Many complex systems are frequently subject to the influence of uncertain disturbances,which can exert a profound effect on the critical transitions(CTs),potentially resulting in catastrophic consequences.Consequently...Many complex systems are frequently subject to the influence of uncertain disturbances,which can exert a profound effect on the critical transitions(CTs),potentially resulting in catastrophic consequences.Consequently,it is of uttermost importance to provide warnings for noise-induced CTs in various applications.Although capturing certain generic symptoms of transition behaviors from observational and simulated data poses a challenging problem,this work attempts to extract information regarding CTs from simulated data of a Gaussian white noise-induced tri-stable system.Using the extended dynamic mode decomposition(EDMD)algorithm,we initially obtain finite-dimensional approximations of both the stochastic Koopman operator and the generator.Subsequently,the drift parameters and the noise intensity within the system are identified from the simulated data.Utilizing the identified system,the parameter-dependent basin of the unsafe regime(PDBUR)is quantified,enabling data-driven early warning of Gaussian white noise-induced CTs.Finally,an error analysis is carried out to verify the effectiveness of the data-driven results.Our findings may serve as a paradigm for understanding and predicting noise-induced CTs in complex systems based on data.展开更多
The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-...The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-in-cell simulations.It is shown that twisted plasma currents and hence magneticflux ropes can be effectively generated as long as the laser frequency difference matches the electron plasma frequency.More importantly,subsequent reconnection of magneticflux ropes can occur.Typical signatures of magnetic reconnection,such as magnetic island formation and plasma heating,are identified in the reconnection of magneticflux ropes.Notably,it is found that a strong axial magneticfield can be generated on the axis,owing to the azimuthal current induced during the reconnection of the ropes.This indicates that in the reconnection of magneticflux ropes,the energy can be transferred not only from the magneticfield to the plasma but also from the plasma current back to the magneticfield.This work opens a new avenue to the study of magneticflux ropes,which helps in understanding magnetic topology changes,and resultant magnetic energy dissipation,plasma heating,and particle acceleration found in solarflares,and magnetic confinement fusion devices.展开更多
Topological band theory has been studied for free fermions for decades,and one of the most profound physical results is the bulk-boundary correspondence.Recently a focus in topological physics is extending topological...Topological band theory has been studied for free fermions for decades,and one of the most profound physical results is the bulk-boundary correspondence.Recently a focus in topological physics is extending topological classification to mixed states.Here,we focus on Gaussian mixed states for which the modular Hamiltonians of the density matrix are quadratic free fermion models with U(1)symmetry and can be classified by topological invariants.The bulk-boundary correspondence is then manifested as stable gapless modes of the modular Hamiltonian and degenerate spectrum of the density matrix.In this article,we show that these gapless modes can be detected by the full counting statistics,mathematically described by a function introduced as F(θ).A divergent derivative atθ=πcan be used to probe the gapless modes in the modular Hamiltonian.Based on this,a topological indicator,whose quantization to unity senses topologically nontrivial mixed states,is introduced.We present the physical intuition of these results and also demonstrate these results with concrete models in both one-and two-dimensions.Our results pave the way for revealing the physical significance of topology in mixed states.展开更多
针对现有SLAM算法在渲染真实感、内存占用和复杂场景适应性方面的不足,提出了一种基于3D Gaussians Splatting的密集SLAM算法——TIGO-SLAM(tensor illumination and Gaussian optimization for indoor SLAM)。该算法集成了基于神经网...针对现有SLAM算法在渲染真实感、内存占用和复杂场景适应性方面的不足,提出了一种基于3D Gaussians Splatting的密集SLAM算法——TIGO-SLAM(tensor illumination and Gaussian optimization for indoor SLAM)。该算法集成了基于神经网络的张量光照模型、改进的高斯遮罩算法以及网格化神经场的几何和颜色属性表示,具体创新包括:a)基于神经网络的张量光照模型,增强镜面反射与漫反射效果,从而提升了渲染真实感;b)通过冗余高斯剔除机制改进高斯遮罩算法,有效降低了内存消耗并提高了实时性;c)结合网格化神经场的几何与颜色属性表示,采用优化的码本存储方式,显著提高了渲染性能和场景重建精度。实验结果表明,TIGO-SLAM在室内场景渲染、内存优化和复杂场景适应性方面均有显著提升,特别是在动态室内环境中的渲染和重建效果表现突出,为SLAM技术在资源受限设备上的应用提供了新的可能。展开更多
