Search Results (105)

Extreme noise severely degrades image quality in photon-limited imaging systems and challenges existing denoising methods. Classical total variation (TV) models rely on fixed local gradients and often introduce cross-edge smoothing, while deep learning methods may become unstable under extremely low signal-to-noise ratios. To address these limitations, we propose DSGR-Net, a hybrid denoising framework integrating Deformable Sparse-Gradient Regularization (DSGR) preprocessing with neural network restoration. The proposed DSGR model performs adaptive neighborhood regularization by selecting the eight smallest local gradients within a deformable neighborhood for sparse total variation compensation. This structure-aware strategy effectively suppresses noise while avoiding cross-edge diffusion and preserving fine image details. Experimental results on both simulated and real optical imaging data demonstrate that the proposed DSGR-Net achieves improved structural preservation and noise suppression compared with representative denoising methods. Full article

This work presents a laboratory prototype of an Electron-Bombarded Active Pixel Sensor (EBAPS) to investigate the effects of passivation film thickness on electron energy loss and bombardment gain. Through combined experimental characterization and numerical simulations, we systematically examine the correlations among accelerating voltage, passivation layer thickness, electron gain, and dead-layer energy dissipation. Experimental results show that the fabricated EBAPS achieves a spatial resolution of 18 lp/mm at an accelerating voltage of 8000 V. Reducing the passivation layer thickness from 70 nm to 30 nm decreases dead-layer energy loss from 2000 eV to 1000 eV. An optimized Monte Carlo model is developed to simulate electron penetration behaviors under different thicknesses and voltages, and its predictions are in good agreement with experimental data. This study confirms that thinning the passivation layer effectively lowers the required bombardment voltage and improves the long-term operational reliability of EBAPS devices. These findings offer both experimental evidence and theoretical guidance for substrate thinning and surface modification strategies in EBAPS development. Full article

Terahertz (THz) radiation generated through ultrafast transient photocurrent mechanisms has become a cornerstone of modern THz photonics, enabling broadband coherent emission with sub-picosecond temporal resolution. This review provides a comprehensive and mechanism-driven analysis of THz pulse generation via photo-Dember diffusion currents, surface depletion field acceleration, and biased photoconductive antenna architectures. We present a comprehensive comparative analysis of wide- and low-bandgap material platforms, including III–V, II–VI, and group IV semiconductors, as well as two-dimensional materials, topological insulators, and Weyl semimetals, highlighting how their intrinsic properties, such as band structure, carrier mobility, recombination dynamics, doping, and dielectric response, govern their THz emission efficiency, bandwidth, and spectral tunability. Special emphasis is placed on germanium (Ge), which has re-emerged as a highly promising THz source material owing to its high carrier mobility, long diffusion lengths, strain-tunable band structure, and CMOS compatibility. We highlight the roles of doping, strain-induced direct transitions, and several fabrication techniques in controlling the nonlinear photoexcited charge-carrier dynamics in Ge, thereby unlocking enhanced broadband THz performance. Finally, we explore the emerging application prospects of THz radiation, ranging from non-invasive security screening to biochemical sensing and archeological preservation. By bridging fundamental material science with scalable device architectures, this review outlines current challenges, highlights evolving opportunities in novel materials, and charts future directions towards integrated THz technologies. Full article

Ultraviolet remote sensing systems generally encounter the technical limitation of insufficient effective signal energy. Optical systems featuring a lightweight and compact layout are emerging as the mainstream research and development trend in this field. Varied-line-space (VLS) gratings can simultaneously achieve effective aberration correction and beam focusing in ultraviolet spectral imaging systems, enabling fewer system components and a simplified optical layout. On this basis, the modulation mechanisms of the groove distribution of planar VLS gratings for aberration correction and dispersion manipulation in the non-vacuum ultraviolet (non-VUV) band are thoroughly investigated. We elaborate on the theories concerning the line density function of VLS gratings based on phase distribution, and implement global optimization for the parameters of holographic gratings. The overall optical performance of the grating system is evaluated via ray tracing, which verifies the capability of VLS gratings to improve spectral resolution. We further perform optical design, device fabrication, and experimental validation using VLS gratings with a central groove density of 300 lp/mm. A spectral resolution of 0.345 nm is finally realized at the central wavelength of 300 nm. This work not only enriches the fundamental theories of VLS grating systems but also demonstrates that VLS gratings can significantly boost the aberration correction performance of ultraviolet spectrometers while adopting only a small number of optical elements. The theoretical conclusions are validated by measured data, and a complementary research framework integrating theoretical analysis and experimental testing is established. This study offers novel design ideas for hyperspectral and high-spatial-resolution spectral imaging systems. Full article

