The nonlinear Schrodinger equation(NLSE) is a key tool for modeling wave propagation in nonlinear and dispersive media. This study focuses on the complex cubic NLSE with δ-potential,explored through the Brownian proc...The nonlinear Schrodinger equation(NLSE) is a key tool for modeling wave propagation in nonlinear and dispersive media. This study focuses on the complex cubic NLSE with δ-potential,explored through the Brownian process. The investigation begins with the derivation of stochastic solitary wave solutions using the modified exp(-Ψ(ξ)) expansion method. To illustrate the noise effects, 3D and 2D visualizations are displayed for different non-negative values of noise parameter under suitable parameter values. Additionally, qualitative analysis of both perturbed and unperturbed dynamical systems is conducted using bifurcation and chaos theory. In bifurcation analysis, we analyze the detailed parameter analysis near fixed points of the unperturbed system. An external periodic force is applied to perturb the system, leading to an investigation of its chaotic behavior. Chaos detection tools are employed to predict the behavior of the perturbed dynamical system, with results validated through visual representations.Multistability analysis is conducted under varying initial conditions to identify multiple stable states in the perturbed dynamical system, contributing to chaotic behavior. Also, sensitivity analysis of the Hamiltonian system is performed for different initial conditions. The novelty of this work lies in the significance of the obtained results, which have not been previously explored for the considered equation. These findings offer noteworthy insights into the behavior of the complex cubic NLSE with δ-potential and its applications in fields such as nonlinear optics, quantum mechanics and Bose–Einstein condensates.展开更多
Dear Editor,This letter addresses the synchronization problem of a class of delayed stochastic complex dynamical networks consisting of multiple drive and response nodes.The aim is to achieve mean square exponential s...Dear Editor,This letter addresses the synchronization problem of a class of delayed stochastic complex dynamical networks consisting of multiple drive and response nodes.The aim is to achieve mean square exponential synchronization for the drive-response nodes despite the simultaneous presence of time delays and stochastic noises in node dynamics.展开更多
This paper concerns two-player zero-sum stochastic differential games with nonanticipative strategies against closed-loop controls in the case where the coefficients of mean-field stochastic differential equations and...This paper concerns two-player zero-sum stochastic differential games with nonanticipative strategies against closed-loop controls in the case where the coefficients of mean-field stochastic differential equations and cost functional depend on the joint distribution of the state and the control.In our game,both the(lower and upper)value functions and the(lower and upper)second-order Bellman–Isaacs equations are defined on the Wasserstein space P_(2)(R^(n))which is an infinite dimensional space.The dynamic programming principle for the value functions is proved.If the(upper and lower)value functions are smooth enough,we show that they are the classical solutions to the second-order Bellman–Isaacs equations.On the other hand,the classical solutions to the(upper and lower)Bellman–Isaacs equations are unique and coincide with the(upper and lower)value functions.As an illustrative application,the linear quadratic case is considered.Under the Isaacs condition,the explicit expressions of optimal closed-loop controls for both players are given.Finally,we introduce the intrinsic notion of viscosity solution of our second-order Bellman–Isaacs equations,and characterize the(upper and lower)value functions as their viscosity solutions.展开更多
We present a general numerical simulation method to solve non-Markovian dynamics of an open quantum system influenced by quantum Brownian motion.Based on the determined memory kernel function,this method enables the r...We present a general numerical simulation method to solve non-Markovian dynamics of an open quantum system influenced by quantum Brownian motion.Based on the determined memory kernel function,this method enables the resolution of non-Markovian dynamics for a wide range of system Hamiltonians and spectral densities.The system dynamics are described by exact integro-differential operator equations without any common approximations and they are simulated in this work by definite-number equations with stochastic initial conditions.This approach ensures the applicability of mature numerical methods and maintains computational complexity that remains largely invariant,even when dealing with more complex models.The high accuracy of our simulation is evident from a comparison with the results obtained from corresponding exact master equations,underscoring the reliability and precision of our method.展开更多
