transceiver systems.

The proposed filter employs a novel H-plane offset magnetic coupling configuration, which simplifies the input–output coupling mechanism. Guided by quasi-elliptic filtering theory, transmission zeros are generated on both sides of the passband through the excitation of TE₂₀₁/TE₁₀₂ and TE₃₀₁/TE₁₀₂ hybrid modes in two respective resonant cavities, resulting in enhanced out-of-band suppression. The filter is implemented in a split-block architecture and fabricated via high-precision computer numerical control (CNC) milling.

Measured results demonstrate an operational passband from 91.5 GHz to 98 GHz, corresponding to a 3 dB fractional bandwidth of 7%, with an in-band insertion loss as low as 0.4 dB and a return loss greater than 15 dB. Except for a slight deviation observed at the upper band edge, the experimental data show strong agreement with simulation, confirming the design’s manufacturability, integration compatibility, and high-frequency performance.

A compact, low-loss W-band quasi-elliptic filter has been successfully realized using only two hybrid-mode cavities. The presented design exhibits notable advantages in terms of fabrication ease, integration suitability, and electrical performance, providing a viable solution for advanced millimeter-wave system applications.

With the rapid development of low-Earth orbit (LEO) satellite communications, there is a pressing need for circularly polarized phased arrays that offer wide-angle scanning capability while maintaining a low profile, which remains a significant challenge in current designs.

This study aims to design a low-profile, wide-beam circularly polarized antenna element and its corresponding wide-angle scanning array to address the limitations of narrow scan angles and high profiles in existing solutions.

A double-layer antenna element was designed, utilizing corner perturbation and cross-slots to achieve left-hand circular polarization, while the beamwidth was broadened via an upper parasitic structure and metallic posts based on pattern superposition. A 4×4 array was constructed by rotating these elements, with annular open slots integrated into the ground plane to suppress mutual coupling.

The proposed antenna element exhibits a 3-dB axial ratio beamwidth greater than 175°, a gain beamwidth of 120°, and a profile of only 0.07λ₀. Simulations of the 4×4 array demonstrate a scan coverage of ±60°, with axial ratio consistently below 2 dB and a stable gain fluctuation of 3.38 dB throughout the scanning range.

The designed antenna and array effectively achieve wide-angle circularly polarized scanning with low profile and stable performance, offering a promising solution for LEO satellite communication terminals and other integrated systems requiring wide spatial coverage.

The study of multi-scale turbulence and related anomalous transport under high-performance plasma operation remains an important topic in the research of magnetic confinement fusion. The parameter range of plasmas in the tokamak experiment determines that far-infrared laser collective scattering is the optimal diagnostic method for multi-scale turbulence diagnostics.

This paper discusses the overall design parameters of the diagnostic system and provide a detailed introduction to the design of the windows for the multi-scale turbulence collective scattering (MSTCS) diagnostic system on the HL-3 Tokamak.

The laser beam entrance window of the MSTCS diagnostic system is located in the mid-plane port #6 of the HL-3 tokamak, and the scattered light beams exit from the windows in the mid-plane port #12. The design aspects of the windows include the material selection, clear aperture calculation, window thickness design, mechanical design, and surface quality requirements. Several interrelated factors need to be considered in the design process. These include the diagnostic wavenumber range, wavenumber resolution, wavenumber purity of the scattering data, laser beam transmission coefficients, and the requirements for vacuum sealing and safety.

On the basis of these considerations, a corresponding design scheme was formulated. The technical details of the analysis and design process as well as the design results are presented.

The MSTCS diagnostic system has been successfully installed on HL-3, and preliminary experimental data confirm the vacuum safety and optical performance of the diagnostic windows, thereby validating the overall design.

In recent years, magnetized laser-plasma research has gained significant importance in multiple frontier fields such as magneto-inertial confinement fusion, magnetic reconnection, collisionless shocks, and magnetohydrodynamic instabilities. Pulsed magnetic field devices have become the mainstream experimental approach, as they can generate magnetic field parameters that meet experimental requirements in terms of strength, spatial scale, and duration. Such devices have been integrated into multiple large-scale laser facilities worldwide, and our research group has also successfully developed several pulsed magnetic field systems adaptable to laser setups of different scales. However, existing devices still face two major challenges: first, strong electromagnetic interference affects data acquisition and equipment safety; second, advances in physical experiments demand higher magnetic field strengths.

