Ultra-sensitive measurement of small optical rotation angles using quantum entanglement based on a quasi-Wollaston prism beam splitter.

The measurement of optical rotation is fundamental to optical atomic magnetometry. Ultra-high sensitivity has been achieved by employing a quasi-Wollaston prism as the beam splitter within a quantum entanglement state, complemented by synchronous detection. Initially, we designed a quasi-Wollaston prism and intentionally rotated the crystal axis of the exit prism element by a specific bias angle. A linearly polarized light beam, incident upon this prism, is divided into three beams, with the intensity of each beam correlated through quantum entanglement. Subsequently, we formulated the equations for optical rotation angles by synchronously detecting the intensities of these beams, distinguishing between differential and reference signals. Theoretical analysis indicates that the measurement uncertainty for optical rotation angles, when using quantum entanglement, exceeds the conventional photon shot noise limit. Moreover, we have experimentally validated the effectiveness of our method. In DC mode, the experimental results reveal that the measurement uncertainty for optical rotation angles is 4.7 × 10-9 rad, implying a sensitivity of 4.7 × 10-10 rad/Hz1/2 for each 0.01 s measurement duration. In light intensity modulation mode, the uncertainty is 48.9 × 10-9 rad, indicating a sensitivity of 4.89 × 10-9 rad/Hz1/2 per 0.01 s measurement duration. This study presents a novel approach for measuring small optical rotation angles with unprecedentedly low uncertainty and high sensitivity, potentially playing a pivotal role in advancing all-optical atomic magnetometers and magneto-optical effect research.

Monolithic integrated chip of AWG and PD for an FBG interrogation system.

To advance the development of a compact and highly integrated fiber Bragg grating (FBG) interrogation system, to the best of our knowledge, this paper is the first to present the design and fabrication of a monolithic integration chip based on silicon-on-insulator (SOI), which is specifically intended for application in fiber grating sensing interrogation systems. By considering the impact of coupling structure dimensions on coupling efficiency as well as the effect of the photodetector (PD) parameters on the optical absorption efficiency of the device, we refine the structure of the monolithic integrated chip for arrayed waveguide grating (AWG) and PD. The test results reveal that the coupling loss between AWG and PD is -2.4 dB. The monolithic integrated interrogation chip achieves an interrogation accuracy of approximately 6.79 pm within a dynamic range of 1.56 nm, accompanied by a wavelength resolution of 1 pm. This exceptional performance highlights the potential of the monolithic integrated chip to enhance the integration of AWG-based fiber grating interrogation systems.

Six-orders-of-magnitude-spanning dispersion measurement via Kalman filtering-aided white-light interferometry.

Dispersion plays a great role in ultrafast laser oscillators, ultrashort pulse amplifiers, and many other nonlinear optical dynamics. Therefore, dispersion measurement is crucial for device characterization, system design and nonlinear dynamics investigation therein. In this work, we demonstrate a versatile approach, i.e., Kalman filtering-aided white-light interferometry, for group delay dispersion (GDD) characterization. Extended Kalman filter is adopted to track the cosine-like interferogram, and to eliminate the unintended bias and the envelope, providing a nearly ideal phase retrieval and GDD estimation. The measurement range could span from tens of fs2 to tens of ps2, with an uncertainty of about 0.1%, enabling precise GDD measurement for diverse optical components, ranging from a millimeter-thick glass slide to highly dispersive chirped fiber Bragg gratings. Benefited by the simplicity, convenient setup, and easy operation as well as relatively low cost, this approach would help photonic device characterization, dispersion management and nonlinear dynamics investigation in the laboratory and work plant.

PMONN: an optical neural network for photonic integrated circuits based on micro-resonator.

We propose an improved optical neural network (ONN) circuit architecture based on conventional micro-resonator ONNs, called the Phase-based Micro-resonator Optical Neural Network (PMONN). PMONN's core architecture features a Convolutions and Batch Normalization (CB) unit, comprising a phase-based (PB) convolutional layer, a Depth-Point-Wise (DPW) convolutional layer, and a reconstructed Batch Normalization (RBN) layer. The PB convolution kernel uses modulable phase shifts of Add-drop MRRs as learnable parameters and their optical transfer function as convolution weights. The DPW convolution kernel amplifies PB convolution weights by learning the amplification factors. To address the internal covariate shift during training, the RBN layer normalizes DPW outputs by reconstructing the BN layer of the electronic neural network, which is then merged with the DPW layer in the test stage. We employ the tunable DAs in the architecture to implement the merged layer. PMONN achieves 99.15% and 91.83% accuracy on MNIST and Fashion-MNIST datasets, respectively. This work presents a method for implementing an optical neural network on the improved architecture based on MRRs and increases the flexibility and reusability of the architecture. PMONN has potential applications as the backbone for future optical object detection neural networks.