The quantum phase transition between Z_(2) plaquette valence bound solid(PVBS) and superfluid(SF) phases on the planar pyrochlore lattice(square ice) is under debate. To gain further insight, here, we focus on the dyn...The quantum phase transition between Z_(2) plaquette valence bound solid(PVBS) and superfluid(SF) phases on the planar pyrochlore lattice(square ice) is under debate. To gain further insight, here, we focus on the dynamical features of the hard-core Bose–Hubbard model on this lattice and study the excitation spectra by combining stochastic analytic continuation and quantum Monte Carlo simulation. In both PVBS and SF phases,a flat band with bow-tie structure is observed and can be explained by certain symmetries. At the transition point,the spectra turn to be continuous and gapless. A(2+1)-dimensional Abelian–Higgs model with mixed 't Hooft anomaly is proposed to describe the transition, where the anomaly matching predicts that the deconfinement can exist on the domain walls. From the snapshot of the spin configuration in real space, we found the existence of the domain wall. We also found that the spectrum along a specific path in momentum space from PVBS phase to the transition point can be well described by an XXZ spin chain, and the critical theory of XXZ spin chain matches the anomaly. The two-spinon continuum along this specific path implies additional domain walls(point defect) can emerge in the domain walls(line defect) and take the role of deconfinement at the transition point.展开更多
The modeling of turbulence,especially the high-speed compressible turbulence encountered in aerospace engineering,has always being a significant challenge in terms of balancing efficiency and accuracy.Most traditional...The modeling of turbulence,especially the high-speed compressible turbulence encountered in aerospace engineering,has always being a significant challenge in terms of balancing efficiency and accuracy.Most traditional models typically show limitations in universality,accuracy,and reliance on past experience.The stochastic multi-scale models show great potential in addressing these issues by representing turbulence across all characteristic scales in a reduced-dimensional space,maintaining sufficient accuracy while reducing computational cost.This review systematically summarizes advances in methods related to a widely used and refined stochastic multi-scale model,the One-Dimensional Turbulence(ODT).The advancements in formulations are emphasized for stand-alone incompressible ODT models,stand-alone compressible ODT models,and coupling methods.Some diagrams are also provided to facilitate more readers to understand the ODT methods.Subsequently,the significant developments and applications of stand-alone ODT models and coupling methods are introduced and critically evaluated.Despite the extensively recognized effectiveness of ODT models in low-speed turbulent flows,it is crucial to emphasize that there is still a research gap in the field of ODT coupling methods that are capable of accurately and efficiently simulating complex,three-dimensional,high-speed compressible turbulent flows up to now.Based on an analysis of the advantages and limitations of existing ODT methods,the recent advancement in the conservative compressible ODT model is considered to have provided a promising approach to tackle the modeling challenges of high-speed compressible turbulence.Therefore,this review outlines several recommended new research subjects and challenging issues to inspire further research in simulating complex,three-dimensional,high-speed compressible turbulent flows using ODT models.展开更多
We present a large deviation theory that characterizes the exponential estimate for rare events in stochastic dynamical systems in the limit of weak noise.We aim to consider a next-to-leading-order approximation for m...We present a large deviation theory that characterizes the exponential estimate for rare events in stochastic dynamical systems in the limit of weak noise.We aim to consider a next-to-leading-order approximation for more accurate calculation of the mean exit time by computing large deviation prefactors with the aid of machine learning.More specifically,we design a neural network framework to compute quasipotential,most probable paths and prefactors based on the orthogonal decomposition of a vector field.We corroborate the higher effectiveness and accuracy of our algorithm with two toy models.Numerical experiments demonstrate its powerful functionality in exploring the internal mechanism of rare events triggered by weak random fluctuations.展开更多
Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation o...Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet.To this end,a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions.Furthermore,an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning.The results show that the daily operation cost can reduce by 3.57%to 5.55%as the number of dynamic charging stations increases.The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning.展开更多
The evolutionary dynamics first conceived by Darwin and Wallace, referring to as Darwinian dynamics in the present paper, has been found to be universally valid in biology. The statistical mechanics and thermodynamics...The evolutionary dynamics first conceived by Darwin and Wallace, referring to as Darwinian dynamics in the present paper, has been found to be universally valid in biology. The statistical mechanics and thermodynamics, while enormous successful in physics, have been in an awkward situation of wanting a consistent dynamical understanding. Here we present from a formal point of view an exploration of the connection between thermodynamics and Darwinian dynamics and a few related topics. We first show that the stochasticity in Darwinian dynamics implies the existence temperature, hence the canonical distribution of Boltzmann-Gibbs type. In term of relative entropy the Second Law of thermodynamics is dynamically demonstrated without detailed balance condition, and is valid regardless of size of the system. In particular, the dynamical component responsible for breaking detailed balance condition does not contribute to the change of the relative entropy. Two types of stochastic dynamical equalities of current interest are explicitly discussed in the present approach： One is based on Feynman-Kac formula and another is a generalization of Einstein relation. Both are directly accessible to experimental tests. Our demonstration indicates that Darwinian dynamics represents logically a simple and straightforward starting point for statistical mechanics and thermodynamics and is complementary to and consistent with conservative dynamics that dominates the physical sciences. Present exploration suggests the existence of a unified stochastic dynamical framework both near and far from equilibrium.展开更多
