Abstract:The multi-wavelength optical switch based on an all-dielectric metastructure consisting of four asymmetric semi-circular rings was designed and analyzed in this paper. Four Fano resonance modes, which can be explained by bound states in the continuum (BIC) theory, are excited in our structure with a maximum Q-factor of about 2 450 and a modulation depth close to 100%. By changing the polarization direction of the incident light, the transmission amplitude of Fano resonances can get effectively modulated. Based on this tuning property, the metastructure can achieve a multi-wavelength optical switch in the near-infrared region (900—980 nm) and the maximum extinction ratio can reach 38.3 dB. In addition, the results indicate that the Fano resonances are sensitive to the changes in the refractive index. The sensitivity (S) and the figure of merit (FOM) are 197 nm/RIU and 492 RIU-1. The proposed metastructure has promising potential in applications such as optical switches, sensors, modulators and lasers.

Abstract:In this paper, we present an electrically controlled tunable narrowband filter based on a thin-film lithium niobate two-dimensional (2D) photonic crystal. The filter incorporates a photonic crystal microcavity structure within the straight waveguide, enabling electronic tuning of the transmitted wavelength through added electrode structures. The optimized microcavity filter design achieves a balance between high transmission rate and quality factor, with a transmission center wavelength of 1 551.6 nm, peak transmission rate of 96.1%, and quality factor of 5 054. Moreover, the filter can shift the central wavelength of the transmission spectrum by applying voltage to the electrodes, with a tuning sensitivity of 13.8 pm/V. The proposed tunable filter adopts a simple-to-fabricate air-hole structure and boasts a compact size (length:11.57 μm, width:5.27 μm, area:60.97 μm2), making it highly suitable for large-scale integration. These features make the filter promising for broad applications in the fields of photonic integration and optical communication.

Abstract:The noise-like pulses (NLPs) with tunable fraction of the pedestal height in the whole intensity autocorrelation (AC) trace are numerically demonstrated in the designed erbium-doped fiber (EDF) mode-locked laser, which contains the saturable absorber (SA) with nonlinear polarization rotation (NPR), sinusoidal-shaped or Gaussian-shaped filter, two segments of EDFs, and two pieces of single-mode fibers (SMFs) with normal dispersion and anomalous dispersion, respectively. The pedestal ratio of the intensity AC trace can be tuned by changing the gain saturation energies of EDFs. The results show that when the net cavity dispersion is 1.06 ps2, the tuning range of the pedestal ratio for the NLPs can reach its maximum values, which are 0.51—0.89 and 0.58—0.88 for the sinusoidal-shaped and Gaussian-shaped filters, respectively. In addition, an appropriate choice of filter bandwidth is also conducive to obtain a wide range of the tuning pedestal ratio for the intensity AC trace.

Abstract:In order to provide a method for accurately detecting the concentration and types of heavy metal ions in water, a fluid ion detection system is designed. It consists of a side-polished fiber-assisted fluid structure and a long-period fiber grating (LPFG) coated with a metal chelating agent membrane. In this study, both theoretical and experimental investigations are conducted to examine the sensing characteristics of the system towards copper ion and iron ion solutions. The results demonstrate that under the premise of ensuring solution flow, the system can achieve specific identification of different types of heavy metal ions. Furthermore, it exhibits concentration sensing sensitivities of 9.23×104 mL.nm/mol and 7.13×104 mL.nm/mol for copper sulfate (CuSO4) and ferric chloride (FeCl3) solutions, respectively. Therefore, this sensing system offers the potential for real-time detection of metal ions.

Abstract:In order to compensate the dispersion accumulated in a single mode fiber (SMF) for higher communication capacity, a simplified dispersion-compensation microstructure fiber (DC-MSF) with seven cores is proposed in this paper. The fiber’s cladding is made of pure silica without air holes, and its outer cores are composed of six germanium up-doped cylinders, which has the advantage of simple structure. The finite element method (FEM) and beam propagation method (BPM) are used to study the properties of the fiber, and the relationship between the structural parameters of the fiber and the dispersion, as well as the phase matching wavelength, is obtained. By optimizing the structural parameters of the fiber, the dispersion of the fiber can reach −5 291.47 ps.nm-1.km-1 at 1 550 nm, and the coupling loss to the conventional single-mode fiber is only 0.137 dB. Compared with the conventional dispersion-compensation fiber, the fiber has lots of advantages, such as single mode transmission, easy to fabricate and low coupling loss with traditional SMF, etc.

