Non-invasive, timely and accurate detection is of great significance for the early diagnosis and treatment of tumors. Raman spectroscopy has shown good application prospects in the field of tumor detection due to its advantages of non-destructive acquisition, high sensitivity and rapid detection. Several studies have given the principles of Raman spectroscopy for detecting cancerous tissues, however, this technique still has the limitations of weak signals and insufficient penetration depth and faces the challenge of improving its ability in detecting subcutaneous deep tumor signals for clinical applications. Spatially offset Raman spectroscopy (SORS) is a deep-penetration Raman spectroscopy, which reduces the signal interference in the surface layer in order to effectively obtain the spectral information of deep samples by physically shifting the spectral acquisition point with a certain distance laterally relative to the excitation point. However, most of the studies indicate that the detection depth of this technique in biological tissues is limited to 2 mm, far from being sufficient for the detection of deep-seated tumors, and the quantitative relationship between the detection depth and the spatial offset distance (Δd) lacks the support of experimental data. In this study, we conduct experiments based on a self-developed fiber optic Raman probe, and investigate the maximum detection depth of the fiber optic Raman probe detection technique by respectively using two acquisition modes of transmission and reflection. Based on the both modes, the SORS is introduced, and the quantitative relationship between Δd and the optimal detection depth is established. This study provides an experimental data support for the application of SORS in clinical tumor diagnosis, and provides a technical reference for the further optimization of Raman spectroscopy.

Raman spectra of pork adipose tissue (PAT) are collected under various experimental conditions based on a self-developed fiber optic Raman probe. First, the experimental optical paths of transmission and reflection modes are constructed (Fig. 2), then the PAT is cut into 3 mm-thick slices, and the samples are stacked layer by layer for spectral acquisition in both transmission and reflection modes until the maximum detection depth is obtained. Then, after obtaining the detection depths in the both Raman spectral acquisition modes, the SORS is introduced, and the experiments are carried out under different sample thicknesses with the Δd increment of 1 mm and the offset ranging from 1 mm to 6 mm, to obtain the Raman spectral data with different Δd in the both modes. Finally, the experimental spectral results are pre-processed and analyzed to summarize the experimental results.

The spectral data show a negative correlation between feature band Raman intensity and tissue thickness. In the transmission and reflection acquisition modes, the maximum acquisition depths of about 30 mm and 6 mm can be achieved, respectively (Figs. 3 and 4). On this basis, the SORS experiment is performed, and the Raman intensity shows a certain attenuation trend with increasing Δd at 3 mm and 6 mm sample thicknesses in the transmission mode (Fig. 5), which indicates that the photons in this thickness range are less likely to diffuse laterally and more likely to penetrate the sample along a straight line. This trend is especially obvious at 3 mm, and the Raman scattering intensity is more uniform with increasing Δd at sample thicknesses from 9 mm to 30 mm, which discloses that the best results are obtained in the transmission mode with no offset acquisition. In the reflection mode, a layered model with PAT in the surface layer and polytetrafluoroethylene (PTFE) in the deep layer is used for the spectral acquisition, and both signals attenuates with increasing Δd (Fig. 6), but the PTFE signal shows a tendency of enhancing and then weakening relative to the PAT signal with increasing Δd (Fig. 7). The relatively strongest signal of PTFE is obtained from the samples with thicknesses of 3 mm and 6 mm, corresponding to Δd of 4 mm and 5 mm, respectively. This indicates that the SORS under the reflection mode can effectively avoid surface signal interference and acquire deep tissue signals, and the optimal Δd is positively correlated with sample thickness.

The potential of Raman spectroscopy based on a novel fiber optic probe for deep tissue detection is systematically investigated. On this basis, the application of SORS under the transmissive mode indicates that the transmissive mode does not possess the ability to acquire tissue information layer by layer although it has a deeper tissue penetration effect. The reflection mode SORS achieves a deeper acquisition depth (6 mm) than previous studies, validating the Monte Carlo simulation based prediction by Mosca et al., and a quantitative relationship between the detection depth and the optimal Δd is established. It confirms the ability of the SORS under the reflective mode to effectively acquire deep/stratified sample signals. This study not only demonstrates the superior performance of the self-developed fiber optic Raman probe in Raman spectroscopy, but also provides an important experimental basis and a technical reference for the further optimization of the SORS, which is of great significance in promoting the application of Raman spectroscopy in clinical diagnosis.