In this paper, formation tracking control problems for second-order multi-agent systems（MASs） with time-varying delays are studied, specifically those where the position and velocity of followers are designed to for...In this paper, formation tracking control problems for second-order multi-agent systems（MASs） with time-varying delays are studied, specifically those where the position and velocity of followers are designed to form a time-varying formation while tracking those of the leader. A neighboring relative state information based formation tracking protocol with an unknown gain matrix and time-varying delays is presented. The formation tracking problems are then transformed into asymptotically stable problems. Based on the Lyapunov-Krasovskii functional approach, conditions sufficient for second-order MASs with time-varying delays to realize formation tracking are examined. An approach to obtain the unknown gain matrix is given and, since neighboring relative velocity information is difficult to measure in practical applications, a formation tracking protocol with time-varying delays using only neighboring relative position information is introduced. The proposed results can be used on target enclosing problems for MASs with second-order dynamics and time-varying delays. An application for target enclosing by multiple unmanned aerial vehicles（UAVs） is given to demonstrate the feasibility of theoretical results.展开更多
A conceptual model for microscopic-macroscopic slow-fast stochastic systems is considered. A dynamical reduction procedure is presented in order to extract effective dynamics for this kind of systems. Under appropriat...A conceptual model for microscopic-macroscopic slow-fast stochastic systems is considered. A dynamical reduction procedure is presented in order to extract effective dynamics for this kind of systems. Under appropriate assumptions, the effective system is shown to approximate the original system, in the sense of a probabilistic convergence.展开更多
The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was...The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was discussed in this study.To efficiently and accurately compute the exponential of the dynamics state matrix and the matrix functions due to external loads,an adaptively filtered precise integration method was proposed,which inherits the high precision of the precise integrationmethod,improves the computational efficiency and saves the memory required.Moreover,the perturbation method was introduced to avoid repeated computations of matrix exponential and terms due to external loads.Based on the filtering and perturbation techniques,an adaptively filtered precise integration method considering perturbation for stochastic dynamics problems was developed.Two numerical experiments,including a model of phononic crystal and a bridge model considering random parameters,were performed to test the performance of the proposed method in terms of accuracy and efficiency.Numerical results show that the accuracy and efficiency of the proposed method are better than those of the existing precise integration method,the Newmark-βmethod and the Wilson-θmethod.展开更多
The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statisti...The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statistics of stochastic channel dynamics in Hodgkin–Huxley neurons. Here, we introduce a modified gate-based Langevin approach with rescaled noise strength to simulate stochastic channel dynamics. The rescaled independent gate and identical gate Langevin approaches improve the statistical results for the mean membrane voltage, inter-spike interval, and spike amplitude.展开更多
We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-pr...We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-prevailingequilibrium under R_(0)<1 and R_(0)>1 is carried out by Lyapunov method and LaSalle's invariant principle.Next,we design an aperiodically intermittent stochastic stabilization method to suppress the rumor propagation.By using the Ito formula and exponential martingale inequality,the expression of the minimum control intensity is calculated.This method can effectively stabilize the rumor propagation by choosing a suitable perturb intensity and a perturb time ratio,while minimizing the control cost.Finally,numerical examples are given to illustrate the analysis and method of the paper.展开更多
