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Published in last 1 year |  In last 2 years |  In last 3 years |  All Please wait a minute... For selected: Download citations EndNote Ris BibTeX Toggle thumbnails Select Visualizing and witnessing first-order coherence, Bell nonlocality and purity by using a quantum steering ellipsoid in the non-inertial frame Huan Yang(杨欢), Ling-Ling Xing(邢玲玲), Ming-Ming Du(杜明明), Min Kong(孔敏), Gang Zhang(张刚), and Liu Ye(叶柳) Chin. Phys. B, 2023, 32 (10): 100305.   DOI: 10.1088/1674-1056/acb762 Abstract （256）   HTML （0）    PDF （3227KB）（194）       Knowledge map    A quantum steering ellipsoid (QSE) is a visual characterization for bipartite qubit systems, and it is also a novel avenue for describing and detecting quantum correlations. Herein, by using a QSE, we visualize and witness the first-order coherence (FOC), Bell nonlocality (BN) and purity under non-inertial frames. Also, the collective influences of the depolarizing channel and the non-coherence-generating channel (NCGC) on the FOC, BN and purity are investigated in the QSE formalism. The results reveal that the distance from the center of the QSE to the center of the Bloch sphere visualizes the FOC of a bipartite system, the lengths of the QSE semiaxis visualize the BN, and the QSE's shape and position dominate the purity of the system. One can capture the FOC, BN and purity via the shape and position of the QSE in the non-inertial frame. The depolarizing channel (the NCGC) gives rise to the shrinking and degradation (the periodical oscillation) of the QSE. One can use these traits to visually characterize and detect the FOC, BN and purity under the influence of external noise. Of particular note is that the condition for the QSE to achieve the center of the Bloch sphere cannot be influenced by the depolarizing channel and the NCGC. The characterization shows that the conditions for the disappearance of the FOC are invariant under the additional influences of the depolarizing channel and NCGC. Select Fixed-time group consensus of second-order multi-agent systems based on event-triggered control Xiaoshuai Wu(武肖帅), Fenglan Sun(孙凤兰), Wei Zhu(朱伟), and Jürgen Kurths Chin. Phys. B, 2023, 32 (7): 070701.   DOI: 10.1088/1674-1056/acb9ee Abstract （193）   HTML （5）    PDF （1023KB）（254）       Knowledge map    The problem of fixed-time group consensus for second-order multi-agent systems with disturbances is investigated. For cooperative-competitive network, two different control protocols, fixed-time group consensus and fixed-time event-triggered group consensus, are designed. It is demonstrated that there is no Zeno behavior under the designed event-triggered control. Meanwhile, it is proved that for an arbitrary initial state of the system, group consensus within the settling time could be obtained under the proposed control protocols by using matrix analysis and graph theory. Finally, a series of numerical examples are propounded to illustrate the performance of the proposed control protocol. Select Influence of the initial parameters on soliton interaction in nonlinear optical systems Xinyi Zhang(张昕仪) and Ye Wu(吴晔) Chin. Phys. B, 2023, 32 (7): 070505.   DOI: 10.1088/1674-1056/ace1da Abstract （172）   HTML （2）    PDF （1573KB）（134）       Knowledge map    In nonlinear optical systems, optical solitons have the transmission properties of reducing error rate, improving system security and stability, and have important research significance in future research on all optical communication. This paper uses the bilinear method to obtain the two-soliton solutions of the nonlinear Schrödinger equation. By analyzing the relevant physical parameters in the obtained solutions, the interaction between optical solitons is optimized. The influence of the initial conditions on the interactions of the optical solitons is analyzed in detail, the reason why the interaction of the optical solitons is sensitive to the initial condition is discussed, and the interactions of the optical solitons are effectively weakened. The relevant results are beneficial for reducing the error rate and promoting the communication quality of the system. Select Soliton propagation for a coupled Schrödinger equation describing Rossby waves Li-Yang Xu(徐丽阳), Xiao-Jun Yin(尹晓军), Na Cao(曹娜) and Shu-Ting Bai(白淑婷) Chin. Phys. B, 2023, 32 (7): 070202.   