A deep learning method for multi-task intelligent detection of oral cancer based on optical fiber Raman spectroscopy.

In the fight against oral cancer, innovative methods like Raman spectroscopy and deep learning have become powerful tools, particularly in integral tasks encompassing tumor staging, lymph node staging, and histological grading. These aspects are essential for the development of effective treatment strategies and prognostic assessment. However, it is important to note that most research so far has focused on solutions to one of these problems and has not taken full advantage of the potential wealth of information in the data. To compensate for this shortfall, we conceived a method that combines Raman spectroscopy with deep learning for simultaneous processing of multiple classification tasks, including tumor staging, lymph node staging, and histological grading. To achieve this innovative approach, we collected 1750 Raman spectra from 70 tissue samples, including normal and cancerous tissue samples from 35 patients with oral cancer. In addition, we used a deep neural network architecture to design four distinct multi-task network (MTN) models for intelligent oral cancer diagnosis, named MTN-Alexnet, MTN-Googlenet, MTN-Resnet50, and MTN-Transformer. To determine their effectiveness, we compared these multitask models to each other and to single-task models and traditional machine learning methods. The preliminary experimental results show that our multi-task network model has good performance, among which MTN-Transformer performs best. Specifically, MTN-Transformer has an accuracy of 81.5%, a precision of 82.1%, a sensitivity of 80.2%, and an F1_score of 81.1% in terms of tumor staging. In the field of lymph node staging, the accuracy, precision, sensitivity, and F1_score of MTN-Transformer are 81.3%, 83.0%, 80.1%, and 81.5% respectively. Similarly, for the histological grading classification tasks, the accuracy was 83.0%, the precision 84.3%, the sensitivity 76.7%, and the F1_score 80.2%. This code is available at https://github.com/ISCLab-Bistu/MultiTask-OralRamanSystem.

High-performance interrogator with bilateral input MMI-based AWG.

Compact fiber Bragg grating (FBG) interrogator is a widely investigated topic in the field of fiber optic sensing. Here we report a dense spectral arrayed waveguide grating (AWG) chip designed for FBG interrogation. By integrating a multimode interference (MMI) coupler with the AWG, bilateral input phase-differential optical signals were achieved at the input port of the AWG. This chip effectively doubles the output channel count without altering the device footprint, while concurrently reducing the channel spacing without modifying the bandwidth and spectral slope of the output spectrum. We further optimized the method for selecting interrogation channels. The results demonstrate that the dynamic range of the interrogation reaches 13.5 nm with an absolute wavelength resolution of 4 pm and an absolute accuracy better than 20 pm.

Camera optimal projection model identification and calibration method based on the NGO-BA architecture.

In order to bridge the fundamental commonalities between imaging models of camera lenses with different principles and structures, allowing for an accurate description of imaging characteristics across a wide range of field-of-view (FOV), we have proposed a generic camera calibration method on the basis of the projection model optimization strategy. First, in order to cover the current mainstream projection models, piecewise functions for geometric projection models and a polynomial function for the fitting projection model are designed. Then, the corresponding camera multistation self-calibration bundle adjustment (BA) module is developed for various projection models. Further, by integrating the self-calibration BA algorithm into the northern goshawk optimization architecture, iterative optimization is performed on the projection model adjustment parameters, camera interior parameters, camera exterior parameters, and lens distortion parameters until the target reprojection (RP) error reaches the global minimum. The experimental results indicate that the calibration RP root mean square error in this method is 1/20 pixel for a 68° FOV camera, 1/13 pixel for an 84° FOV camera, 1/9 pixel for a 115° FOV camera, 1/9 pixel for a 135° FOV camera, and 1/6 pixel for a 180° FOV camera. This calibration method offers fast and versatile optimization for various projection model types, encompassing a wide range of projection functions. It can efficiently determine the optimal projection model and all imaging parameters for multiple cameras during the calibration process.

Low dark current density extended short-wavelength infrared superlattice photodetector with atomic layer deposited Al2O3 passivation.

We report on a low dark current density P-B-i-N extended short-wavelength infrared photodetector with atomic layer deposited (ALD) A l 2 O 3 passivation based on a InAs/GaSb/AlSb superlattice. The dark current density of the A l 2 O 3 passivated device was reduced by 38% compared to the unpassivated device. The cutoff wavelength of the photodetector is 1.8 µm at 300 K. The photodetector exhibited a room-temperature (300 K) peak responsivity of 0.44 A/W at 1.52 µm, corresponding to a quantum efficiency of 35.8%. The photodetector exhibited a specific detectivity (D ∗) of 1.08×1011 c m⋅H z 1/2/W with a low dark current density of 3.4×10-5 A/c m 2 under -50m v bias at 300 K. The low dark current density A l 2 O 3 passivated device is expected to be used in the fabrication of extended short-wavelength infrared focal plane arrays for imaging.