This study presents a novel coaxial-structure pulsed magnetic field device, designed to optimize the circuit configuration for suppressing electromagnetic interference (EMI) and enhancing magnetic field strength, thereby providing a more reliable high-field environment for magnetized laser-plasma experiments.

The experiment employs an all-coaxial architecture to enhance electromagnetic compatibility. Multiple soft coaxial cables are connected in parallel to link a 5 μF high-voltage coaxial capacitor with a rigid coaxial transmission line inside the vacuum target chamber, thereby minimizing system inductance.

At 40 kV charging voltage, a discharge current with a peak intensity of 105 kA, a rise time of 1.2 μs, and a flat top width of 1.4 μs is produced, which generates an intense magnetic field of 22 T in the center of a three-turn magnetic field coil of 12 mm diameter. Compared with our previous pulsed intense magnetic field device, the present device can generate larger current and stronger magnetic field, while the free-space EM noise and potential jitter (voltage fluctuation) of the vacuum chamber are significantly reduced.

Experimental results demonstrate that the key performance of this device has reached the mainstream advanced level of international counterparts, such as relevant systems from the U.S. LLNL, France's LULI, and Germany’s HZDR. This device combines high magnetic field strength, microsecond-level flat-top stability, and low electromagnetic interference, providing precisely controllable strong magnetic field experimental conditions—previously difficult to achieve—for frontier research areas such as magneto-inertial confinement fusion, laboratory astrophysics, magnetohydrodynamic instabilities, and pulsed laser deposition coating.

Series resonant capacitor charging power supply is widely used in the field of pulse power due to its high efficiency, high power density, and short-circuit resistance. However, its traditional PFM constant current charging control method leads to significant charging losses and reduced efficiency, which is particularly prominent in the early stages of charging.

A multimodal hybrid constant-current charging control strategy is proposed to enhance both the charging efficiency and input power utilization.

This strategy achieves smooth transitions of charging voltage while reducing charging losses and improving efficiency through collaborative control of half-bridge mode (early charging stage), hybrid mode (mid charging stage), and full-bridge mode (late charging stage). In addition, the conversion of working modes is achieved by multiplexing power devices, which not only meets the requirements of high-voltage charging but also reduces system costs.

Based on this approach, a 650 V/1 A charging power supply prototype has been designed and built. Experimental results demonstrate that, compared to conventional PFM control, the proposed strategy significantly improves overall charging efficiency, achieving a maximum efficiency of 96.4%.

This method not only provides an effective solution for capacitor energy storage charging systems with high efficiency and low cost, but its modal switching mechanism is also transferable to the design of other resonant converters, demonstrating broad engineering applicability.

Simultaneous and accurate detection of multiple physical and biochemical parameters, such as refractive index (RI) and temperature, is critically important in complex sensing environments, including biological analysis and cancer cell detection. Photonic crystal fiber sensors based on surface plasmon resonance (PCF-SPR) have attracted considerable attention due to their high sensitivity and compact structure. However, achieving ultra-wide RI detection ranges, effective temperature compensation, and low cross-sensitivity within a single fiber platform remains a significant challenge, particularly when higher-order mode excitation and polarization selectivity are required.

The purpose of this study is to propose and numerically investigate a dual-channel PCF-SPR sensor capable of simultaneous RI and temperature sensing over an ultra-wide range, while achieving polarization-resolved mode excitation and reduced cross-interference between sensing channels.

An anchor-shaped asymmetric photonic crystal fiber with orthogonally polished semi-circular surfaces is designed. Gold (Au) and polydimethylsiloxane (PDMS) thin films are selectively deposited on different polished surfaces to construct two independent SPR sensing channels. Polarization-resolved excitation of high-order modes is achieved through structural asymmetry and selective coating. A full-vector finite-element method based on COMSOL Multiphysics is employed to analyze mode distributions, loss spectra, and resonance wavelength shifts. Key structural parameters, including air-hole geometry and metal-dielectric layer thicknesses, are systematically optimized to enhance plasmonic coupling strength and mode confinement.