DOI: 10.1088/1674-1056/acb9e5 Abstract （157）   HTML （2）    PDF （4449KB）（102）       Knowledge map    We study a coupled Schrödinger equation which is started from the Boussinesq equation of atmospheric gravity waves by using multiscale analysis and reduced perturbation method. For the coupled Schrödinger equation, we obtain the Manakov model of all-focusing, all-defocusing and mixed types by setting parameters value and apply the Hirota bilinear approach to provide the two-soliton and three-soliton solutions. Especially, we find that the all-defocusing type Manakov model admits bright-bright soliton solutions. Furthermore, we find that the all-defocusing type Manakov model admits bright-bright-bright soliton solutions. Therefrom, we go over how the free parameters affect the Manakov model's all-focusing type's two-soliton and three-soliton solutions' collision locations, propagation directions, and wave amplitudes. These findings are useful for setting a simulation scene in Rossby waves research. The answers we have found are helpful for studying physical properties of the equation in Rossby waves. Select Interaction solutions and localized waves to the (2+1)-dimensional Hirota-Satsuma-Ito equation with variable coefficient Xinying Yan(闫鑫颖), Jinzhou Liu(刘锦洲), and Xiangpeng Xin(辛祥鹏) Chin. Phys. B, 2023, 32 (7): 070201.   DOI: 10.1088/1674-1056/acb9f2 Abstract （155）   HTML （2）    PDF （3208KB）（126）       Knowledge map    This article investigates the Hirota-Satsuma-Ito equation with variable coefficient using the Hirota bilinear method and the long wave limit method. The equation is proved to be Painlevé integrable by Painlevé analysis. On the basis of the bilinear form, the forms of two-soliton solutions, three-soliton solutions, and four-soliton solutions are studied specifically. The appropriate parameter values are chosen and the corresponding figures are presented. The breather waves solutions, lump solutions, periodic solutions and the interaction of breather waves solutions and soliton solutions, etc. are given. In addition, we also analyze the different effects of the parameters on the figures. The figures of the same set of parameters in different planes are presented to describe the dynamical behavior of solutions. These are important for describing water waves in nature. Select Transition from isotropic to polar state of self-driven eccentric disks Jinghan Wang(王静晗), Tianliang Xu(许天亮), Jingxi He(何景熙), Kang Chen(陈康), and Wende Tian(田文得) Chin. Phys. B, 2023, 32 (7): 070501.   DOI: 10.1088/1674-1056/accd4d Abstract （153）   HTML （2）    PDF （2338KB）（68）       Knowledge map    Inspired by the eccentricity design of self-driven disks, we propose a computational model to study the remarkable behavior of this kind of active matter via Langevin dynamics simulations. We pay attention to the effect of rotational friction coefficient and rotational noise on the phase behavior. A homogeneous system without rotational noise exhibits a sharp discontinuous transition of orientational order from an isotropic to a polar state with the increase of rotational friction coefficient. When there is rotational noise, the transition becomes continuous. The formation of polar state originates from the effective alignment effect due to the mutual coupling of the positional and orientational degrees of freedom of each disk. The rotational noise could weaken the alignment effect and cause the large spatial density inhomogeneity, while the translational noise homogenizes the system. Our model makes further conceptual progress on how the microscopic interaction among self-driven agents yields effective alignment. Select Efficient semi-quantum secret sharing protocol using single particles Ding Xing(邢丁), Yifei Wang(王艺霏), Zhao Dou(窦钊), Jian Li(李剑),Xiubo Chen(陈秀波), and Lixiang Li(李丽香) Chin. Phys. B, 2023, 32 (7): 070308.   DOI: 10.1088/1674-1056/ace159 Abstract （152）   HTML （1）    PDF （495KB）（78）       Knowledge map    Semi-quantum secret sharing (SQSS) is a branch of quantum cryptography which only requires the dealer to have quantum capabilities, reducing the difficulty of protocol implementation. However, the efficiency of the SQSS protocol still needs to be further studied. In this paper, we propose a semi-quantum secret sharing protocol, whose efficiency can approach 100% as the length of message increases. The protocol is based on single particles to reduce the difficulty of resource preparation. Particle reordering, a simple but effective operation, is used in the protocol to improve efficiency and ensure security. Furthermore, our protocol can share specific secrets while most SQSS protocols could not. We also prove that the protocol is secure against common attacks. Select Variational quantum semi-supervised classifier based on label propagation Yan-Yan Hou(侯艳艳), Jian Li(李剑), Xiu-Bo Chen(陈秀波), and Chong-Qiang Ye(叶崇强) Chin. Phys. B, 2023, 32 (7): 070309.   