In recent years, Raman distributed fiber sensors (RDFS) has been applied in various fields. Inadequate spatial resolution can lead to significant errors in measurements. Some application scenarios, such as pipeline leakage monitoring and power grid safety monitoring, require high spatial resolution in the millimeter range. Therefore, enhancing the spatial resolution of RDFS is crucial. Various schemes have been proposed by researchers to optimize the spatial resolution of RDFS. In this paper, a differential pulse-pair detection scheme for RDFS is proposed. This scheme avoids the problem that it is difficult to balance the spatial resolution and the sensing distance of conventional RDFS. In addition, this scheme can also synchronously achieve the measurement of fiber loss anomalies, and achieve the dual-parametric simultaneous measurement of fiber loss points and temperature.

The experimental setup (Fig. 2) includes a pulsed laser, an erbium-doped fiber amplifier (EDFA), a wavelength division multiplexer (WDM), an avalanche photodetector (APD), a high-speed data acquisition card (DAQ), an arbitrary waveform generator (AWG), and a multimode fiber (MMF). The pulsed laser produces pulses with a central wavelength of 1550 nm. These pulses pass through an EDFA for power amplification before entering the WDM. The Raman scattering signal produced in the sensing fiber is first separated by the WDM and then fed into the APD. The received Raman scattering signal is converted into an electrical signal by the APD. The APD bandwidth is 200 MHz. This signal is subsequently collected by the DAQ and finally input into the computer for demodulation. The AWG produces periodic pulsed electrical signals to synchronize the operating time of the pulsed laser with that of the DAQ. The fbier under test (FUT) is set at the end of the multimode fiber.

Loss point detection experiments depict that the dual-pulse differential detection scheme improves the accuracy of identifying two loss points compared to the single pulse scheme. Two sharp peaks are clearly observed. The conventional scheme fails to identify two loss points, in contrast to the dual-pulse differential detection scheme. Temperature detection experiments depict that in a case of a short FUT, the superiority of the dual-pulse differential detection scheme in terms of temperature measurement accuracy becomes evident as the FUT temperature increases. The temperature error of the dual-pulse differential detection scheme is less than 0.6 ℃. The experiments depict that the dual-pulse differential detection scheme improves the temperature measurement accuracy. Temperature resolution experiments depict that with the increase of sensing distance, the Raman scattering signal is gradually weakened, and the signal to noise ratio (SNR) deteriorates. As the sensing distance continues to increase, the standard deviation of temperature deteriorates sharply.

In the dual-pulse differential detection scheme, the differential equivalent pulse width (obtained by subtracting input pulses with different widths) is a crucial factor that affects the system SNR and spatial resolution. The longer pulse leads to an unstable amplification power of the EDFA, making it difficult to maintain a constant peak power for pulses with differential pulse widths, which in turn affects the final demodulation results. Figure 8 depicts the relationship between temperature resolution and equivalent pulse width at varying sensing distances. As the equivalent pulse width increases, the temperature accuracy increases. An increase in the equivalent pulse width does not result in an infinite increase in temperature accuracy. The wider the equivalent pulse width, the less obvious the optimization of temperature measurement accuracy. The experimental results (Fig. 9) depict a gradual decrease in the standard deviation of temperature over the same sensing distance with the increase of equivalent pulse width.

This paper proposes a differential dual-pulse demodulation method based on RDFS, aiming to address the technical challenge of limited spatial resolution in traditional kilometer-range RDFS systems. The proposed scheme enables simultaneous measurement of temperature and loss parameters through differential pulse pair demodulation. Experimental results demonstrate that the sensing system achieves a spatial resolution of 0.56 m under a sensing distance of 5.6 km, with a temperature standard deviation of less than 1 ℃. Furthermore, it accurately identifies two loss event points spaced 0.4 m under a sensing distance of 8.0 km. Additionally, this scheme achieves synchronous enhancement of dual-parameter sensing capability and spatial resolution without modifying the system architecture. Its primary advantages lie in its simplicity in design and low hardware cost, demonstrating significant application value in engineering scenarios such as pipeline micro-leakage monitoring and power grid security early warning.

