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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 × 10-9â rad, implying a sensitivity of 4.7 × 10-10â rad/Hz1/2 for each 0.01 s measurement duration. In light intensity modulation mode, the uncertainty is 48.9 × 10-9â rad, indicating a sensitivity of 4.89 × 10-9â 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.
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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 -2.4â 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.
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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.
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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.
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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 13.5â nm with an absolute wavelength resolution of 4â pm and an absolute accuracy better than 20â pm.
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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.
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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.
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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.
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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.
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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.
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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 mâ 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.
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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.
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The changes of biomechanical properties, especially the elasticity of the ocular tissues, are closely related to some ophthalmic diseases. Currently, the ophthalmic optical coherence elastography (OCE) systems are dedicated either to the anterior segment or to the retina. The elasticity measurements of the whole eye remain challenging. Here we demonstrated an acoustic radiation force optical coherence elastography (ARF-OCE) method to quantify the elasticity of the cornea and the retina. The experiment results show that the Young's moduli of the cornea and the retina were 16.66 ± 6.51 kPa and 207.96 ± 4.75 kPa, respectively. Our method can measure the elasticity of the anterior segment and the posterior segment, and provides a powerful tool to enhance ophthalmology research.
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Diagnóstico por Imagen de Elasticidad , Elasticidad , Diagnóstico por Imagen de Elasticidad/métodos , Fantasmas de Imagen , Retina , Tomografía de Coherencia Óptica/métodosRESUMEN
In this Letter, we propose an all-optical diffractive deep neural network modeling method based on nonlinear optical materials. First, the nonlinear optical properties of graphene and zinc selenide (ZnSe) are analyzed. Then the optical limiting effect function corresponding to the saturation absorption coefficient of the nonlinear optical materials is fitted. The optical limiting effect function is taken as the nonlinear activation function of the neural network. Finally, the all-optical diffractive neural network model based on nonlinear materials is established. The numerical simulation results show that the model can effectively improve the nonlinear representation ability of the all-optical diffractive neural network. It provides a theoretical support for the further realization of a photonic artificial intelligence chip based on nonlinear optical materials.
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The referenced article [Appl. Opt.56, 9325 (2017)APOPAI0003-693510.1364/AO.56.009325] has been retracted by the authors.
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Fibras Ópticas , Piel , AnimalesRESUMEN
Fano resonance has an asymmetric and sharp resonance peak near the resonance wavelength, enhancing optical modulation performance. Here, a Fano resonant silicon optical modulator with a micro-ring resonator (MRR) coupled with a T-shaped waveguide is designed. Compared with an MRR modulator, a Fano resonance-based modulator has a smaller wavelength range of changes in optical intensity (from 0 a.u. to 1 a.u.). Under the condition of achieving the same light intensity change, Fano resonance only needs to shift the wavelength by 0.07 times compared with MRR. By optimizing the doping section and the Fano resonance line shape, the modulation depth of the Fano modulator is 12.44 dB, and an insertion loss of 0.41 dB is obtained. Moreover, it improves the modulation linearity. This modulator provides a new idea, to the best of our knowledge, for the single-cavity Fano resonance modulator.
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Near-space airships are high-end airships that are being vigorously developed in the aerospace industry. It has important application value in the telecommunication, surveillance, monitoring, remote sensing, and exploration fields. The envelope is the key component that provides lift to the airship. Online monitoring of envelope status is critical to ensuring airship performance, safety, and reliability. However, online monitoring of the 3D shape and strain of the airship envelope is still a challenging task. A hybrid multi-core and single-core fiber-optic monitoring method with a temperature self-compensation function is proposed to address this issue. The method uses multi-core fiber optic sensors, 3D curves, and a surface reconstruction algorithm to obtain the 3D shape of the envelope. Temperature decoupling of the sensing signal is carried out via sensors on the central core of the multi-core fibers that are only sensitive to temperature, thereby eliminating the influence of temperature changes on the measurement accuracy. The strain field of the envelope skin is measured by single-core fiber optic sensors and a strain interpolation algorithm. The accuracy of the proposed method is experimentally validated. The results show that the 3D shape measurement error of the envelope skin is 4.82% when the skin is bent in the range of 10m -1-15.38m -1. When the ambient temperature changes in the range of -50∘ C-150∘ C, the position measurement error caused by the temperature change is only 1.2% of the effective measurement length (160 mm) of the multi-core fiber optic sensor. When the skin is stretched in the range of 500-5000µÎµ, the measurement error of the average value of the skin strain field is only 0.75%. This proves that the proposed method can simultaneously measure the 3D shape and strain field of the envelope skin and also effectively suppress the influence of ambient temperature changes on the measurement accuracy. The proposed method has application prospects in the online monitoring of airship envelopes.