A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density （GSPHD） filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of ...A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density （GSPHD） filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaussian sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival probability, and detection probability are all Gaussian sums. The analysis also shows that the existing Gaussian mixture probability hypothesis density （GMPHD） filter, which is unsuitable for handling the non-Gaussian noise cases, is no more than a special case of the proposed algorithm, which fills the shortage of incapability of treating non-Gaussian noise. The multi-target tracking simulation results verify the effectiveness of the proposed GSPHD.展开更多
We apply methods of algebraic integral geometry to prove a special case of the Gaussian kinematic formula of Adler-Taylor.The idea,suggested already by Adler and Taylor,is to view the GKF as the limit of spherical kin...We apply methods of algebraic integral geometry to prove a special case of the Gaussian kinematic formula of Adler-Taylor.The idea,suggested already by Adler and Taylor,is to view the GKF as the limit of spherical kinematic formulas for spheres of large dimension N and curvature1/N.展开更多
A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a ...A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a universal testing machine to gather data on stress, strain, and Young's modulus. This data was then analyzed through both statistical approaches to evaluate their ability to model important mechanical characteristics, including tensile strength, strain at break, and Young's modulus. The study identifies the strengths and weaknesses of each statistical method when it is applied to natural fibers, emphasizing their suitability for modeling different mechanical properties. The results of this analysis provide important insights that can guide the selection of the most appropriate statistical method, depending on the type of mechanical property being studied and the specific characteristics of the data. This research makes significant contributions to advancing the understanding of natural fiber mechanics and improving the methods used for their characterization.展开更多
Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrat...Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrating Gaussian beam tracing with seabed scattering physics.The model synthesizes time-domain reverberation signals by superimposing scattering signals received across multiple propagation paths.It accurately resolves scattering signals along distinct paths and enables simulation of reverberation under diverse shallow-water environments by adjusting the marine parameters.Furthermore,we model the seabed reverberation signals in the time domain and the space domain for a cylindrical transceiver array,and provide a detailed statistical characterization of the simulated seabed reverberation signals.Finally,shallow-water seabed reverberation experiments were conducted with a cylindrical transceiver array.Comparisons between shallow-water seabed reverberation measurements and simulation estimates at various sites and transceiver depths demonstrate that the proposed seabed reverberation model can efficiently simulate shallow-water seabed reverberation.展开更多
The elastic properties of membranes are typically characterized by a few phenomenological parameters,including bending and Gaussian curvature moduli measuring the membrane rigidity against its deformation and topologi...The elastic properties of membranes are typically characterized by a few phenomenological parameters,including bending and Gaussian curvature moduli measuring the membrane rigidity against its deformation and topological change,as well as spontaneous curvature arising from the asymmetry between the two leaflets in the lipid bilayers.Though tether-based and fluctuationbased experiments are commonly utilized to measure the bending modulus,measuring the Gaussian curvature modulus and the spontaneous curvature of the membrane is considered to be much more difficult.In this paper,we study the buckling process of a circular membrane with nonzero spontaneous curvature under compressive stresses.It is found that when the stress exceeds a critical value,the circular membrane will transform from a spherical cap to a buckled shape,with its buckling degree enhanced with the increase of stress until its base is constricted to almost zero.As the stress-strain relationship of the buckled membrane strongly depends on the Gaussian curvature modulus and the spontaneous curvature,we therefore propose a method to determine the Gaussian curvature modulus and the spontaneous curvature simultaneously by measuring its stress-strain relationship during a buckling process.展开更多