Abstract:The distributed acoustic sensing technology was used for real-time speech reproduction and recognition, in which the voiceprint can be extracted by the Mel frequency cepstral coefficient (MFCC) method. A classic ancient Chinese poem “You Zi Yin”, also called “A Traveler’s Song”, was analyzed both in time and frequency domains, where its real-time reproduction was achieved with a 116.91 ms time delay. The smaller scaled MFCC0 at 1/12 of MFCC matrix was taken as a feature vector of each line against the ambient noise, which provides a recognition method via cross-correlation among the 6 original and recovered verse pairs. The averaged cross-correlation coefficient of the matching pairs is calculated to be 0.580 6 higher than 0.188 3 of the nonmatched pairs, promising an accurate and fast method for real-time speech reproduction and recognition over a passive optical fiber.

Abstract:Phase unwrapping is used to establish the mapping relationship between camera and projector, which is one of the key technologies in fringe projection profilometry (FPP) based three-dimensional (3D) measurement. Although complementary Gray code assisted phase unwrapping technology can get a good result on the periodic boundary, it needs more coded images to obtain a high frequency fringe. Aiming at this problem, a complementary binary code assisted phase unwrapping method is proposed in this paper. According to the periodic consistency between the wrapping phase and binary codes, the coded patterns are generated. Then the connected domain strategy is performed to calculate the fringe orders using the positive and negative image binaryzation. To avoid the mistake near the periodic boundary, complementary binary code inspired by the complementary Gray code is proposed. The fringe order correction is also discussed for different situations in the first measured period. Only two binary images are needed in the proposed method, and the fringe frequency is not limited. Both the simulation and experiment have verified the feasibility of proposed method.

Abstract:Remote sensing images are taken at high altitude from above, with complex spatial scenes of images and a large number of target types. The detection of image targets on large scale remote sensing images suffers from the problem of small target size and target density. This paper proposes an improved model for remote sensing image detection based on you only look once version 7 (YOLOv7). First, the small-scale detection layer is added to reacquire tracking frames to improve the network's recognition ability of small-scale targets, and then Bottleneck Transformers are fused in the backbone to make full use of the convolutional neural network (CNN)+Transformer architecture to enhance the feature extraction ability of the network. After that, the convolutional block attention module (CBAM) mechanism is added in the head to improve the model's ability of small-scale target. Finally, the non-maximum suppressed (NMS) of YOLOv7 algorithm is changed to distance intersection over union-non maximum suppression (DIOU-NMS) to improve the detection ability of overlapping targets in the network. The results show that the method in this paper can improve the detection rate of small-scale targets in remote sensing images and effectively solve the problem of high overlap and is tested on the NWPU-VHR10 and DOTA1.0 datasets, and the accuracy of the improved model is improved by 6.3% and 4.2%, respectively, compared with the standard YOLOv7 algorithm.

Abstract: The effectiveness of deep learning networks in detecting small objects is limited, thereby posing challenges in addressing practical object detection tasks. In this research, we propose a small object detection model that operates at multiple scales. The model incorporates a multi-level bidirectional pyramid structure, which integrates deep and shallow networks to simultaneously preserve intricate local details and augment global features. Moreover, a dedicated multi-scale detection head is integrated into the model, specifically designed to capture crucial information pertaining to small objects. Through comprehensive experimentation, we have achieved promising results, wherein our proposed model exhibits a mean average precision (mAP) that surpasses that of the well-established you only look once version 7 (YOLOv7) model by 1.1%. These findings validate the improved performance of our model in both conventional and small object detection scenarios.

Abstract:Breast cancer is the most common malignant tumor in women, which seriously threatens the physical and mental health of women worldwide. The existing detection methods have problems, such as large sample consumption, time-consuming sample preparation, expensive equipment, and low sensitivity. In order to solve these problems, this paper proposes a method for quickly detecting breast cancer using surface-functionalized terahertz metamaterial biosensors. The use of PIK3CA-modified sensors enhances the detection sensitivity and specificity of exosomes. Based on the red shift of the sensor absorption peak caused by exosomes, breast cancer patients can be distinguished from healthy controls. This study demonstrates that exosome detection is effective for the repeatable and non-invasive diagnosis of breast cancer patients. The terahertz metamaterial biosensor designed in this paper has high specificity, repeatability, and sensitivity, and has great potential for application in the development of modern diagnostic instruments.