Energy derived from inertial confinement fusion (ICF) is clean and sustainable; however, achieving controlled nuclear fusion remains a major challenge. In laser-driven fusion experiments, X-ray radiation fields are generated within the hohlraum. To investigate the propagation characteristics of X-rays, it is essential to detect spatially resolved X-ray spectra and diagnose radiation from doped materials. This approach enables the analysis of X-ray transport paths, energy loss profiles, and the extraction of key parameters such as electron temperature and density. Crystal-based X-ray diffraction spectroscopy, a fundamental plasma diagnostic technique, plays a vital role in ICF research.

Current crystal-based diagnostic tools exhibit limitations: flat crystals lack focusing capabilities; cylindrical crystals deviate from the Rowland circle geometry; conical crystals suffer from defocusing effects; and spherical and toroidal crystals are primarily designed for two-dimensional imaging. To meet the demands for high-resolution, high-throughput spectroscopy with minimal source broadening, this study proposes a novel X-ray spectrometer utilizing a sinusoidal exponential-type crystal. By incorporating a curved crystal geometry with tunable sagittal and meridional radii while preserving the Rowland circle configuration, the developed spectrometer achieves superior spectral resolution for X-ray diagnostics.

The sinusoidal exponential-type crystal designed in this study adheres to the Rowland circle configuration, which effectively mitigates spectral resolution degradation caused by source size broadening. The curved crystal is engineered to associate each diffraction position with a distinct energy point, ensuring that all energy points within the spectral range are focused optimally. This configuration ensures that all energy points across the diagnostic spectrum maintain a high spectral resolution. The crystal structure features independently tunable curvature radii in the sagittal and meridional planes. Incident and reflected X-rays tangentially converge at imaging points along variable-radius circles. Crucially, these focal points correspond to a common reflection path. By positioning the detector at this optimized location, optical aberrations are minimized, and spectral broadening induced by source size extension is significantly suppressed. This dual-curvature design thereby accomplishes the objective of high-resolution X-ray spectroscopy.

The designed sinusoidal exponential-type crystal spectrometer system operates within a spectral energy range of 7.8?8.2 keV, corresponding to X-ray wavelengths of 0.1512 nm to 0.1590 nm. An α-quartz (202ˉ3) crystal with a lattice constant of 0.2749 nm is employed as the diffraction element, enabling detection across a Bragg angle range of 33.3° to 35.3°. The central arc length of the crystal spectrometer is 28.88 mm, with a physical dimension of 35 mm×30 mm to account for edge effects. With a detector resolution of 110 μm, the theoretical spectral resolving power of the system is calculated as 15170.

In the X-ray spectral detection system design, the distance from the X-ray source to the crystal center is set to 300 mm, and the crystal-to-detector distance is optimized to 795.76 mm for ideal focusing. The diffraction focusing capability and spectral resolution of the sinusoidal exponential-type crystal are numerically validated using XCD simulation software. Five monoenergetic Gaussian-distributed sources spanning 7.8?8.2 keV are simulated, yielding well-focused spot images for all energy points (Fig. 7), thus demonstrating excellent focusing performance across the 7800?8200 eV range. The influence of source size on focusing is analyzed with the detector positioned at the optimal location (Fig. 8). Results indicate that increased source dimensions induce horizontal spot broadening. Furthermore, the combined effects of source size and detector misalignment on spectral resolution are quantified (Fig. 9). The findings reveal no significant resolution loss when transitioning from an ideal point source to a source with a radius of 0.5 mm. In the simulation experiment, the spectral resolution of the system is calculated to be approximately 11000.

Experimental validation is conducted using a copper-target X-ray tube setup, incorporating the sinusoidal exponential-type crystal and a complementary metal-oxide-semiconductor transistor (CMOS) detector. Experimental results align with simulations: distinct focal spots corresponding to Cu Kα1 and Kα2 emission lines are observed (Fig. 11), confirming superior photon throughput. The practical spectral resolving power is measured as 2810 (Fig. 12). Discrepancies between theoretical and experimental resolutions are attributed to limitations in crystal surface figure accuracy and fabrication tolerances, highlighting the need for advanced high-precision crystal machining techniques in future studies.

This work is based on the Rowland circle geometry and introduces a sinusoidal exponential-type crystal with variable radii in the sagittal and meridional planes. The designed spectrometer achieves high photon throughput and high spectral resolving power simultaneously. Theoretical simulations predict its resolving capability, subsequently validated through systematic X-ray diffraction experiments. Experimental results demonstrate that the spectrometer exhibits exceptional focusing performance within a defined spectral range, effectively concentrating X-rays into distinct bright spots. The sinusoidal exponential-type crystal significantly suppresses spectral resolution degradation caused by source size broadening, achieving a practical resolving power of 2800 and demonstrating high-resolution spectroscopic characteristics.