The packaging quality of coaxial laser diodes(CLDs)plays a pivotal role in determining their optical performance and long-term reliability.As the core packaging process,high-precision laser welding requires precise co...The packaging quality of coaxial laser diodes(CLDs)plays a pivotal role in determining their optical performance and long-term reliability.As the core packaging process,high-precision laser welding requires precise control of process parameters to suppress optical power loss.However,the complex nonlinear relationship between welding parameters and optical power loss renders traditional trial-and-error methods inefficient and imprecise.To address this challenge,a physics-informed(PI)and data-driven collaboration approach for welding parameter optimization is proposed.First,thermal-fluid-solid coupling finite element method(FEM)was employed to quantify the sensitivity of welding parameters to physical characteristics,including residual stress.This analysis facilitated the identification of critical factors contributing to optical power loss.Subsequently,a Gaussian process regression(GPR)model incorporating finite element simulation prior knowledge was constructed based on the selected features.By introducing physics-informed kernel(PIK)functions,stress distribution patterns were embedded into the prediction model,achieving high-precision optical power loss prediction.Finally,a Bayesian optimization(BO)algorithm with an adaptive sampling strategy was implemented for efficient parameter space exploration.Experimental results demonstrate that the proposedmethod effectively establishes explicit physical correlations between welding parameters and optical power loss.The optimized welding parameters reduced optical power loss by 34.1%,providing theoretical guidance and technical support for reliable CLD packaging.展开更多
Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM m...Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM method may present fragmented patches and encounter problems caused by excessive smoothing of velocity peaks,leading to difficulty in short-wavelength deformation detection and improper geophysical interpretation.Therefore,we propose a novel GNSS imaging method based on Gaussian process regression with velocity uncertainty considered(GPR-VU).Gaussian processing regression is introduced to describe the spatial relationship between neighboring site pairs as a priori weights and then reweight velocities by known station uncertainties,converting the discrete velocity field to a continuous one.The GPR-VU method is applied to reconstruct VLM images in the southwestern United States and the eastern Qinghai-Xizang Plateau,China,using the GNSS position time series in vertical direction.Compared to the traditional GIM method,the root-mean-square(RMS)and overall accuracy of the confusion matrix of the GPR-VU method increase by 5.0%and 14.0%from the 1°×1°checkerboard test in the southwestern United States.Similarly,the RMS and overall accuracy increase by 33.7%and 15.8%from the 6°×6°checkerboard test in the eastern Qinghai-Xizang Plateau.These checkerboard tests validate the capability to effectively capture the spatiotemporal variations characteristics of VLM and show that this algorithm outperforms the sparsely distributed network in the Qinghai-Xizang Plateau.The images from the GPR-VU method using real data in both regions show significant subsidence around Lassen Volcanic in northern California within a 30 km radius,slight uplift in the northern Sichuan Basin,and subsidence in its central and southern sections.These results further qualitatively illustrate consistency with previous findings.The GPR-VU method outperforms in diminishing the effect by fragmented patches,excessive smoothing of velocity peaks,and detecting potential short-wavelength deformations.展开更多
Fluid-conveying pipes generally face combined excitations caused by periodic loads and random noises.Gaussian white noise is a common random noise excitation.This study investigates the random vibration response of a ...Fluid-conveying pipes generally face combined excitations caused by periodic loads and random noises.Gaussian white noise is a common random noise excitation.This study investigates the random vibration response of a simply-supported pipe conveying fluid under combined harmonic and Gaussian white noise excitations.According to the generalized Hamilton’s principle,the dynamic model of the pipe conveying fluid under combined harmonic and Gaussian white noise excitations is established.Subsequently,the averaged stochastic differential equations and Fokker–Planck–Kolmogorov(FPK)equations