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
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
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
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
Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.Th...Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.展开更多
Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noi...Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.展开更多
Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme hea...Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme head poses,partial occlusions,and abnormal lighting,remains challenging.Existing models often struggle to effectively focus on discriminative ocular features,leading to suboptimal performance.To address these limitations,this paper proposes dual-branch gaze estimation with Gaussian mixture distribution heatmaps and dynamic adaptive loss function(DMGDL),a novel dual-branch gaze estimation algorithm.By introducing Gaussian mixture distribution heatmaps centered on pupil positions as spatial attention guides,the model is enabled to prioritize ocular regions.Additionally,a dual-branch network architecture is designed to separately extract features for yaw and pitch angles,enhancing flexibility and mitigating cross-angle interference.A dynamic adaptive loss function is further formulated to address discontinuities in angle estimation,improving robustness and convergence stability.Experimental evaluations on three benchmark datasets demonstrate that DMGDL outperforms state-of-the-art methods,achiev-ing a mean angular error of 3.98°on the Max-Planck institute for informatics face gaze(MPI-IFaceGaze)dataset,10.21°on the physically unconstrained gaze estimation in the wild(Gaze360)dataset and 6.14°on the real-time eye gaze estimation in natural environments(RT-Gene)dataset,exhibiting superior generalization and robustness.展开更多
In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel functi...In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.展开更多
In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Usin...In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Using the perturbation method,we analyze the first-and second-order sideband generations in the output field from the system under the actions of a strong control field and a weak probe field.Numerical simulations show that the Kerr nonlinearity can lead to the occurrence of the asymmetric line shape in the transmission of the probe field.Comparing with traditional scheme for generating the second-order sideband,our spectral shape of the second-order sideband is amplified and becomes asymmetric,which has potential applications in precision measurement,high-sensitivity devices,and frequency conversion.展开更多
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.
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(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.
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 Central Government’s Guidance Fund for Local Science and Technology Development(2024ZY-CGZY-19)。
文摘Observing plants across time and diverse scenes is critical in uncovering plant growth patterns.Classic methods often struggle to observe or measure plants against complex backgrounds and at different growth stages.This highlights the need for a universal approach capable of providing realistic plant visualizations across time and scene.Here,we introduce PlantGaussian,an approach for generating realistic three-dimensional(3D)visualization for plants across time and scenes.It marks one of the first applications of 3D Gaussian splatting techniques in plant science,achieving high-quality visualization across species and growth stages.By integrating the Segment Anything Model(SAM)and tracking algorithms,PlantGaussian overcomes the limitations of classic Gaussian reconstruction techniques in complex planting environments.A new mesh partitioning technique is employed to convert Gaussian rendering results into measurable plant meshes,offering a methodology for accurate 3D plant morphology phenotyping.To support this approach,PlantGaussian dataset is developed,which includes images of four crop species captured under multiple conditions and growth stages.Using only plant image sequences as input,it computes high-fidelity plant visualization models and 3D meshes for 3D plant morphological phenotyping.Visualization results indicate that most plant models achieve a Peak Signal-to-Noise Ratio(PSNR)exceeding 25,outperforming all models including the original 3D Gaussian Splatting and enhanced NeRF.The mesh results indicate an average relative error of 4%between the calculated values and the true measurements.As a generic 3D digital plant model,PlantGaussian will support expansion of plant phenotype databases,ecological research,and remote expert consultations.
基金supported by the ERC Advanced Grant QU-BOSS(QUantum advantage via nonlinear BOSon Sampling,Grant No.884676)by ICSC-Centro Nazionale di Ricerca in High Performance Computing,Big Data,and Quantum Computing,funded by the European Union-NextGenerationEU.D.S.acknowledges Thales Alenia Space Italia for supporting the PhD fellowship.N.S.acknowledges funding from Sapienza Universitàdi Roma via Bando Ricerca 2020:Progetti di Ricerca Piccoli,Project No.RP120172B8A36B37.