When studying the efficacy of laser surgery for vascular skin diseases using the rat dorsal skinfold window model, conventional approaches typically need removing the superficial skin tissue to directly irradiate exposed blood vessels. Such a methodology neglects critical factors including skin absorption, scattering, and thermal transfer, thus severely underestimating the required laser parameters for clinical treatments. A novel transdermal irradiation method is proposed to solve this issue by maintaining the intact skin layer during laser exposure, thus providing a research method more in line with the clinical scenario. The use of dual-modal imaging combining laser speckle contrast imaging (LSCI) with infrared thermography can precisely characterize and compare vascular thermal effects induced by direct laser irradiation and transdermal laser irradiation.

A dual-modal imaging system combining LSCI with infrared thermography is developed to monitor blood flow dynamics and temperature changes simultaneously during therapeutic laser irradiation. The dorsal skinfold window model is prepared in Sprague-Dawley (SD) rats, facilitating visualization and monitoring of microvascular structures. Two irradiation modes are investigated: the direct irradiation of vessels exposed by skin removal and the transdermal irradiation of vessels beneath an intact skin layer (average depth of ~1.3 mm). The laser used is a long-pulsed Nd∶YAG (1064 nm) system, and the experimental parameters include energy densities of 7.88 J·cm^-2 and 11.04 J·cm^-2, pulse durations of 1 ms and 5 ms, frequency of 1 Hz, and pulse numbers of 4 and 10. To improve image quality and temporal resolution, a lightweight deep-learning denoising algorithm, LDSCI-GAN, is applied to raw speckle images, significantly enhancing the detection of rapid vascular changes.

The LDSCI-GAN deep-learning denoising method enhances the quality of temporal laser speckle blood flow images by using only 5 frame raw speckle images, improving peak signal-to-noise ratio (PSNR),mean structural similarity index (MSSIM), and correlation coefficient R from 14.6±6.1, 0.25±0.18, and 0.38±0.09 to 33.9±3.1, 0.97±0.03, and 0.99±0.01, with corresponding increases of 132.2%, 288.0%, and 160.5%, respectively (Fig. 3 and Fig. 4). The denoised image quality matches the quality of processed 50 frame raw speckle images using MD-ABM3D, enabling a tenfold improvement in temporal resolution and allowing reliable visualization of transient blood flow changes. Under identical laser parameters (energy density of 7.88 J·cm^-2, pulse duration of 5 ms, and pulse number of 4), the direct irradiation induces a complete vessel closure with a peak temperature of 50.6 ℃, whereas the transdermal irradiation results in only a mild blood flow reduction with a peak temperature of 37.6 ℃ (Fig. 5). This discrepancy is due to substantial optical attenuation and thermal diffusion within the skin, which causes the direct irradiation model to underestimate the energy threshold required for deep vessel treatment. In other words, the transdermal irradiation better replicates clinical conditions and provides a more realistic in vivo model for laser therapy evaluation. Increasing the pulse duration from 1 ms to 5 ms at 9.27 J·cm^-2 (5 pulses) enables clear vessel contraction (Fig. 6). Raising the energy density from 9.27 J·cm^-2 to 11.04 J·cm^-2 (pulse duration of 1 ms, 5 pulses) significantly enhances the thermal response, with a peak temperature difference between direct and transdermal modes reaching 27.3 ℃ (Fig. 7). Increasing the pulse number from 4 to 10 at 7.88 J·cm^-2 (pulse duration of 5 ms) elevates the vessel temperature from 42.5 ℃ to 57.6 ℃ and achieves a complete occlusion under transdermal conditions (Fig. 8). These findings confirm that optimizing laser parameters is essential for effective treatment of deep vessels and demonstrate the value of transdermal models in guiding clinically relevant laser therapy strategies.