This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are rega...This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are regarded as stochastic variables,whereas the interval variables are used to treat the uncertainty parameters with limited stochastic knowledge.In this method,the PCE model is constructed through the Galerkin projection method,in which the sparse grid strategy is used to generate the integral points and the corresponding integral weights.Through the sampling in PCE,the original dynamic systems with hybrid stochastic and interval parameters can be transformed into deterministic dynamic systems,without changing their expressions.The yielded PCE model is utilized as a computationally efficient,surrogate model,and the supremum and infimum of the dynamic responses over all time iteration steps can be easily approximated through Monte Carlo simulation and percentile difference.A numerical example and an artillery exterior ballistic dynamics model are used to illustrate the feasibility and efficiency of this approach.The numerical results indicate that the dynamic response bounds obtained by the PCE approach almost match the results of the direct Monte Carlo simulation,but the computational efficiency of the PCE approach is much higher than direct Monte Carlo simulation.Moreover,the proposed method also exhibits fine precision even in high-dimensional uncertainty analysis problems.展开更多
The research on spatial epidemic models is a topic of considerable recent interest. In another hand, the advances in computer technology have stimulated the development of stochastic models. Metapopulation models are ...The research on spatial epidemic models is a topic of considerable recent interest. In another hand, the advances in computer technology have stimulated the development of stochastic models. Metapopulation models are spatial designs that involve movements of individuals between distinct subpopulations. The purpose of the present work has been to develop stochastic models in order to study the transmission dynamics and control of infectious diseases in metapopulations. The authors studied Susceptible-Infected-Susceptible （SIS） and Susceptible-lnfected-Recovered （SIR） epidemic schemes, using the Gillespie algorithm, Computational numerical simulations were carried in order to explore the models. The results obtained show how the dynamics of transmission and the application of control measures within each subpopulation may affect all subpopulations of the system. They also show how the distribution of control measures among subpopulations affects the efficacy of these strategies. The dynamics of the stochastic models developed in the current study follow the trends observed in the classic deterministic designs. Also, the present models exhibit fluctuating behavior. This work highlights the importance of the spatial distribution of the population in spread and control of infectious diseases. In addition, it shows how chance could play an important role in these scenarios.展开更多
This paper considers a concrete stochastic nonlinear system with stochastic unmeasurable inverse dynamics. Motivated by the concept of integral input-to-state stability （iISS） in deterministic systems and stochastic...This paper considers a concrete stochastic nonlinear system with stochastic unmeasurable inverse dynamics. Motivated by the concept of integral input-to-state stability （iISS） in deterministic systems and stochastic input-to-state stability （SISS） in stochastic systems, a concept of stochastic integral input-to-state stability （SiISS） using Lyapunov functions is first introduced. A constructive strategy is proposed to design a dynamic output feedback control law, which drives the state to the origin almost surely while keeping all other closed-loop signals almost surely bounded. At last, a simulation is given to verify the effectiveness of the control law.展开更多
In this paper, for a class of high-order stochastic nonlinear systems with zero dynamics which are neither necessarily feedback linearizable nor affine in the control input, the problem of state feedback stabilization...In this paper, for a class of high-order stochastic nonlinear systems with zero dynamics which are neither necessarily feedback linearizable nor affine in the control input, the problem of state feedback stabilization is investigated for the first time. Under some weaker assumptions, a smooth state feedback controller is designed, which ensures that the closed-loop system has an almost surely unique solution on [0,∞）, the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability, and all the states can be regulated to the origin almost surely. A simulation example demonstrates the control scheme.展开更多
The law of vehicle movement has long been studied under the umbrella of microscopic traffic flow models,especially the car-following(CF)models.These models of the movement of vehicles serve as the backbone of traffic ...The law of vehicle movement has long been studied under the umbrella of microscopic traffic flow models,especially the car-following(CF)models.These models of the movement of vehicles serve as the backbone of traffic flow analysis,simulation,autonomous vehicle development,etc.Two-dimensional(2D)vehicular movement is basically stochastic and is the result of interactions between a driver's behavior and a vehicle's characteristics.Current microscopic models either neglect 2D noise,or overlook vehicle dynamics.The modeling capabilities,thus,are limited,so that stochastic lateral movement cannot be reproduced.The present research extends an intelligent driver model(IDM)by explicitly considering both vehicle dynamics and 2D noises to formulate a stochastic 2D IDM model,with vehicle dynamics based on the stochastic differential equation(SDE)theory.Control inputs from the vehicle include the steer rate and longitudinal acceleration,both of which are developed based on an idea from a traditional intelligent driver model.The stochastic stability condition is analyzed on the basis of Lyapunov theory.Numerical analysis is used to assess the two cases:(i)when a vehicle accelerates from a standstill and(ii)when a platoon of vehicles follow a leader with a stop-and-go speed profile,the formation of congestion and subsequent dispersion are simulated.The results show that the model can reproduce the stochastic 2D trajectories of the vehicle and the marginal distribution of lateral movement.The proposed model can be used in both a simulation platform and a behavioral analysis of a human driver in traffic flow.展开更多