The modernization of traditional Chinese medicine (TCM) is significantly impeded by the elusive material basis of its meridian system and by a lack of objective, quantitative diagnostic standards. Recent breakthroughs in photonic technologies and optoelectronic chips offer transformative paradigms to address these systemic bottlenecks. This review systematically evaluates the complete academic and engineering chain of “Photonic TCM,” spanning fundamental mechanisms, optical diagnostics, advanced therapeutics, and core chip-level technologies. Specifically, we analyze how ultra-weak photon emission (UPE), two-photon microscopy, and infrared thermography can objectify meridian dynamics and acupuncture pathways. For clinical translation, laser acupuncture has emerged as a robust, non-invasive modality for managing disorders such as chronic pain and insomnia, supported by cumulative evidence-based data. At the device level, vertical-cavity surface-emitting laser (VCSEL)-based photonic computing chips enable ultrafast herbal medicine recognition, while flexible optoelectronics and lab-on-a-chip systems lay the technical groundwork for wearable neuromodulation. Crucially, this review concludes that the Photonic TCM paradigm is transitioning from isolated clinical validation to integrated engineering implementation. We identify biological tissue scattering and parameter heterogeneities as the primary bottlenecks. To navigate these challenges, we propose that the field’s future should converge toward edge-computing-driven wearable closed-loop systems and multi-dimensional optical big data ecosystems. Ultimately, these technological trajectories will steer TCM from an empirical discipline toward a data-driven, precise, and standardized medical science. Full article

Predicting the evolution of microstructure and field quantities under varying processing and loading conditions is a central challenge in computational materials science and metal additive manufacturing (AM). While deep learning (DL) methods offer ultra-fast prediction capabilities post-training, existing models often struggle with poor spatial and temporal extrapolation, high parameter burdens, and an inability to effectively integrate diverse conditioning parameters alongside high-dimensional input fields. To address these bottlenecks, we propose a novel conditional generative adversarial network (CPGAN), which is designed to seamlessly ingest both initial fields and governing condition parameters. The CPGAN framework offers three distinct advantages: (1) it accurately maps the combined effects of initial states and process conditions onto evolved fields; (2) it demonstrates robust extrapolation capabilities across diverse spatial and temporal scales, including the unique ability to natively generate high-resolution rectangular domains; and (3) it achieves superior predictive accuracy and training stability compared to standard convolutional baselines by effectively suppressing spurious artifacts. We validate CPGAN’s performance against rigorous physics-based ground truths across three representative engineering applications: porosity evolution in selective laser sintering (SLS), spatial distribution of 2D von Mises stress fields in solid structures, and the spatiotemporal evolution of grain growth. The results confirm that CPGAN is a highly adaptable and efficient surrogate model, capable of simulating continuous structural and morphological evolutions even when driven by highly non-uniform spatial or temporal kinetics. Full article

High-power laser diodes are extensively utilized in advanced optoelectronic systems. These devices typically operate under high-current injection conditions, under which intrinsic parasitic parameters become non-negligible and exert a substantial influence on their electro-optical response characteristics. Furthermore, when multiple single emitters are monolithically integrated into a linear array along the epitaxial-layer direction on a single substrate, additional parasitic elements are inevitably introduced. These parameters are critical for characterizing the output performance of high-power laser diodes. This paper presents the implementation of an equivalent circuit model for large-signal laser-diode operation within the Advanced Design System (ADS) computer-aided environment. The proposed model enables accurate simulation of the device’s operating-voltage waveform and optical-output-power response under both DC steady-state and pulsed-transient driving conditions, thereby achieving a coupled representation of electrical behavior and optical emission. Sensitivity analysis of various parasitic elements is performed to systematically evaluate their influence on output characteristics and device reliability. The results provide theoretical guidance for structural optimization and packaging design, offering new insights into future modeling and reliability assessment of high-power laser diodes. Full article