ECFuse: Edge-Consistent and Correlation-Driven Fusion Framework for Infrared and Visible Image Fusion.

Infrared and visible image fusion (IVIF) aims to render fused images that maintain the merits of both modalities. To tackle the challenge in fusing cross-modality information and avoiding texture loss in IVIF, we propose a novel edge-consistent and correlation-driven fusion framework (ECFuse). This framework leverages our proposed edge-consistency fusion module to maintain rich and coherent edges and textures, simultaneously introducing a correlation-driven deep learning network to fuse the cross-modality global features and modality-specific local features. Firstly, the framework employs a multi-scale transformation (MST) to decompose the source images into base and detail layers. Then, the edge-consistent fusion module fuses detail layers while maintaining the coherence of edges through consistency verification. A correlation-driven fusion network is proposed to fuse the base layers containing both modalities' main features in the transformation domain. Finally, the final fused spatial image is reconstructed by inverse MST. We conducted experiments to compare our ECFuse with both conventional and deep leaning approaches on TNO, LLVIP and M3FD datasets. The qualitative and quantitative evaluation results demonstrate the effectiveness of our framework. We also show that ECFuse can boost the performance in downstream infrared-visible object detection in a unified benchmark.

Temperature and strain simultaneous sensing measurement based on an all-fiber Mach-Zehnder interferometer and fiber Bragg grating.

We designed and fabricated what we believe to be a novel dual-parameter fiber optic sensor for simultaneous measurement of temperature and strain, which was composed of a femtosecond laser inscribed fiber Bragg grating (FBG), three segments of a single-mode fiber (SMF), and two segments of a multimode fiber (MMF), forming a SMF-MMF-FBG-MMF-SMF structure. The FBG and Mach-Zehnder interferometer (MZI) were present in this structure so that the changes of the temperature and strain parameters can be sensed by the shifts of the reflection center wavelength of the FBG and the interference valley wavelength of the MZI. We simulated the light field distribution of the sensor structure, compared the shapes of the interference spectra formed by the MZI structure with different sensing arm lengths of 25, 35, and 45 mm, and analyzed the spectra in the spatial frequency domain. The simulation results showed that the interference spectrum of the MZI structure with a 25 mm length sensing arm was clearer and more suitable for the experiment. The experimental results showed that the temperature sensitivity of the FBG and MZI was 14.81 and 43.54 pm/°C in the range of 80°C to 240°C, and the strain sensitivity was 1.49 and -2.58 pm/µÎµ in the range of 0 to 1200 µÎµ, with a high linearity and excellent repeatability. The sensor is economical, sensitive, and convenient to fabricate, and exhibits promising applications in the fields of biochemical medical detection and industrial production monitoring.

Design and optimization of an SOI-based electro-absorption-type VOA.

A silicon-on-insulator (SOI) variable optical attenuator (VOA) based on the plasma dispersion effect is optimized and realized, and the effects of doping concentration and distance about the VOA's modulation depth and attenuation efficiency are investigated. Two structures of the VOA component are designed to achieve low power consumption, high stability, and high modulation efficiency. The modulation depth of the series VOA scheme reached 60.11 dB, and the insertion loss is only 4.87 dB. Compared with conventional components, our optimized VOA can not only improve the modulation accuracy and efficiency but also reduce the wavelength dependence.

Resonant-cavity-enhanced infrared detector incorporating an ultra-thin type-II superlattice: design and simulation.

A resonant-cavity-enhanced type-II superlattice (T2SL) infrared detector based on a metal grating has been designed to address the weak photon capture and low quantum efficiency (QE) issues of T2SL infrared detectors. Simulations have been conducted to analyze the effects of metal grating parameters, including length, thickness, and incident angle, on the spectral response and absorptivity of the absorption layers in T2SL infrared detectors. By optimizing the design, an appropriate resonant cavity structure was obtained. Research results indicate that the resonant cavity structure can significantly enhance the absorption rate of a T2SL infrared detector with a 0.2 µm thick absorption layer in the 3-5 µm wavelength range, observing peak absorption rates at 3.82 µm and 4.73 µm, with values of 97.6% and 98.2%, respectively. The absorption rate of the 0.2 µm thick T2SL absorption layer at peak wavelengths increased from 6.03% and 2.3% to 54.48% and 27.91%, respectively. The implementation of the resonant-cavity-enhanced T2SL infrared detector improves the QE while reducing absorption layer thickness, thus opening up new avenues for improving T2SL detector performance.