Molecular dynamics with the stochastic process provides a convenient way to compute structural and thermodynamic properties of chemical, biological, and materials systems. It is demonstrated that the virtual dynamics ...Molecular dynamics with the stochastic process provides a convenient way to compute structural and thermodynamic properties of chemical, biological, and materials systems. It is demonstrated that the virtual dynamics case that we proposed for the Langevin equation [J. Chem. Phys. 147, 184104 （2017）] in principle exists in other types of stochastic thermostats as well. The recommended ＂middle＂ scheme [J. Chem. Phys. 147, 034109 （2017）] of the Andersen thermostat is investigated as an example. As shown by both analytic and numerical results, while the real and virtual dynamics cases approach the same plateau of the characteristic correlation time in the high collision frequency limit, the accuracy and efficiency of sampling are relatively insensitive to the value of the collision frequency in a broad range. After we compare the behaviors of the Andersen thermostat to those of Langevin dynamics, a heuristic schematic representation thermostatting processes with molecular is proposed for understanding efficient stochastic dynamics.展开更多
基金Supporting Project under Grant No.RSP2025R472,King Saud University,Riyadh,Saudi Arabia。
文摘The nonlinear Schrodinger equation(NLSE) is a key tool for modeling wave propagation in nonlinear and dispersive media. This study focuses on the complex cubic NLSE with δ-potential,explored through the Brownian process. The investigation begins with the derivation of stochastic solitary wave solutions using the modified exp(-Ψ(ξ)) expansion method. To illustrate the noise effects, 3D and 2D visualizations are displayed for different non-negative values of noise parameter under suitable parameter values. Additionally, qualitative analysis of both perturbed and unperturbed dynamical systems is conducted using bifurcation and chaos theory. In bifurcation analysis, we analyze the detailed parameter analysis near fixed points of the unperturbed system. An external periodic force is applied to perturb the system, leading to an investigation of its chaotic behavior. Chaos detection tools are employed to predict the behavior of the perturbed dynamical system, with results validated through visual representations.Multistability analysis is conducted under varying initial conditions to identify multiple stable states in the perturbed dynamical system, contributing to chaotic behavior. Also, sensitivity analysis of the Hamiltonian system is performed for different initial conditions. The novelty of this work lies in the significance of the obtained results, which have not been previously explored for the considered equation. These findings offer noteworthy insights into the behavior of the complex cubic NLSE with δ-potential and its applications in fields such as nonlinear optics, quantum mechanics and Bose–Einstein condensates.
基金supported in part by the National Natural Science Foundation of China(11771001)the Key Natural Science Research Project of Universities of Anhui Province,China(2022AH050108)。
文摘Dear Editor,This letter addresses the synchronization problem of a class of delayed stochastic complex dynamical networks consisting of multiple drive and response nodes.The aim is to achieve mean square exponential synchronization for the drive-response nodes despite the simultaneous presence of time delays and stochastic noises in node dynamics.
基金supported by Natural Science Foundation of Shandong Province(Grant Nos.ZR2020MA032,ZR2022MA029)National Natural Science Foundation of China(Grant Nos.12171279,72171133)+1 种基金The second named author was supported by National Key R&D Program of China(Grant No.2022YFA1006102)National Natural Science Foundation of China(Grant No.11831010)。
文摘This paper concerns two-player zero-sum stochastic differential games with nonanticipative strategies against closed-loop controls in the case where the coefficients of mean-field stochastic differential equations and cost functional depend on the joint distribution of the state and the control.In our game,both the(lower and upper)value functions and the(lower and upper)second-order Bellman–Isaacs equations are defined on the Wasserstein space P_(2)(R^(n))which is an infinite dimensional space.The dynamic programming principle for the value functions is proved.If the(upper and lower)value functions are smooth enough,we show that they are the classical solutions to the second-order Bellman–Isaacs equations.On the other hand,the classical solutions to the(upper and lower)Bellman–Isaacs equations are unique and coincide with the(upper and lower)value functions.As an illustrative application,the linear quadratic case is considered.Under the Isaacs condition,the explicit expressions of optimal closed-loop controls for both players are given.Finally,we introduce the intrinsic notion of viscosity solution of our second-order Bellman–Isaacs equations,and characterize the(upper and lower)value functions as their viscosity solutions.