To simulate real clinical scenarios, a novel transdermal irradiation method is proposed to overcome the inaccurate estimation of laser-tissue interactions caused by the removal of the upper skin layers. Using a dual-modal imaging system that combines LSCI with infrared thermography, the thermal effects by new and traditional methods are compared. Experimental comparisons reveal that direct irradiation significantly underestimates the energy required for effective vessel treatment due to the absence of skin-mediated scattering and heat diffusion. When the upper skin layers are preserved, higher energy density, larger pulse duration, and larger pulse number are necessary to reach an ideal thermal response. In conclusion, this work emphasizes the necessity of transdermal irradiation models in experimental dermatologic laser studies and provides a powerful imaging framework to guide the development of safer and more effective laser therapies.

Balanced optical cross-correlators (BOCs) enable sub-femtosecond pulse timing interval measurements and are widely utilized in ultrafast laser diagnostics and synchronization control. Conventional free-space BOCs depend on bulk nonlinear crystals, which demonstrate low second-harmonic generation (SHG) conversion efficiency (0.4%, corresponding to a normalized efficiency of 0.0065%·W^-1·cm^-2), thus necessitating relatively high pump power. Thin-film lithium niobate (TFLN) photonic platforms provide exceptional second-order nonlinearity (d₃₃=25 pm/V, d₃₁=4.6 pm/V), electric-field-induced domain inversion capability, a broad transparency window (400 nm to 5 μm), and strong optical confinement (with a refractive index contrast of ~0.7 relative to silicon dioxide), presenting a promising approach toward fully integrated on-chip BOCs. In this study, we demonstrate a polarization-independent reflector on TFLN photonic platforms. A polarization- rotating Bragg grating (PRBG) structure is implemented by introducing bidirectional asymmetry to suppress the polarization dependence of both the TE₀ and TM₀ modes. We designed and fabricated a 210 μm-long asymmetric Bragg grating. Experimental results show that within the 1548.3?1556.8 nm wavelength range, the transmission spectra of the TE₀ and TM₀ modes are nearly identical, with a 3 dB bandwidth of approximately 8.5 nm and a polarization extinction ratio exceeding 20 dB, confirming the strong polarization-independent performance of the structure. These results provide a key technological foundation for the realization of fully integrated on-chip BOCs.

This study employs the finite element method (FEM) to simulate the wavelength-dependent effective refractive indices of the TE₀ and TM₀ modes in a z-cut TFLN waveguide with a width of W=0.9 μm. Considering the fabrication constraint, a sidewall tilt angle of 67° was incorporated into the design. The performance of the PRBG reflector was analyzed using the eigenmode expansion method (EME), through which the effects of variations in waveguide width, unetched thickness, sidewall angle, duty cycle, and grating period were systematically investigated. Based on design results, the device was patterned using 100 kV electro-beam lithography with ZEP520A positive-tone resist, followed by pattern transfer to the TFLN layer through an optimized argon ion beam milling process. After cleavage to expose the waveguide facet, the device performance was characterized using a fiber-to-chip coupling system.

To analyze the experimental results, the transmission spectra under TE₀ and TM₀ modes incidence are initially simulated using EME method, as shown in Fig. 5(b) and Fig. 5(c). Considering fabrication-induced deviations, the grating period in the simulation is adjusted from the designed value of 420 nm to 419 nm to better match the actual structure. The results demonstrate that the TE₀ mode is effectively reflected in the wavelength ranges of 1509.6?1521.1 nm and 1549.2?1557.1 nm, with the TM₀ mode being the dominant transmitted component. Conversely, the TM₀ mode is effectively reflected within 1549.2?1557.1 nm, with TE₀ as the primary transmitted mode. By superimposing and normalizing the transmission spectra, the overall simulated transmission spectrum is obtained, as shown by the black curves in Fig. 5(d) and Fig. 5(e). From experimental measurements, we have recorded the normalized transmission spectra, as shown in the red curves in Fig. 5(d) and Fig. 5(e). The reflector exhibits excellent reflection characteristics for both TE₀ and TM₀ modes within the 1548.3?1556.8 nm wavelength range, with a central transmission wavelength of approximately 1552.6 nm, a 3 dB bandwidth of ~8.5 nm, and a polarization extinction ratio exceeding 20 dB—indicating strong polarization-independent reflection performance. Furthermore, the experimental results demonstrate high consistency with the simulated spectra in this range, validating the accuracy and reliability of the device design parameters. Additionally, when the input is TE₀, strong reflection is observed in the 1511.4?1519.0 nm band, which aligns well with the expected design.