DOI: 10.1088/1674-1056/acb9fb Abstract （150）   HTML （2）    PDF （707KB）（22）       Knowledge map    Label propagation is an essential semi-supervised learning method based on graphs, which has a broad spectrum of applications in pattern recognition and data mining. This paper proposes a quantum semi-supervised classifier based on label propagation. Considering the difficulty of graph construction, we develop a variational quantum label propagation (VQLP) method. In this method, a locally parameterized quantum circuit is created to reduce the parameters required in the optimization. Furthermore, we design a quantum semi-supervised binary classifier based on hybrid Bell and Z bases measurement, which has a shallower circuit depth and is more suitable for implementation on near-term quantum devices. We demonstrate the performance of the quantum semi-supervised classifier on the Iris data set, and the simulation results show that the quantum semi-supervised classifier has higher classification accuracy than the swap test classifier. This work opens a new path to quantum machine learning based on graphs. Select Vibrational resonance in globally coupled bistable systems under the noise background Jiangling Liu(刘江令), Chaorun Li(李朝润), Hailing Gao(高海玲), and Luchun Du(杜鲁春) Chin. Phys. B, 2023, 32 (7): 070502.   DOI: 10.1088/1674-1056/acc05f Abstract （148）   HTML （3）    PDF （846KB）（41）       Knowledge map    Effects of system size, coupling strength, and noise on vibrational resonance (VR) of globally coupled bistable systems are investigated. The power spectral amplifications obtained by the three methods all show that the VR exists over a wide range of parameter values. The increase in system size induces and enhances the VR, while the increase in noise intensity suppresses and eventually eliminates the VR. Both the stochastic resonance and the system size resonance can coexist with the VR in different parameter regions. This research has potential applications to the weak signal detection process in stochastic multi-body systems. Select A new method of constructing adversarial examples for quantum variational circuits Jinge Yan(颜金歌), Lili Yan(闫丽丽), and Shibin Zhang(张仕斌) Chin. Phys. B, 2023, 32 (7): 070304.   DOI: 10.1088/1674-1056/ac9b32 Abstract （148）   HTML （5）    PDF （725KB）（123）       Knowledge map    A quantum variational circuit is a quantum machine learning model similar to a neural network. A crafted adversarial example can lead to incorrect results for the model. Using adversarial examples to train the model will greatly improve its robustness. The existing method is to use automatic differentials or finite difference to obtain a gradient and use it to construct adversarial examples. This paper proposes an innovative method for constructing adversarial examples of quantum variational circuits. In this method, the gradient can be obtained by measuring the expected value of a quantum bit respectively in a series quantum circuit. This method can be used to construct the adversarial examples for a quantum variational circuit classifier. The implementation results prove the effectiveness of the proposed method. Compared with the existing method, our method requires fewer resources and is more efficient. Select Quantum homomorphic broadcast multi-signature based on homomorphic aggregation Xin Xu(徐鑫) and Ai-Han Yin(殷爱菡) Chin. Phys. B, 2023, 32 (7): 070302.   DOI: 10.1088/1674-1056/acac0e Abstract （148）   HTML （2）    PDF （528KB）（88）       Knowledge map    Quantum multi-signature has attracted extensive attention since it was put forward. Beside its own improvement, related research is often combined with other quantum signature. However, this type of quantum signature has one thing in common, that is, the generation and verification of signature depend heavily on the shared classical secret key. In order to increase the reliability of signature, the homomorphic aggregation technique is applied to quantum multi-signature, and then we propose a quantum homomorphic multi-signature protocol. Unlike previous quantum multi-signature protocols, this protocol utilizes homomorphic properties to complete signature generation and verification. In the signature generation phase, entanglement swapping is introduced, so that the individual signatures of multiple users are aggregated into a new multi-signature. The original quantum state is signed by the shared secret key to realize the verification of the signature in the verification phase. The signature process satisfies the homomorphic property, which can improve the reliability of the signature. Select First-order quantum phase transition and entanglement in the Jaynes-Cummings model with a squeezed light Chun-Qi Tang(汤椿琦) and Li-Tuo Shen(沈利托) Chin. Phys. B, 2023, 32 (7): 070303.   