Microchannel plate gated framing camera is commonly used in inertial confinement fusion diagnostics. However, it is a vacuum electronic device with bulkiness and non-single-line-of-sight imaging. To reduce the size of the camera and achieve a single line of sight image, a CMOS image sensor composed of a pixel unit and a readout circuit is presented to form the framing camera. The CMOS image sensor has a 32 × 32 × 4 pixel array with ultrashort shutter-time and four-frame imaging. The pixel array and analog to digital converter (ADC) readout circuit are designed using a standard 0.18 μm CMOS process. The pixel array includes 5T structured pixel units, a voltage-controlled delay, a clock tree and the row decoding scan circuits. A temporal resolution of 65 ps for the pixel circuit is achieved. The ADC readout circuit is composed of a counter, a comparator, a ramp generator and a register, which operates at a sampling frequency of 24.41 kS/s. An effective number of bits of 11.3, a spurious free dynamic range (SFDR) of 73.4 dB, and a signal-to-noise ratio (SNR) of 70.0 dB for the ADC are achieved. The CMOS image sensor will provide a novel and important imaging method for the field of ultrafast science. Full article

To enable non-destructive quantitative characterization of constituent content in C/C–SiC ceramic-matrix composites, this study develops a physics-guided framework based on multispectral photon-counting X-ray detection. In practical photon-counting measurements, multispectral attenuation features are jointly distorted by detector-response non-idealities, including charge sharing, K-escape, and finite energy resolution, as well as by beam-hardening effects from the polychromatic X-ray source. To address this coupled problem, a Geant4 11.2-based detector-response model was incorporated into a unified correction workflow together with beam-hardening compensation, so that physically consistent multispectral attenuation vectors could be recovered for subsequent constituent inversion rather than merely for spectrum restoration. On this basis, a fine-grained theoretical database covering different SiC mass fractions was established, and quantitative constituent inversion was achieved by matching the corrected attenuation features to the database. Experimental results show that the proposed framework effectively suppresses thickness-dependent bias in attenuation measurements and yields an average relative error below 3% for pure aluminum. For C/C–SiC composites, the SiC mass fraction can be quantified with an accuracy better than 3 wt%. These results demonstrate that the proposed method provides a practical non-destructive route for constituent-content characterization in heterogeneous ceramic-matrix composites and is valuable for manufacturing quality control and in-service assessment. Full article

Baseline correction of Raman spectra is a critical step for achieving high-precision quantitative analysis. However, the presence of complex background noise, nonlinear baseline drift, and spectral peak distortion due to peak overlap in real spectral data severely limits the performance of conventional correction methods. To better preserve spectral details, this study proposes an improved penalized least squares method for Raman spectral baseline correction. Compared with common baseline correction approaches, the proposed method optimizes the iterative weight function through precise noise classification, significantly enhancing the algorithm’s flexibility. The traditional single smoothing parameter is extended into a smoothing vector, and a classification strategy consistent with that of the penalty parameter is adopted, enabling synchronous optimization and coordinated adjustment of both during iteration. Furthermore, based on the physical constraints of Raman spectra, the algorithm eliminates non-physical solutions that may arise in traditional iterative processes, ensuring the fidelity of the corrected spectra. Experimental results demonstrate that the proposed method exhibits strong robustness under various noise conditions and significantly improves correction accuracy. Full article

High quality factor (Q factor) resonant metasurfaces enable efficient mid-infrared (MIR) upconversion, yet their narrow operating bandwidths severely limit practical broadband detection and imaging applications. Although high Q magnetic toroidal dipole (MTD) modes exhibit outstanding momentum space ($k$-space) stability in linear optics, their application in nonlinear processes has primarily been confined to degenerate second-harmonic generation (SHG), leaving complex non-degenerate processes such as sum-frequency generation (SFG) largely unexplored. Here, we propose a tunable MIR upconversion platform based on an all-dielectric gallium phosphide (GaP) dimer metasurface. Breaking the in-plane symmetry to trigger Brillouin zone folding excites robust MTD quasi-guided modes (MTD-QGM), tightly confining the locally enhanced optical fields within the highly nonlinear GaP nanostructure. Synchronizing this high Q resonance with a spatially overlapping pump mode yields an exceptional SFG conversion efficiency of $7.9\times {10}^{-4}$, successfully translating a 3101.8 nm MIR signal to the 903 nm near-infrared band. Crucially, the intrinsic $k$-space stability of the MTD-QGM enables continuous, broadband upconversion through simple angle tuning. This mechanism effectively overcomes the narrow-band limitations characteristic of typical symmetry-protected resonators, establishing a robust paradigm for room-temperature MIR detection. Full article