This research presents the pioneering implementation of a polarization-independent photonic reflector utilizing the TFLN photonic platform. The design incorporates a PRBG structure, developed through a systematic parameter optimization methodology. A comprehensive analysis examined the effects of critical structural parameters, including waveguide width, unetched thickness, sidewall angle, duty cycle, grating period, and number of periods, on device performance. The reflector fabrication is accomplished through a single-step electron-beam lithography and dry etching process. Experimental measurements demonstrate that both TE₀ and TM₀ modes achieve high reflectivity within the wavelength range of 1548.3?1556.8 nm, featuring a 3 dB bandwidth of approximately 8.5 nm and a polarization extinction ratio exceeding 20 dB. The measured transmission spectra demonstrate excellent agreement with simulation results, confirming the validity of the design methodology. When combined with existing z-cut TFLN periodic poling techniques, this polarization-independent reflector demonstrates significant potential for monolithic integration with type-II QPM PPLN waveguides, advancing the development of fully integrated on-chip BOC devices and enabling ultrafast optical signal processing.

Combinatorial optimization problems are fundamental and widespread across diverse scientific and industrial domains, encompassing fields that range from artificial intelligence and communication networks to transportation planning and large-scale logistics management. These problems are typically classified as nondeterministic polynomial-time hard, with numerous emblematic cases, such as the traveling-salesperson problem and the maximum-cut problem categorized specifically as nondeterministic polynomial-time complete. Due to the exponential growth of candidate configurations with increasing problem size, exhaustive search methods executed on conventional digital hardware quickly become infeasible in terms of both computation time and energy expenditure.

Traditional processors based on the John von Neumann architecture encounter intrinsic limitations stemming from their sequential instruction execution and the physical separation of memory and logic units—a fundamental constraint commonly known as the “von Neumann bottleneck.” As the coupling complexity among decision variables intensifies, these processors suffer from excessively high latency and power consumption. Consequently, there has been significant interest in exploring alternative physical substrates capable of evaluating multiple candidate solutions in parallel, thereby overcoming the scaling constraints inherent to conventional, clock-driven computing machines.

One particularly promising approach involves reformulating combinatorial optimization problems as energy-minimization tasks within the framework of the Ising model, a theoretical construct originally introduced in statistical physics to describe ferromagnetic phenomena. In this mapping, each binary decision variable corresponds to a discrete spin state that can adopt either an “up” or “down” orientation, with pairwise couplings explicitly encoding the problem’s cost function. Driving such a spin network toward its ground-state configuration is mathematically equivalent to finding an optimal or near-optimal solution to the original combinatorial optimization problem.

Photonic Ising machines have attracted significant attention due to the distinct advantages inherent in photonic technologies, including extremely low transmission losses, high operational bandwidth, and intrinsic capabilities for massively parallel computations enabled by optical interference and nonlinear optical phenomena. By leveraging physical processes such as optical parametric oscillation and coherent photonic interactions, photonic Ising machines exhibit remarkable potential to dramatically reduce energy consumption and computational costs associated with solving large-scale combinatorial optimization problems. Specifically, integrated photonic Ising machines, which employ chip-scale photonic circuits for spin coupling and evolution, have garnered considerable interest due to their compactness, low energy consumption, and high stability. These characteristics make integrated photonic Ising machines especially suited to demanding applications in data centers, high-speed communications, and edge computing scenarios.

The significance of these advancements is profound, as they offer pathways toward sustainable, scalable, and highly efficient computational technologies capable of addressing the increasingly complex optimization challenges encountered in contemporary scientific and industrial contexts. Integrated photonic Ising machines inherently integrate physical optimization processes onto photonic chips, enabling efficient on-chip optimization processes with reduced reliance on external electronic control systems, thereby enhancing overall energy efficiency and computational speed.

Moreover, integrated photonic Ising machines represent a versatile computing platform capable of addressing a broad spectrum of real-world applications beyond conventional optimization tasks. The intrinsic parallelism, scalability, and chip-scale integration of photonic technologies align exceptionally well with emerging computational demands, including advanced neural network training, real-time decision-making systems, and adaptive resource management. This alignment underscores their substantial potential to revolutionize computational paradigms across multiple disciplines. Consequently, the convergence of photonics and computational science embodied specifically in integrated photonic Ising machines not only constitutes a significant technological breakthrough but also opens new research avenues into the intricate interplay between physical processes and computational efficiency, thereby enriching both theoretical insights and practical approaches within the field of optimization science.