基金supported by the National Natural Science Foundation of China(Grant No.12304389,12274053)the Science and Technology Research Project of Xiamen University of Technology(Grant No.YKJ19025R)the Scientific Research Foundation of NEU(Grant No.01270021920501*115)。
文摘We present a general numerical simulation method to solve non-Markovian dynamics of an open quantum system influenced by quantum Brownian motion.Based on the determined memory kernel function,this method enables the resolution of non-Markovian dynamics for a wide range of system Hamiltonians and spectral densities.The system dynamics are described by exact integro-differential operator equations without any common approximations and they are simulated in this work by definite-number equations with stochastic initial conditions.This approach ensures the applicability of mature numerical methods and maintains computational complexity that remains largely invariant,even when dealing with more complex models.The high accuracy of our simulation is evident from a comparison with the results obtained from corresponding exact master equations,underscoring the reliability and precision of our method.
基金supported by the start-up funding of CQNU (Grant No. 24XLB010)supported by the Science and Technology Research Program of Chongqing Municipal Education Commission (Grant No. KJQN202100514)+3 种基金funding from Chongqing Natural Science Foundation under Grant No. CSTB2022NSCQ-JQX0018the Fundamental Research Funds for the Central Universities Grant No. 2021CDJZYJH-003Xiaomi Foundation/Xiaomi Young Talents Programfunding from the National Science Foundation of China under Grant Nos. 12404169, 12147172, 12274046, 11874094, 12147102, and 12347101。
文摘The quantum phase transition between Z_(2) plaquette valence bound solid(PVBS) and superfluid(SF) phases on the planar pyrochlore lattice(square ice) is under debate. To gain further insight, here, we focus on the dynamical features of the hard-core Bose–Hubbard model on this lattice and study the excitation spectra by combining stochastic analytic continuation and quantum Monte Carlo simulation. In both PVBS and SF phases,a flat band with bow-tie structure is observed and can be explained by certain symmetries. At the transition point,the spectra turn to be continuous and gapless. A(2+1)-dimensional Abelian–Higgs model with mixed 't Hooft anomaly is proposed to describe the transition, where the anomaly matching predicts that the deconfinement can exist on the domain walls. From the snapshot of the spin configuration in real space, we found the existence of the domain wall. We also found that the spectrum along a specific path in momentum space from PVBS phase to the transition point can be well described by an XXZ spin chain, and the critical theory of XXZ spin chain matches the anomaly. The two-spinon continuum along this specific path implies additional domain walls(point defect) can emerge in the domain walls(line defect) and take the role of deconfinement at the transition point.
基金cosupported by the National Natural Science Foundation of China(No.12202487)。
文摘The modeling of turbulence,especially the high-speed compressible turbulence encountered in aerospace engineering,has always being a significant challenge in terms of balancing efficiency and accuracy.Most traditional models typically show limitations in universality,accuracy,and reliance on past experience.The stochastic multi-scale models show great potential in addressing these issues by representing turbulence across all characteristic scales in a reduced-dimensional space,maintaining sufficient accuracy while reducing computational cost.This review systematically summarizes advances in methods related to a widely used and refined stochastic multi-scale model,the One-Dimensional Turbulence(ODT).The advancements in formulations are emphasized for stand-alone incompressible ODT models,stand-alone compressible ODT models,and coupling methods.Some diagrams are also provided to facilitate more readers to understand the ODT methods.Subsequently,the significant developments and applications of stand-alone ODT models and coupling methods are introduced and critically evaluated.Despite the extensively recognized effectiveness of ODT models in low-speed turbulent flows,it is crucial to emphasize that there is still a research gap in the field of ODT coupling methods that are capable of accurately and efficiently simulating complex,three-dimensional,high-speed compressible turbulent flows up to now.Based on an analysis of the advantages and limitations of existing ODT methods,the recent advancement in the conservative compressible ODT model is considered to have provided a promising approach to tackle the modeling challenges of high-speed compressible turbulence.Therefore,this review outlines several recommended new research subjects and challenging issues to inspire further research in simulating complex,three-dimensional,high-speed compressible turbulent flows using ODT models.
基金Project supported by the Natural Science Foundation of Jiangsu Province (Grant No.BK20220917)the National Natural Science Foundation of China (Grant Nos.12001213 and 12302035)。
文摘We present a large deviation theory that characterizes the exponential estimate for rare events in stochastic dynamical systems in the limit of weak noise.We aim to consider a next-to-leading-order approximation for more accurate calculation of the mean exit time by computing large deviation prefactors with the aid of machine learning.More specifically,we design a neural network framework to compute quasipotential,most probable paths and prefactors based on the orthogonal decomposition of a vector field.We corroborate the higher effectiveness and accuracy of our algorithm with two toy models.Numerical experiments demonstrate its powerful functionality in exploring the internal mechanism of rare events triggered by weak random fluctuations.