DOI: 10.1088/1674-1056/acb9f0 Abstract （147）   HTML （4）    PDF （2176KB）（51）       Knowledge map    We study the quantum phase transition and entanglement in the Jaynes-Cummings model with squeezed light, utilize a special transformation method to obtain the analytical ground state of the model within the near-resonance regime, and numerically verify the validity of the analytical ground state. It is found that the ground state exhibits a first-order quantum phase transition at the critical point linearly induced by squeezed light, and the ground state entanglement reaches its maximum when the qubit-field coupling strength is large enough at the critical point. Select ESR-PINNs: Physics-informed neural networks with expansion-shrinkage resampling selection strategies Jianan Liu(刘佳楠), Qingzhi Hou(侯庆志), Jianguo Wei(魏建国), and Zewei Sun(孙泽玮) Chin. Phys. B, 2023, 32 (7): 070702.   DOI: 10.1088/1674-1056/acc1d5 Abstract （145）   HTML （3）    PDF （3330KB）（40）       Knowledge map    Neural network methods have been widely used in many fields of scientific research with the rapid increase of computing power. The physics-informed neural networks (PINNs) have received much attention as a major breakthrough in solving partial differential equations using neural networks. In this paper, a resampling technique based on the expansion-shrinkage point (ESP) selection strategy is developed to dynamically modify the distribution of training points in accordance with the performance of the neural networks. In this new approach both training sites with slight changes in residual values and training points with large residuals are taken into account. In order to make the distribution of training points more uniform, the concept of continuity is further introduced and incorporated. This method successfully addresses the issue that the neural network becomes ill or even crashes due to the extensive alteration of training point distribution. The effectiveness of the improved physics-informed neural networks with expansion-shrinkage resampling is demonstrated through a series of numerical experiments. Select Inatorial forecasting method considering macro and micro characteristics of chaotic traffic flow Yue Hou(侯越), Di Zhang(张迪), Da Li(李达), and Ping Yang(杨萍) Chin. Phys. B, 2023, 32 (10): 100508.   DOI: 10.1088/1674-1056/acd3df Abstract （142）   HTML （1）    PDF （981KB）（40）       Knowledge map    Traffic flow prediction is an effective strategy to assess traffic conditions and alleviate traffic congestion. Influenced by external non-stationary factors and road network structure, traffic flow sequences have macro spatiotemporal characteristics and micro chaotic characteristics. The key to improving the model prediction accuracy is to fully extract the macro and micro characteristics of traffic flow time sequences. However, traditional prediction model by only considers time features of traffic data, ignoring spatial characteristics and nonlinear characteristics of the data itself, resulting in poor model prediction performance. In view of this, this research proposes an intelligent combination prediction model taking into account the macro and micro features of chaotic traffic data. Firstly, to address the problem of time-consuming and inefficient multivariate phase space reconstruction by iterating nodes one by one, an improved multivariate phase space reconstruction method is proposed by filtering global representative nodes to effectively realize the high-dimensional mapping of chaotic traffic flow. Secondly, to address the problem that the traditional combinatorial model is difficult to adequately learn the macro and micro characteristics of chaotic traffic data, a combination of convolutional neural network (CNN) and convolutional long short-term memory (ConvLSTM) is utilized for capturing nonlinear features of traffic flow more comprehensively. Finally, to overcome the challenge that the combined model performance degrades due to subjective empirical determined network parameters, an improved lightweight particle swarm is proposed for improving prediction accuracy by optimizing model hyperparameters. In this paper, two highway datasets collected by the Caltrans Performance Measurement System (PeMS) are taken as the research objects, and the experimental results from multiple perspectives show that the comprehensive performance of the method proposed in this research is superior to those of the prevalent methods. Select Dynamical analysis, geometric control and digital hardware implementation of a complex-valued laser system with a locally active memristor Yi-Qun Li(李逸群), Jian Liu(刘坚), Chun-Biao Li(李春彪), Zhi-Feng Hao(郝志峰), and Xiao-Tong Zhang(张晓彤) Chin. Phys. B, 2023, 32 (8): 080503.   