Recent advancements in integrated photonic Ising machines are reviewed in this paper, focusing on their practical deployment and computational benefits. Current photonic Ising architectures can be categorized into spatial optical and integrated on-chip solutions, with integrated platforms increasingly favored due to their miniaturization, low power consumption, and stability, qualities essential for data centers, high-speed communications, and edge computing applications. Key implementations include schemes based on degenerate optical parametric oscillators (DOPOs) utilizing microresonators (Fig. 2), Mach?Zehnder interferometer (MZI) networks (Fig. 3), and time-domain multiplexed lithium niobate electro-optic modulators for computational annealing (Fig. 5, Table 1). These approaches achieve rapid spin evolution, scalability, and programmability critical for diverse application scenarios, including MIMO communications (Fig. 6), path planning, and restricted Boltzmann machines (RBMs) for unsupervised learning (Fig. 7).

Notably, recent studies have demonstrated significant performance enhancements through methods such as regularized Ising formulations for MIMO signal detection, reducing error floors and improving near-optimal detection accuracy. Advanced methodologies, including multi-stage optimization techniques and noise-injected sampling, have shown superior efficiency in handling complex combinatorial optimization tasks and facilitating RBM training by accurately simulating Boltzmann distributions (Fig. 8, Fig. 9).

Integrated photonic Ising machines significantly advance the resolution of combinatorial optimization problems through inherent parallel computation, low power consumption, and high-speed responses enabled by optical technologies. Nevertheless, achieving practical scalability remains challenging due to constraints in photonic device dimensions, typically at micrometer scales, limiting integration density compared to electronic counterparts. Additionally, precise control over spin evolution processes is essential for accurate results, yet optical systems frequently suffer from instabilities caused by intrinsic noise and fabrication imperfections. Future research should prioritize innovations in photonic device technologies, enhanced control methods, and the integration of physical and algorithmic strategies. Given the Turing completeness of Ising machines, extending their applications beyond optimization into deep learning, real-time adaptive systems, and general-purpose computing holds substantial promise. Continued interdisciplinary efforts are critical to realizing the full potential of integrated photonic Ising machines as versatile computational platforms.

Addressing optical physical layer security for metropolitan-optimized optical transport network (M-OTN) presents a critical challenge for telecom operators. This paper introduces and experimentally validates a methodology for real-time optical service unit (OSU) optical signal time-domain scrambling integrated with decoy-state quantum key distribution (DS-QKD). The system processes OSU optical signals in real-time utilizing tunable Fabry-Perot cavity (FPC) with dynamically updated and synchronized keys. The DS-QKD system implements the decoy-state BB84 protocol and polarization coding for seed key distribution. The research demonstrates effective end-to-end optical physical layer security for M-OTN (OTU2, 10.709 Gbit/s) data transmission under real-time key update conditions.

Figure 2 illustrates the operational principle of real-time OSU optical signal time-domain random scrambling integrated with the DS-QKD system. The system employs a symmetric encryption architecture, incorporating a DS-QKD transmitter and receiver, with key transmission via DS-QKD. Through the quantum channel, the transmitter communicates a random seed key to the receiver without service data transmission. The DS-QKD system initially transfers the seed key to the local field-programmable gate array (FPGA), which maintains the seed key and establishes a running key pool. The transmitter's FPGA then utilizes a running key from the pool to scramble the input OSU optical signal. Concurrently, it transmits the synchronization marker to the receiver's FPGA through the synchronization channel. Upon receiving the synchronization marker, the receiver’s FPGA employs the corresponding running key from its pool to descramble the received OSU optical signal. FPC facilitates the time-domain scrambling of the OSU optical signal (Fig. 3). Each FPC incorporates an independent temperature control module (TCM), and the scrambling/descrambling controller modifies the FPCs’ parameters using the running key after transmitter-receiver synchronization, specifically adjusting the cavity’s optical thickness for time-domain scrambling/descrambling.