Simulation results indicate that the x-polarized channel coated with Au and PDMS exhibits dual sensitivity to RI and temperature, whereas the y-polarized channel coated only with Au responds exclusively to RI variations of another analyte. The proposed sensor achieves an ultra-wide RI detection range from 1.21 to 1.44, with a maximum RI sensitivity of 14 500 nm/RIU. The temperature sensing range spans from −100 ℃ to 100 ℃, and a peak temperature sensitivity of 4 nm/℃ is obtained. Clear polarization-dependent resonance characteristics and effective channel decoupling are demonstrated.

The proposed dual-channel anchor-shaped PCF-SPR sensor combines ultra-wide RI detection, temperature sensing capability, and polarization-resolved selectivity within a compact fiber structure. Its high sensitivity, flexible channel configuration, and strong resistance to cross-interference make it a promising platform for real-time multi-parameter sensing in complex biological and chemical applications, such as cancer cell detection and biochemical analysis.

Laser self-mixing interferometry (SMI) is a highly sensitive and non-contact technique widely used for micro-displacement measurement. However, traditional displacement reconstruction methods typically involve complex phase unwrapping calculations, which increases computational difficulty and limits the efficiency of signal processing in practical applications.

This study aims to propose a novel micro-displacement reconstruction method for semiconductor laser SMI based on convolutional neural networks (CNN). The objective is to achieve direct and accurate reconstruction of micron-scale displacement while bypassing the tedious phase unwrapping process.

The proposed method involves segmenting the SMI signal and using the window-averaged displacement as the label for training the CNN. The architecture of the network consists of three sets of convolutional layers, pooling layers, and Rectified Linear Unit (ReLU) functions. Specifically, the convolutional layers are utilized to extract local displacement features from the SMI signal, the pooling layers are designed to compress feature information and enhance noise immunity, and the ReLU functions help highlight critical displacement features within the signal.

In theoretical simulations, SMI signals with 10 dB noise were input into the trained CNN, resulting in a displacement reconstruction RMSE of 5.3 × 10⁻⁸. In experimental tests, SMI signals containing system noise were processed by the network, yielding a reconstructed displacement RMSE of 2.1 × 10⁻⁷. The simulation and experimental results demonstrate consistent performance.

Both theoretical and experimental results indicate that the convolutional neural network can effectively achieve micron-level displacement reconstruction by analyzing the temporal segments of SMI signals. This method provides an efficient alternative for semiconductor laser self-mixing interference systems by eliminating the need for complex phase-based algorithms.

The reaction kinetics in lasers often involves a lot of excited state species. The mutual effects and numerical stiffness arising from the excited state species pose significant challenges in numerical simulations of lasers. The development of artificial intelligence has made neural networks (NNs) a promising approach to address the computational intensity and instability in excited state reaction kinetics (ESRK).

However, the complexity of ESRK poses challenges for NN training. These reactions involve numerous species and mutual effects, resulting in a high-dimensional variable space. This demands that the NN possess the capability to establish complex mapping relationships. Moreover, the significant change in state before and after the reaction leads to a broad variable space coverage, which amplifies the demand for NN’s accuracy.

To address the aforementioned challenges, this study introduced successful sequence-to-sequence learning from large language learning into ESRK to enhance prediction accuracy in complex, high-dimensional regression. Additionally, a statistical regularization method was proposed to improve the diversity of the outputs. NNs with different architectures were trained using randomly sampled data, and their capabilities were compared and analyzed.

The proposed method is validated using a vibrational reaction mechanism for hydrogen fluoride, which involves 16 species and 137 reactions. The results demonstrate that the sequential model achieves lower training loss and relative error during training. Furthermore, experiments with different hyperparameters reveal that variation in the random seed can significantly impact model performance.

In this work, the introduction of the sequential model successfully reduced the parameter count of the conventional wide model without compromising accuracy. However, due to the intrinsic complexity of ESRK, there remains considerable room for improvement in NN-based regression tasks for this domain.