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Due to their flexible structure and excellent optical characteristics hollow-core photonic crystal fibers (HC-PCFs) are used in many fields, such as active optical devices, communications, and optical fiber sensing. In this paper, to analyze the characteristics of HC-PCFs, we carried out finite element analysis and analyzed the design for the band gap cladding structure of HC-PCFs. First, the characteristics of HC19-1550 and HC-1550-02 in the C-band were simulated. Subsequently, the structural optimization of the seven-cell HC-1550-02 and variations in characteristics of the optimized HC-1550-02 in the wavelength range 1250-1850 nm were investigated. The simulation results revealed that the optimal number of cladding layers is eight, the optimal core radius is 1.8 times the spacing of adjacent air holes, and the optimal-relative thickness of the core quartz-ring is 2.0. In addition, the low confinement loss bandwidth of the optimized structure is 225 nm. Under the transmission bandwidth of the optimized structure, the core optical power is above 98%, the confinement loss is below 9.0 × 10-3 dB/m, the variation range of the effective mode field area does not exceed 10 µm2, and the relative sensitivity is above 0.9570. The designed sensor exhibits an ultra-high relative sensitivity and almost zero confinement loss, making it highly suitable for high-sensitivity gas or liquid sensing.
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An Ag-graphene layers-coated H-shaped photonic crystal fiber (PCF) surface plasmon resonance (SPR) sensor with a U-shaped grooves open structure for refractive index (RI) sensing is proposed and numerically simulated by the finite element method (FEM). The designed sensor could solve the problems of air-holes material coating and analyte filling in PCF. Two big air-holes in the x-axis produce a birefringence phenomenon leading to the confinement loss and sensitivity of x-polarized light being much stronger than y-polarized. Graphene is deposited on the layer of silver in the grooves; its high surface to volume ratio and rich π conjugation make it a suitable dielectric layer for sensing. The effect of structure parameters such as air-holes size, U-shaped grooves depth, thickness of the silver layer and number of graphene layers on the sensing performance of the proposed sensor are numerical simulated. A large analyte RI range from 1.33 to 1.41 is calculated and the highest wavelength sensitivity is 12,600 nm/RIU. In the linear RI sensing region of 1.33 to 1.36; the average wavelength sensitivity we obtained can reach 2770 nm/RIU with a resolution of 3.61 × 10-5 RIU. This work provides a reference for developing a high-sensitivity; multi-parameter measurement sensor potentially useful for water pollution monitoring and biosensing in the future.
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A high throughput measurement method of human red blood cells (RBCs) deformability combined with optical tweezers technology and the microfluidic chip was proposed to accurately characterize the deformability of RBCs statistically. Firstly, the effective stretching deformation of RBCs was realized by the interaction of photo-trapping force and fluid viscous resistance. Secondly, the characteristic parameters before and after the deformation of the single cell were extracted through the image processing method to obtain the deformation index of area and circumference. Finally, statistical analysis was performed, and the average deformation index parameters (DIS¯, DIC¯) were used to characterize the deformability of RBCs. A high-throughput detection system was built, and the optimal experimental conditions were obtained through a large number of experiments. Three groups of samples with different deformability were used for statistical verification. The results showed that the smallest cell component DIS¯ was 9.71%, and the detection flux of 8-channel structure was about 370 cells/min. High-throughput detection and characterization methods can effectively distinguish different deformed RBCs statistically, which provides a solution for high-throughput deformation analysis of other types of samples.