DOI: 10.1088/1674-1056/acd68b Abstract （141）   HTML （1）    PDF （4704KB）（179）       Knowledge map    In order to make the peak and offset of the signal meet the requirements of artificial equipment, dynamical analysis and geometric control of the laser system have become indispensable. In this paper, a locally active memristor with non-volatile memory is introduced into a complex-valued Lorenz laser system. By using numerical measures, complex dynamical behaviors of the memristive laser system are uncovered. It appears the alternating appearance of quasi-periodic and chaotic oscillations. The mechanism of transformation from a quasi-periodic pattern to a chaotic one is revealed from the perspective of Hamilton energy. Interestingly, initial-values-oriented extreme multi-stability patterns are found, where the coexisting attractors have the same Lyapunov exponents. In addition, the introduction of a memristor greatly improves the complexity of the laser system. Moreover, to control the amplitude and offset of the chaotic signal, two kinds of geometric control methods including amplitude control and rotation control are designed. The results show that these two geometric control methods have revised the size and position of the chaotic signal without changing the chaotic dynamics. Finally, a digital hardware device is developed and the experiment outputs agree fairly well with those of the numerical simulations. Select Turing/Turing-like patterns: Products of random aggregation of spatial components Jian Gao(高见), Xin Wang(王欣), Xinshuang Liu(刘心爽), and Chuansheng Shen(申传胜) Chin. Phys. B, 2023, 32 (7): 070503.   DOI: 10.1088/1674-1056/acc0f9 Abstract （140）   HTML （1）    PDF （6816KB）（29）       Knowledge map    Turing patterns are typical spatiotemporal ordered structures in various systems driven far from thermodynamic equilibrium. Turing's reaction-diffusion theory, containing a long-range inhibiting agent and a local catalytic agent, has provided an explanation for the formation of some patterns in nature. Numerical, experimental and theoretical studies about Turing/Turing-like patterns have been generally focused on systems driven far from thermodynamic equilibrium. The local dynamics of these systems are commonly very complex, which brings great difficulties to understanding of formation of patterns. Here, we investigate a type of Turing-like patterns in a near-equilibrium thermodynamic system experimentally and theoretically, and put forward a new formation mechanism and a quantitative method for Turing/Turing-like patterns. Specifically, we observe a type of Turing-like patterns in starch solutions, and study the effect of concentration on the structure of patterns. The experimental results show that, with the increase of concentration, patterns change from spots to inverse spots, and labyrinthine stripe patterns appear in the region of intermediate concentration. We analyze and model the formation mechanism of these patterns observed in experiments, and the simulation results agree with the experimental results. Our conclusion indicates that the random aggregation of spatial components leads to formation of these patterns, and the proportion of spatial components determines the structures. Our findings shed light on the formation mechanism for Turing/Turing-like patterns. Select A deep learning method based on prior knowledge with dual training for solving FPK equation Denghui Peng(彭登辉), Shenlong Wang(王神龙), and Yuanchen Huang(黄元辰) Chin. Phys. B, 2024, 33 (1): 010202.   DOI: 10.1088/1674-1056/ad071b Abstract （139）   HTML （2）    PDF （7755KB）（120）       Knowledge map    The evolution of the probability density function of a stochastic dynamical system over time can be described by a Fokker—Planck—Kolmogorov (FPK) equation, the solution of which determines the distribution of macroscopic variables in the stochastic dynamic system. Traditional methods for solving these equations often struggle with computational efficiency and scalability, particularly in high-dimensional contexts. To address these challenges, this paper proposes a novel deep learning method based on prior knowledge with dual training to solve the stationary FPK equations. Initially, the neural network is pre-trained through the prior knowledge obtained by Monte Carlo simulation (MCS). Subsequently, the second training phase incorporates the FPK differential operator into the