Lossless image compression is pivotal for deep-space exploration. Considering the requirements of deep-space exploration for a high compression ratio and real-time processing, traditional image compression algorithms have garnered significant attention. However, existing algorithms struggle with real-time processing speed and compression degradation in high-noise regions, failing to meet the throughput demands of next-generation sensors. To address these challenges, this paper proposes a high-throughput and noise-resilient lossless image compression architecture, named HT-NRC, for deep-space CMOS cameras. First, to overcome the throughput bottleneck, we introduce a parallel processing method, which is built on index-based dispatch and Reorder mechanism. This is achieved by dynamically distributing pixel streams into parallel cores and utilizing a Reorder Buffer for sequence restoration. Second, to mitigate low compression efficiency in noisy backgrounds, we present a Heterogeneous Dual-Path Coding scheme. This system adaptively separates structural information for predictive coding and stochastic noise for raw packing with Bit-Plane Slicing (BPS) strategy. The proposed architecture was implemented on a Xilinx Virtex-7 FPGA (Xilinx, Inc., San Jose, CA, USA). Operating at 100 MHz, the system achieves a processing throughput of 414.7 Mpixel/s and a high average compression ratio under deep-space image datasets, while consuming an estimated total on-chip power of only 2.1 W. Experimental results show that our proposed method substantially outperforms existing baseline methods. Specifically, compared to the optimized serial JPEG-LS implementation processing one pixel per clock cycle, our parallel architecture achieves an approximately 314.7% increase in processing throughput. Full article

Characterizing both the CO₂ distribution and wind dynamics in the Martian mesosphere and lower thermosphere is vital for planetary atmospheric science and mission planning. In this work, we propose a novel dual-channel passive limb-viewing imaging system designed to simultaneously observe partial CO₂ column density and line-of-sight (LOS) wind speed from ultraviolet and visible airglow emissions under dayside and terminator illumination conditions. A dichroic beam splitter separates the ultraviolet and visible channels, ensuring high optical throughput and independent optimization of both subsystems. The ultraviolet channel targets O(¹S) 297.2 nm emission, a well-established Martian limb emission driven by CO₂ photodissociation under solar Lyman-α flux. By applying narrow-band imaging and brightness inversion, this channel provides quantitative constraints on CO₂ column density with a stable and well-defined response function. In the visible channel, we introduce a lens array-based compact static Michelson interferometer optimized for the O(¹S) 557.7 nm green line emission, which has been observed in the Martian dayside limb, providing Doppler wind measurements in the 60–180 km altitude range. Radiative transfer simulations using Mars Climate Database indicate retrieval precisions of ±6~8% for CO₂ column density and better than ±5 m/s for wind speed within the primary emission layer (approximately 60–160 km) under representative dayside limb conditions. This dual-parameter remote sensing concept simultaneously constrains the composition and dynamics of the Martian mesosphere and lower thermosphere region, addressing a long-standing observational gap. The compact and modular design of the system makes it well suited for future Mars orbiter payloads under nominal dayside and terminator observation geometries, providing critical data for validating global circulation models and supporting future entry, descent, and landing system design. Full article

The versatile surface reconstruction mechanisms, tunable surface properties, and exceptional electron emission characteristics of SrTiO₃ films have garnered significant research interest. In this study, SrTiO₃ films were synthesized on n-Si(100) substrates via radio frequency magnetron sputtering. To evaluate the impact of thermal annealing, the as-deposited films underwent post-deposition annealing in an oxygen ambient at 600 °C, 800 °C, and 1000 °C for a duration of 2 h each. The structural, chemical, and secondary electron emission (SEE) characteristics of the SrTiO₃ films were characterized as a function of their high thermal process. Post-deposition annealing induced a significant improvement in crystallinity, which directly correlated with a heightened SEE yield (SEY). Furthermore, composition analysis revealed a marked stoichiometric reconfiguration at the surface, with the Sr:Ti:O ratio evolving from 1:0.32:1.14 to 1:0.22:0.94, suggesting a move toward an Sr-O terminated surface. The Sr-O terminated surface inherent to these SrTiO₃ films promotes efficient electron escape due to its reduced work function. Following a 1000 °C annealing process, the peak SEY undergoes a significant shift from 2.11 to 2.76, representing a thermal optimization of the SEE performance by approximately 30.8%. High-temperature annealing enhances the SEE performance of SrTiO₃ films, validating their significant potential for electron multiplication applications. This study provides a scalable pathway for developing highly efficient SEE materials with optimized crystalline and surface properties. Full article