文摘Quantum photonic processors are emerging as promising platforms to prove preliminary evidence of quantum computational advantage toward the realization of universal quantum computers.In the context of nonuniversal noisy intermediate quantum devices,photonic-based sampling machines solving the Gaussian boson sampling(GBS)problem currently play a central role in the experimental demonstration of quantum computational advantage.A relevant issue is the validation of the sampling process in the presence of experimental noise,such as photon losses,which could undermine the hardness of simulating the experiment.We test the capability of a validation protocol that exploits the connection between GBS and graph perfect match counting to perform such an assessment in a noisy scenario.In particular,we use as a test bench the recently developed machine Borealis,a large-scale sampling machine that has been made available online for external users,and address its operation in the presence of noise.The employed approach to validation is also shown to provide connections with the open question on the effective advantage of using noisy GBS devices for graph similarity and isomorphism problems and thus provides an effective method for certification of quantum hardware.
基金supported by the Key Project of the NationalLanguage Commission(No.ZDI145-110)the AcademicResearch Projects of Beijing Union University(No.ZK20202514)+1 种基金the Key Laboratory Project(No.YYZN-2024-6)the Project for the Construction and Support of High-Level Innovative Teams in Beijing Municipal Institutions(No.BPHR20220121).
文摘Gaze estimation,a crucial non-verbal communication cue,has achieved remarkable progress through convolutional neural networks.However,accurate gaze prediction in uncon-strained environments,particularly in extreme head poses,partial occlusions,and abnormal lighting,remains challenging.Existing models often struggle to effectively focus on discriminative ocular features,leading to suboptimal performance.To address these limitations,this paper proposes dual-branch gaze estimation with Gaussian mixture distribution heatmaps and dynamic adaptive loss function(DMGDL),a novel dual-branch gaze estimation algorithm.By introducing Gaussian mixture distribution heatmaps centered on pupil positions as spatial attention guides,the model is enabled to prioritize ocular regions.Additionally,a dual-branch network architecture is designed to separately extract features for yaw and pitch angles,enhancing flexibility and mitigating cross-angle interference.A dynamic adaptive loss function is further formulated to address discontinuities in angle estimation,improving robustness and convergence stability.Experimental evaluations on three benchmark datasets demonstrate that DMGDL outperforms state-of-the-art methods,achiev-ing a mean angular error of 3.98°on the Max-Planck institute for informatics face gaze(MPI-IFaceGaze)dataset,10.21°on the physically unconstrained gaze estimation in the wild(Gaze360)dataset and 6.14°on the real-time eye gaze estimation in natural environments(RT-Gene)dataset,exhibiting superior generalization and robustness.
基金supported by the Basic Science Center Program of the National Natural Science Foundation of China(62388101)the National Natural Science Foundation of China(61873275).
文摘In this paper,the newly-derived maximum correntropy Kalman filter(MCKF)is re-derived from the M-estimation perspective,where the MCKF can be viewed as a special case of the M-estimations and the Gaussian kernel function is a special case of many robust cost functions.Based on the derivation process,a unified form for the robust Gaussian filters(RGF)based on M-estimation is proposed to suppress the outliers and non-Gaussian noise in the measurement.The RGF provides a unified form for one Gaussian filter with different cost functions and a unified form for one robust filter with different approximating methods for the involved Gaussian integrals.Simulation results show that RGF with different weighting functions and different Gaussian integral approximation methods has robust antijamming performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.12174344 and 12175199)Foundation of Department of Science and Technology of Zhejiang Province(Grant No.2022R52047)。
文摘In this paper,we investigate the phenomena of electromagnetically induced transparency and the generation of second-order sideband in a Laguerre–Gaussian cavity optorotational system with a Kerr nonlinear medium.Using the perturbation method,we analyze the first-and second-order sideband generations in the output field from the system under the actions of a strong control field and a weak probe field.Numerical simulations show that the Kerr nonlinearity can lead to the occurrence of the asymmetric line shape in the transmission of the probe field.Comparing with traditional scheme for generating the second-order sideband,our spectral shape of the second-order sideband is amplified and becomes asymmetric,which has potential applications in precision measurement,high-sensitivity devices,and frequency conversion.