loss function, while a supervisory term consisting of local maximum points is specifically included to mitigate the generation of zero solutions. This dual-training strategy not only expedites convergence but also enhances computational efficiency, making the method well-suited for high-dimensional systems. Numerical examples, including two different two-dimensional (2D), six-dimensional (6D), and eight-dimensional (8D) systems, are conducted to assess the efficacy of the proposed method. The results demonstrate robust performance in terms of both computational speed and accuracy for solving FPK equations in the first three systems. While the method is also applicable to high-dimensional systems, such as 8D, it should be noted that computational efficiency may be marginally compromised due to data volume constraints. Select Orientation determination of nitrogen-vacancy center in diamond using a static magnetic field Yangpeng Wang(王杨鹏), Rujian Zhang(章如健), Yan Yang(杨燕), Qin Wu(吴琴), Zhifei Yu(于志飞), and Bing Chen(陈冰) Chin. Phys. B, 2023, 32 (7): 070301.   DOI: 10.1088/1674-1056/acc0f7 Abstract （138）   HTML （2）    PDF （1149KB）（132）       Knowledge map    Nitrogen-vacancy (NV) centers in a bulk diamond are often employed to realize measurement of multiple physical quantities, which depends on orientation information of NV axis. We report a fast and effective method to determine the orientation of NV axis with the aid of a static magnetic field. By measuring the optically detected magnetic resonance spectra, we can precisely extract the polar angle information between the NV axis and the known magnetic field. Combining with the polar angle information of different kinds of NV centers, we employ the Nelder-Mead algorithm to get the optimal solution of the orientation of NV axis. This method is simple and efficient, and is easily applied in NV-based quantum sensing. Select Optical anapole modes in hybrid metal-dielectric nanoantenna for near-field enhancement and optical sensing Debao Wang(王德宝), Jingwei Lv(吕靖薇), Wei Liu(刘伟), Yanru Ren(任艳茹), Wei Li(李薇), Xinchen Xu(许鑫辰), Chao Liu(刘超), and Paul K Chu(朱剑豪) Chin. Phys. B, 2023, 32 (11): 110204.   DOI: 10.1088/1674-1056/acfaf4 Abstract （138）   HTML （0）    PDF （4610KB）（54）       Knowledge map    Metal-dielectric nanostructures in the optical anapole modes are essential for light-matter interactions due to the low material loss and high near-field enhancement. Herein, a hybrid metal-dielectric nanoantenna composed of six wedge-shaped gold (Au) nanoblocks as well as silica (SiO2) and silicon (Si) nanodiscs is designed and analyzed by the finite element method (FEM). The nanoantenna exhibits flexibility in excitation and manipulation of the anapole mode through the strong coupling between the metal and dielectrics, consequently improving the near-field enhancement at the gap. By systematically optimizing the structural parameters, the electric field enhancement factors at wavelengths corresponding to the anapole modes (AM1 and AM2) can be increased to 518 and 1482, respectively. Moreover, the nanoantenna delivers great performance in optical sensing such as a sensitivity of 550 nm/RIU. The results provide guidance and insights into enhancing the coupling between metals and dielectrics for applications such as surface-enhanced Raman scattering and optical sensing. Select Angle robust transmitted plasmonic colors with different surroundings utilizing localized surface plasmon resonance Xufeng Gao(高旭峰), Qi Wang(王琦), Shijie Zhang(张世杰), Ruijin Hong(洪瑞金), and Dawei Zhang(张大伟) Chin. Phys. B, 2023, 32 (7): 070204.   DOI: 10.1088/1674-1056/ac921e Abstract （131）   HTML （2）    PDF （2054KB）（126）       Knowledge map    Color filters in different surroundings inherently suffer from angular sensitivity, which hinders their practical applications. Here, we present an angle-insensitive plasmonic filter that can produce different color responses to different surrounding environments. The color filters are based on a two-dimensional periodically and randomly distributed silver nanodisk array on a silica substrate. The proposed plasmonic color filters not only produce bright colors by altering the diameter of the Ag nanodisk, but also achieve continuous color palettes by changing the surrounding environment. Due to the weak coupling between the metallic nanodisks, the plasmonic color filters can enable good incident angle-insensitive properties (up to 30°). The strategy presented here could exhibit robust and promising applicability in anti-counterfeiting and imaging technologies. page Page 1 of 9 Total 161 records First page Prev page Next page Last page