The eye diagrams of the experimental results for OSU optical signal scrambling and descrambling (Fig. 6), with Fig. 6(a) and Fig. 6(b) showing the original and scrambled signals, respectively. The scrambled signal differs substantially from the original 10.709 Gbit/s non-return-to-zero (NRZ) signal due to the FPC array's bit overlapping scrambling. This confirms the scrambler’s effectiveness in disrupting the temporal position relationship between bits, rendering the OSU optical signal undigitizable. The unperturbed eye diagrams are shown in Fig. 6(c) and Fig. 6(d), respectively. Figure 7 illustrates the system’s running key performance, while Fig. 8 shows the bit error rate (BER) performance of the OSU signal after backhaul (B2B). These results confirm the effective enhancement of optical physical layer security.

This research presents and experimentally validates an OSU optical physical layer security protection method utilizing real-time optical signal time-domain scrambling. DS-QKD provides the seed key, enabling running key generation between the transmitter and receiver. System performance testing confirms that only authorized users employing the synchronous scrambler/de-scrambler and correct running key can successfully recover OSU data. Without the synchronization running key, eavesdroppers cannot extract the OSU optical signal’s digital features. The proposed method enhances M-OTN security by implementing protection in the optical domain, supplementing traditional electrical domain encryption algorithms.

The exponential growth of emerging big data services and global internet traffic has driven traditional single-mode optical fiber communication systems toward their capacity limits. Mode division multiplexing (MDM) technology has emerged as a promising solution to expand communication capacity by enabling multi-mode parallel transmission within a single fiber core and utilizing spatial dimensions. However, variations in the intensity and phase distributions of different modes present significant challenges: the precise manipulation of modes and accurate separation and conversion of mode channels. This precision is essential for achieving high-performance communication systems. Consequently, research on mode manipulation and its applications in MDM-based optical fiber communication holds substantial importance for addressing the growing demand for communication capacity and advancing optical fiber communication technology.

Mode manipulation and MDM-based optical fiber communication research has demonstrated significant advancements in recent years. Scientists have explored the fundamental principles of mode manipulation, encompassing effective refractive index matching, mode coupling, and optical field wavefront control. Multiple mode multiplexing/demultiplexing technologies have emerged, including planar waveguide-based, fiber-based, and free-space approaches. Planar waveguide-based technologies achieve high integration and miniaturization through waveguide construction on substrates. Shanghai Jiao Tong University demonstrated 4-channel multiplexing/demultiplexing using a silicon-based waveguide with a multimode interferometer structure. Zhejiang University developed a compact 4-mode multiplexer/demultiplexer with low insertion loss and high crosstalk suppression utilizing multimode micro-ring waveguides. Fiber-based technologies, employing fibers as the control medium, provide direct integration with few-mode fibers. Long-period fiber gratings, mode-selective couplers, and photonic lanterns represent key implementations. Shanghai University and Peking University have achieved significant advances in mode conversion and multiplexing/demultiplexing using these methods. Free-space-based technologies facilitate manipulation of optical field amplitude, phase, and polarization in free space. Multi-plane light conversion (MPLC) technology has been widely implemented for precise mode conversion control. Researchers at Cailabs in France achieved multiplexing/demultiplexing of multiple LP modes with high mode purity and low inter-modal crosstalk. Our research team has contributed significant advancements, developing a high-precision, non-destructive characterization technique for fiber microstructures, enabling 3D reconstruction of multi-core and few-mode fiber structures. We implemented mode multiplexing/demultiplexing technologies based on MPLC and fiber coupling, achieving high-efficiency mode conversion. Additionally, we proposed innovative few-mode fiber designs and pumping schemes to address gain imbalance in few-mode fiber amplifiers, supporting long-haul MDM transmission systems.

Mode manipulation, a fundamental approach in MDM-based optical fiber communication systems, has demonstrated substantial research progress through the development of mode multiplexing/demultiplexing techniques and devices, offering innovative solutions for capacity expansion in fiber-optic communication systems. Our research team has contributed significantly in three key areas: 1) high-precision characterization of fiber microstructures, 2) advanced mode manipulation technologies, and 3) development of few-mode fiber amplifiers. As technology advances, mode manipulation applications are expanding beyond telecommunications into emerging fields such as optical imaging and photonic computing systems, while requiring more precise multidimensional parameter coordination and crosstalk suppression. Future research directions will emphasize exploring novel materials with exceptional optoelectronic properties, designing advanced photonic structures with subwavelength precision, and developing innovative methodologies for intelligent mode control. These developments are anticipated to advance MDM technology toward ultra-high-capacity optical networks while fostering interdisciplinary innovations in photonic information processing.