of the pipe conveying fluid subjected to combined excitations are acquired by the modified stochastic averaging method.The effectiveness of the analysis results is verified through the Monte Carlo method.The effects of fluid speed,noise intensity,amplitude of harmonic excitation,and damping factor on the probability density functions of amplitude,displacement,as well as velocity are discussed in detail.The results show that with an increase in fluid speed or noise intensity,the possible greatest amplitude for the fluid-conveying pipe increases,and the possible greatest displacement and velocity also increase.With an increase in the amplitude of harmonic excitation or damping factor,the possible greatest amplitude for the pipe decreases,and the possible greatest displacement and velocity also decrease.展开更多
Quantum phase estimation based on Gaussian states plays a crucial role in many application fields.In this paper,we study the precision bound for the scheme using two-mode squeezed Gaussian states.The quantum Fisher in...Quantum phase estimation based on Gaussian states plays a crucial role in many application fields.In this paper,we study the precision bound for the scheme using two-mode squeezed Gaussian states.The quantum Fisher information is calculated and its maximization is used to determine the optimal parameters.We find that two single-mode squeezed vacuum states are the optimal Gaussian inputs for a fixed two-mode squeezing process.The corresponding precision bound is sub-Heisenberg-limited and scales as N^(-1)/2.For practical purposes,we consider the effects originating from photon loss.The precision bound can still outperform the shot-noise limit when the lossy rate is below 0.4.Our work may demonstrate a significant and promising step towards practical quantum metrology.展开更多
基金Project supported by the National Natural Science Foundation of China(No.12402033)the National Natural Science Foundation for Distinguished Young Scholars of China(No.52225211)。
文摘Many complex systems are frequently subject to the influence of uncertain disturbances,which can exert a profound effect on the critical transitions(CTs),potentially resulting in catastrophic consequences.Consequently,it is of uttermost importance to provide warnings for noise-induced CTs in various applications.Although capturing certain generic symptoms of transition behaviors from observational and simulated data poses a challenging problem,this work attempts to extract information regarding CTs from simulated data of a Gaussian white noise-induced tri-stable system.Using the extended dynamic mode decomposition(EDMD)algorithm,we initially obtain finite-dimensional approximations of both the stochastic Koopman operator and the generator.Subsequently,the drift parameters and the noise intensity within the system are identified from the simulated data.Utilizing the identified system,the parameter-dependent basin of the unsafe regime(PDBUR)is quantified,enabling data-driven early warning of Gaussian white noise-induced CTs.Finally,an error analysis is carried out to verify the effectiveness of the data-driven results.Our findings may serve as a paradigm for understanding and predicting noise-induced CTs in complex systems based on data.
基金supported by the National Natural Science Foundation of China(Grant Nos.12375236 and 12135009)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant Nos.XDA25050100 and XDA25010100).
文摘The generation and reconnection of magneticflux ropes in a plasma irradiated by two Laguerre–Gaussian laser pulses with different frequen-cies and opposite topological charges are investigated numerically by particle-in-cell simulations.It is shown that twisted plasma currents and hence magneticflux ropes can be effectively generated as long as the laser frequency difference matches the electron plasma frequency.More importantly,subsequent reconnection of magneticflux ropes can occur.Typical signatures of magnetic reconnection,such as magnetic island formation and plasma heating,are identified in the reconnection of magneticflux ropes.Notably,it is found that a strong axial magneticfield can be generated on the axis,owing to the azimuthal current induced during the reconnection of the ropes.This indicates that in the reconnection of magneticflux ropes,the energy can be transferred not only from the magneticfield to the plasma but also from the plasma current back to the magneticfield.This work opens a new avenue to the study of magneticflux ropes,which helps in understanding magnetic topology changes,and resultant magnetic energy dissipation,plasma heating,and particle acceleration found in solarflares,and magnetic confinement fusion devices.