Si-Based Polarizer and 1-Bit Phase-Controlled Non-Polarizing Beam Splitter-Based Integrated Metasurface for Extended Shortwave Infrared.

Metasurfaces, composed of micro-nano-structured planar materials, offer highly tunable control over incident light and find significant applications in imaging, navigation, and sensing. However, highly efficient polarization devices are scarce for the extended shortwave infrared (ESWIR) range (1.7~2.5 µm). This paper proposes and demonstrates a highly efficient all-dielectric diatomic metasurface composed of single-crystalline Si nanocylinders and nanocubes on SiO2. This metasurface can serve as a nanoscale linear polarizer for generating polarization-angle-controllable linearly polarized light. At the wavelength of 2172 nm, the maximum transmission efficiency, extinction ratio, and linear polarization degree can reach 93.43%, 45.06 dB, and 0.9973, respectively. Moreover, a nonpolarizing beam splitter (NPBS) was designed and deduced theoretically based on this polarizer, which can achieve a splitting angle of ±13.18° and a phase difference of π. This beam splitter can be equivalently represented as an integration of a linear polarizer with controllable polarization angles and an NPBS with one-bit phase modulation. It is envisaged that through further design optimization, the phase tuning range of the metasurface can be expanded, allowing for the extension of the operational wavelength into the mid-wave infrared range, and the splitting angle is adjustable. Moreover, it can be utilized for integrated polarization detectors and be a potential application for optical digital encoding metasurfaces.

High-efficiency all fluorescence white OLEDs with high color rendering index by manipulating excitons in co-host recombination layers.

All fluorescence white organic light-emitting diodes (WOLEDs) based on thermally activated delayed fluorescence (TADF) emitters are an attractive route to realize highly efficient and high color quality white light sources. However, harvesting triplet excitons in these devices remains a formidable challenge, particularly for WOLEDs involving conventional fluorescent emitters. Herein, we report a universal design strategy based on a co-host system and a cascaded exciton transfer configuration. The co-host system furnishes a broad and charge-balanced exciton generation zone, which simultaneously endows the devices with low efficiency roll-off and good color stability. A yellow TADF layer is put forward as an intermediate sensitizer layer between the blue TADF light-emitting layer (EML) and the red fluorescence EML, which not only constructs an efficient cascaded Förster energy transfer route but also blocks the triplet exciton loss channel through Dexter energy transfer. With the proposed design strategy, three-color all fluorescence WOLEDs reach a maximum external quantum efficiency (EQE) of 22.4% with a remarkable color rendering index (CRI) of 92 and CIE coordinates of (0.37, 0.40). Detailed optical simulation confirms the high exciton utilization efficiency. Finally, by introducing an efficient blue emitter 5Cz-TRZ, a maximum EQE of 30.1% is achieved with CIE coordinates of (0.42, 0.42) and a CRI of 84 at 1000 cd m-2. These outstanding results demonstrate the great potential of all fluorescence WOLEDs in solid-state lighting and display panels.

A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning.

Unmanned Aerial Vehicle (UAV) path planning is to plan an optimal path for its flight in a specific environment. But it cannot get satisfactory results using ordinary algorithms. To solve this problem, a hybrid algorithm is proposed named as PESSA, where particle swarm optimization (PSO) and an enhanced sparrow search algorithm (ESSA) work in parallel. In the ESSA, the random jump of the producer's position is strengthened to guarantee the global search ability. Each scrounger keeps learning from the vintage experience of the producers. For the best-positioned sparrow, when it perceives the threat, the difference between the best individual and the worst individual will be imposed to speed up the search process. The elite reverse search strategy was added to yields the optimum diversity. In this paper, the performance of the PESSA algorithm is verified by 10 basic functions, and it can find the optimal value on the 7 test functions. Compared with the other 12 algorithms, PESSA's average value always ranks first. Finally, the proposed PESSA is applied in 4 different scenarios including two groups of 2D environments and two groups of 3D environments. In 2D environments, the average optimization results can reach 0.0165 and 0.0521 in two cases respectively. In 3D environments, the average optimization results can reach 0.6635 and 0.5349 in two cases respectively. The results show that the PESSA algorithm can acquire more feasible and effective route than compared algorithms.

All-parameter calibration method of the on-orbit multi-view dynamic photogrammetry system.

Photogrammetry (PG) can present accurate data to evaluate the functional performance of large space structures. For camera calibration and orientation, the On-orbit Multi-view Dynamic Photogrammetry System (OMDPS) lacks appropriate spatial reference data. A multi-data fusion calibration method for all parameters for this kind of system is proposed in this paper as a solution to this issue. Firstly, a multi-camera relative position model is developed to solve the reference camera position unconstrained problem in the full-parameter calibration model of the OMDPS in accordance with the imaging model of stars and scale bar targets. Subsequently, the problem of adjustment failure and inaccurate adjustment in the multi-data fusion bundle adjustment is solved using the two-norm matrix and the weight matrix to adjust the Jacobian matrix with respect to all system parameters (e.g., camera interior parameters (CIP), camera exterior parameters (CEP), and lens distortion parameters (LDP)). Finally, all system parameters can be optimized simultaneously using this algorithm. In the actual data ground-based experiment, 333 spatial targets are measured using the V-star System (VS) and OMDPS. Taking the measurement of VS as the true value, the measurement results of OMDPS indicated that the in-plane Z-direction target coordinates root-mean-square error (RMSE) is less than 0.0538 mm and the Z-direction RMSE is less than 0.0428 mm. Out-of-plane Y-direction RMSE is less than 0.1514 mm. The application potential of the PG system for on-orbit measurement tasks is demonstrated through the actual data ground-based experiment.

Multi-task generative adversarial network for retinal optical coherence tomography image denoising.

Objective. Optical coherence tomography (OCT) has become an essential imaging modality for the assessment of ophthalmic diseases. However, speckle noise in OCT images obscures subtle but important morphological details and hampers its clinical applications. In this work, a novel multi-task generative adversarial network (MGAN) is proposed for retinal OCT image denoising.Approach. To strengthen the preservation of retinal structural information in the OCT denoising procedure, the proposed MGAN integrates adversarial learning and multi-task learning. Specifically, the generator of MGAN simultaneously undertakes two tasks, including the denoising task and the segmentation task. The segmentation task aims at the generation of the retinal segmentation map, which can guide the denoising task to focus on the retina-related region based on the retina-attention module. In doing so, the denoising task can enhance the attention to the retinal region and subsequently protect the structural detail based on the supervision of the structural similarity index measure loss.Main results. The proposed MGAN was evaluated and analyzed on three public OCT datasets. The qualitative and quantitative comparisons show that the MGAN method can achieve higher image quality, and is more effective in both speckle noise reduction and structural information preservation than previous denoising methods.Significance. We have presented a MGAN for retinal OCT image denoising. The proposed method provides an effective way to strengthen the preservation of structural information while suppressing speckle noise, and can promote the OCT applications in the clinical observation and diagnosis of retinopathy.

Terahertz Enhanced Sensing of Uric Acid Based on Metallic Slot Array Metamaterial.

An enzyme-free terahertz uric acid sensor based on a metallic slot array metamaterial was proposed and realized both theoretically and experimentally. The sensing model was verified in simulation and femtosecond laser processing technology was employed to ablate slots in the copper plate to fabricate metamaterials. Analytes were tested with liquid phase deposition on the metamaterial by a terahertz frequency domain spectroscopy system. Gradient concentrations of uric acid, ascorbic acid, and a mixture of them were measured separately with a good linear response. A significant decrease in sensitivity was observed in the ascorbic acid assay compared with the uric acid assay. The test results of the mixture also proved that our device is resistant to ascorbic acid. It is a simple and effective method for monitoring uric acid concentrations and the strategy of eliminating interference while modulating the resonance peak location mentioned here can be rationally projected for the development of other sensors.

Surface engineering of ZnO nanoparticles with diethylenetriamine for efficient red quantum-dot light-emitting diodes.

Due to the outstanding electron injection/transport capability of ZnO nanoparticles (NPs), quantum-dot light-emitting diodes (QLEDs) are commonly constructed by employing a hybrid device structure with ZnO electron-transporting layer and organic hole-transporting layer. However, the emission quenching of quantum dots and excessive electron injection induced by ZnO NPs also limits the device efficiency and operational stability. Here, diethylenetriamine (DETA) molecules as the ligands are introduced to modify the surface of ZnO NPs, which not only passivate the surface defects of ZnO but also suppress the overwhelming electron injection in the QLED. As a result, the device based on the DETA-modified ZnO NPs exhibits a peak external quantum efficiency of 23.7%, corresponding to an enhancement factor of 129% in comparison with that of the device with as-synthesized ZnO as the electron-transporting layer. The easy and feasible strategy may also be applicable to other photoelectric devices, such as solar cells and photodetectors.