基金supported by the National Key R&D Program of China(Grant No.2023YFA1406702)the Innovation Program for Quantum Science and Technology 2021ZD0302005+1 种基金the XPLORER Prizepartly supported by the Start-up Research Fund of Southeast University(RF1028624190)。
文摘Topological band theory has been studied for free fermions for decades,and one of the most profound physical results is the bulk-boundary correspondence.Recently a focus in topological physics is extending topological classification to mixed states.Here,we focus on Gaussian mixed states for which the modular Hamiltonians of the density matrix are quadratic free fermion models with U(1)symmetry and can be classified by topological invariants.The bulk-boundary correspondence is then manifested as stable gapless modes of the modular Hamiltonian and degenerate spectrum of the density matrix.In this article,we show that these gapless modes can be detected by the full counting statistics,mathematically described by a function introduced as F(θ).A divergent derivative atθ=πcan be used to probe the gapless modes in the modular Hamiltonian.Based on this,a topological indicator,whose quantization to unity senses topologically nontrivial mixed states,is introduced.We present the physical intuition of these results and also demonstrate these results with concrete models in both one-and two-dimensions.Our results pave the way for revealing the physical significance of topology in mixed states.
文摘针对现有SLAM算法在渲染真实感、内存占用和复杂场景适应性方面的不足,提出了一种基于3D Gaussians Splatting的密集SLAM算法——TIGO-SLAM(tensor illumination and Gaussian optimization for indoor SLAM)。该算法集成了基于神经网络的张量光照模型、改进的高斯遮罩算法以及网格化神经场的几何和颜色属性表示,具体创新包括:a)基于神经网络的张量光照模型,增强镜面反射与漫反射效果,从而提升了渲染真实感;b)通过冗余高斯剔除机制改进高斯遮罩算法,有效降低了内存消耗并提高了实时性;c)结合网格化神经场的几何与颜色属性表示,采用优化的码本存储方式,显著提高了渲染性能和场景重建精度。实验结果表明,TIGO-SLAM在室内场景渲染、内存优化和复杂场景适应性方面均有显著提升,特别是在动态室内环境中的渲染和重建效果表现突出,为SLAM技术在资源受限设备上的应用提供了新的可能。
基金National Natural Science Foundation of China (60572023)
文摘A new multi-target filtering algorithm, termed as the Gaussian sum probability hypothesis density （GSPHD） filter, is proposed for nonlinear non-Gaussian tracking models. Provided that the initial prior intensity of the states is Gaussian or can be identified as a Gaussian sum, the analytical results of the algorithm show that the posterior intensity at any subsequent time step remains a Gaussian sum under the assumption that the state noise, the measurement noise, target spawn intensity, new target birth intensity, target survival probability, and detection probability are all Gaussian sums. The analysis also shows that the existing Gaussian mixture probability hypothesis density （GMPHD） filter, which is unsuitable for handling the non-Gaussian noise cases, is no more than a special case of the proposed algorithm, which fills the shortage of incapability of treating non-Gaussian noise. The multi-target tracking simulation results verify the effectiveness of the proposed GSPHD.
文摘We apply methods of algebraic integral geometry to prove a special case of the Gaussian kinematic formula of Adler-Taylor.The idea,suggested already by Adler and Taylor,is to view the GKF as the limit of spherical kinematic formulas for spheres of large dimension N and curvature1/N.
文摘A detailed comparative examination of the Weibull and Gaussian statistical methods is offered to analyze the mechanical properties of natural date palm fibers. Tensile tests were conducted on 35 fiber samples using a universal testing machine to gather data on stress, strain, and Young's modulus. This data was then analyzed through both statistical approaches to evaluate their ability to model important mechanical characteristics, including tensile strength, strain at break, and Young's modulus. The study identifies the strengths and weaknesses of each statistical method when it is applied to natural fibers, emphasizing their suitability for modeling different mechanical properties. The results of this analysis provide important insights that can guide the selection of the most appropriate statistical method, depending on the type of mechanical property being studied and the specific characteristics of the data. This research makes significant contributions to advancing the understanding of natural fiber mechanics and improving the methods used for their characterization.
基金The Youth Project of National Natural Science Foundation of China under contract No.12304507the Natural Science Foundation of Guangdong Province,China under contract No.2024A1515011512+2 种基金the Stable Supporting Fund of Acoustic Science and Technology Laboratory under contract No.JCKYS2025SSJS010the Fundamental Research Funds for the Central Universities under contract No.20720240108the Special Project for Marine Economy Development of Guangdong Province,China under contract No.GDNRC2023-47.
文摘Shallow-water seabed reverberation presents a critical disturbance in acoustic propagation,affecting the target detection performance of monostatic sonar.This paper proposes a novel seabed reverberation model integrating Gaussian beam tracing with seabed scattering physics.The model synthesizes time-domain reverberation signals by superimposing scattering signals received across multiple propagation paths.It accurately resolves scattering signals along distinct paths and enables simulation of reverberation under diverse shallow-water environments by adjusting the marine parameters.Furthermore,we model the seabed reverberation signals in the time domain and the space domain for a cylindrical transceiver array,and provide a detailed statistical characterization of the simulated seabed reverberation signals.Finally,shallow-water seabed reverberation experiments were conducted with a cylindrical transceiver array.Comparisons between shallow-water seabed reverberation measurements and simulation estimates at various sites and transceiver depths demonstrate that the proposed seabed reverberation model can efficiently simulate shallow-water seabed reverberation.
基金the financial support from the National Natural Science Foundation of China under Grant Nos.12174323 and 12474199Fundamental Research Funds for Central Universities of China under Grant No.20720240144(RM)111 project B16029。
文摘The elastic properties of membranes are typically characterized by a few phenomenological parameters,including bending and Gaussian curvature moduli measuring the membrane rigidity against its deformation and topological change,as well as spontaneous curvature arising from the asymmetry between the two leaflets in the lipid bilayers.Though tether-based and fluctuationbased experiments are commonly utilized to measure the bending modulus,measuring the Gaussian curvature modulus and the spontaneous curvature of the membrane is considered to be much more difficult.In this paper,we study the buckling process of a circular membrane with nonzero spontaneous curvature under compressive stresses.It is found that when the stress exceeds a critical value,the circular membrane will transform from a spherical cap to a buckled shape,with its buckling degree enhanced with the increase of stress until its base is constricted to almost zero.As the stress-strain relationship of the buckled membrane strongly depends on the Gaussian curvature modulus and the spontaneous curvature,we therefore propose a method to determine the Gaussian curvature modulus and the spontaneous curvature simultaneously by measuring its stress-strain relationship during a buckling process.
基金funded by the National Key R&D Program of China,Grant No.2024YFF0504904.
文摘The packaging quality of coaxial laser diodes(CLDs)plays a pivotal role in determining their optical performance and long-term reliability.As the core packaging process,high-precision laser welding requires precise control of process parameters to suppress optical power loss.However,the complex nonlinear relationship between welding parameters and optical power loss renders traditional trial-and-error methods inefficient and imprecise.To address this challenge,a physics-informed(PI)and data-driven collaboration approach for welding parameter optimization is proposed.First,thermal-fluid-solid coupling finite element method(FEM)was employed to quantify the sensitivity of welding parameters to physical characteristics,including residual stress.This analysis facilitated the identification of critical factors contributing to optical power loss.Subsequently,a Gaussian process regression(GPR)model incorporating finite element simulation prior knowledge was constructed based on the selected features.By introducing physics-informed kernel(PIK)functions,stress distribution patterns were embedded into the prediction model,achieving high-precision optical power loss prediction.Finally,a Bayesian optimization(BO)algorithm with an adaptive sampling strategy was implemented for efficient parameter space exploration.Experimental results demonstrate that the proposedmethod effectively establishes explicit physical correlations between welding parameters and optical power loss.The optimized welding parameters reduced optical power loss by 34.1%,providing theoretical guidance and technical support for reliable CLD packaging.
基金supported by the National Natural Science Foundation of China(Grant No.42274035)the Major Science and Technology Program for Hubei Province(No.2022AAA002)the Hunan Provincial Land Surveying and Mapping Project(HNGTCH-2023-05)。
文摘Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM method may present fragmented patches and encounter problems caused by excessive smoothing of velocity peaks,leading to difficulty in short-wavelength deformation detection and improper geophysical interpretation.Therefore,we propose a novel GNSS imaging method based on Gaussian process regression with velocity uncertainty considered(GPR-VU).Gaussian processing regression is introduced to describe the spatial relationship between neighboring site pairs as a priori weights and then reweight velocities by known station uncertainties,converting the discrete velocity field to a continuous one.The GPR-VU method is applied to reconstruct VLM images in the southwestern United States and the eastern Qinghai-Xizang Plateau,China,using the GNSS position time series in vertical direction.Compared to the traditional GIM method,the root-mean-square(RMS)and overall accuracy of the confusion matrix of the GPR-VU method increase by 5.0%and 14.0%from the 1°×1°checkerboard test in the southwestern United States.Similarly,the RMS and overall accuracy increase by 33.7%and 15.8%from the 6°×6°checkerboard test in the eastern Qinghai-Xizang Plateau.These checkerboard tests validate the capability to effectively capture the spatiotemporal variations characteristics of VLM and show that this algorithm outperforms the sparsely distributed network in the Qinghai-Xizang Plateau.The images from the GPR-VU method using real data in both regions show significant subsidence around Lassen Volcanic in northern California within a 30 km radius,slight uplift in the northern Sichuan Basin,and subsidence in its central and southern sections.These results further qualitatively illustrate consistency with previous findings.The GPR-VU method outperforms in diminishing the effect by fragmented patches,excessive smoothing of velocity peaks,and detecting potential short-wavelength deformations.
基金supported by the National Natural Science Foundation of China(Nos.12272211 and 12072181).
文摘Fluid-conveying pipes generally face combined excitations caused by periodic loads and random noises.Gaussian white noise is a common random noise excitation.This study investigates the random vibration response of a simply-supported pipe conveying fluid under combined harmonic and Gaussian white noise excitations.According to the generalized Hamilton’s principle,the dynamic model of the pipe conveying fluid under combined harmonic and Gaussian white noise excitations is established.Subsequently,the averaged stochastic differential equations and Fokker–Planck–Kolmogorov(FPK)equations of the pipe conveying fluid subjected to combined excitations are acquired by the modified stochastic averaging method.The effectiveness of the analysis results is verified through the Monte Carlo method.The effects of fluid speed,noise intensity,amplitude of harmonic excitation,and damping factor on the probability density functions of amplitude,displacement,as well as velocity are discussed in detail.The results show that with an increase in fluid speed or noise intensity,the possible greatest amplitude for the fluid-conveying pipe increases,and the possible greatest displacement and velocity also increase.With an increase in the amplitude of harmonic excitation or damping factor,the possible greatest amplitude for the pipe decreases,and the possible greatest displacement and velocity also decrease.
基金Project supported by the National Natural Science Foundation of China(Grant No.12104193)the Program of Zhongwu Young Innovative Talents of Jiangsu University of Technology(Grant No.20230013)。
文摘Quantum phase estimation based on Gaussian states plays a crucial role in many application fields.In this paper,we study the precision bound for the scheme using two-mode squeezed Gaussian states.The quantum Fisher information is calculated and its maximization is used to determine the optimal parameters.We find that two single-mode squeezed vacuum states are the optimal Gaussian inputs for a fixed two-mode squeezing process.The corresponding precision bound is sub-Heisenberg-limited and scales as N^(-1)/2.For practical purposes,we consider the effects originating from photon loss.The precision bound can still outperform the shot-noise limit when the lossy rate is below 0.4.Our work may demonstrate a significant and promising step towards practical quantum metrology.