基金the Key Soft Science Project of Shanghai“Science and Technology Innovation Action Plan”(No.21692195200)the Project of Chinese Academy of Engineering(No.2020-XZ-15)。
文摘Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet.To this end,a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions.Furthermore,an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning.The results show that the daily operation cost can reduce by 3.57%to 5.55%as the number of dynamic charging stations increases.The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning.
基金The project supported in part by USA NIH Grant under HG002894
文摘The evolutionary dynamics first conceived by Darwin and Wallace, referring to as Darwinian dynamics in the present paper, has been found to be universally valid in biology. The statistical mechanics and thermodynamics, while enormous successful in physics, have been in an awkward situation of wanting a consistent dynamical understanding. Here we present from a formal point of view an exploration of the connection between thermodynamics and Darwinian dynamics and a few related topics. We first show that the stochasticity in Darwinian dynamics implies the existence temperature, hence the canonical distribution of Boltzmann-Gibbs type. In term of relative entropy the Second Law of thermodynamics is dynamically demonstrated without detailed balance condition, and is valid regardless of size of the system. In particular, the dynamical component responsible for breaking detailed balance condition does not contribute to the change of the relative entropy. Two types of stochastic dynamical equalities of current interest are explicitly discussed in the present approach： One is based on Feynman-Kac formula and another is a generalization of Einstein relation. Both are directly accessible to experimental tests. Our demonstration indicates that Darwinian dynamics represents logically a simple and straightforward starting point for statistical mechanics and thermodynamics and is complementary to and consistent with conservative dynamics that dominates the physical sciences. Present exploration suggests the existence of a unified stochastic dynamical framework both near and far from equilibrium.
基金co-supported by the National Natural Science Foundation of China (Nos. 61333011, 91216304 and 61121003)
文摘In this paper, formation tracking control problems for second-order multi-agent systems（MASs） with time-varying delays are studied, specifically those where the position and velocity of followers are designed to form a time-varying formation while tracking those of the leader. A neighboring relative state information based formation tracking protocol with an unknown gain matrix and time-varying delays is presented. The formation tracking problems are then transformed into asymptotically stable problems. Based on the Lyapunov-Krasovskii functional approach, conditions sufficient for second-order MASs with time-varying delays to realize formation tracking are examined. An approach to obtain the unknown gain matrix is given and, since neighboring relative velocity information is difficult to measure in practical applications, a formation tracking protocol with time-varying delays using only neighboring relative position information is introduced. The proposed results can be used on target enclosing problems for MASs with second-order dynamics and time-varying delays. An application for target enclosing by multiple unmanned aerial vehicles（UAVs） is given to demonstrate the feasibility of theoretical results.
基金supported by NSF of China (10901065, 10971225, and11028102)the NSF Grants 1025422 and 0731201the Cheung Kong Scholars Program, and an open research grant from the State Key Laboratory for Nonlinear Mechanics at the Chinese Academy of Sciences
文摘A conceptual model for microscopic-macroscopic slow-fast stochastic systems is considered. A dynamical reduction procedure is presented in order to extract effective dynamics for this kind of systems. Under appropriate assumptions, the effective system is shown to approximate the original system, in the sense of a probabilistic convergence.
基金the support of the National Natural Science Foundation of China(Grant Nos.11472067 and 51609034)the Science Foundation of Liaoning Province of China(No.2021-MS-119)+1 种基金the Dalian Youth Science and Technology Star Project(No.2018RQ06)the Fundamental Research Funds for the Central Universities(Grant No.DUT20GJ216).
文摘The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was discussed in this study.To efficiently and accurately compute the exponential of the dynamics state matrix and the matrix functions due to external loads,an adaptively filtered precise integration method was proposed,which inherits the high precision of the precise integrationmethod,improves the computational efficiency and saves the memory required.Moreover,the perturbation method was introduced to avoid repeated computations of matrix exponential and terms due to external loads.Based on the filtering and perturbation techniques,an adaptively filtered precise integration method considering perturbation for stochastic dynamics problems was developed.Two numerical experiments,including a model of phononic crystal and a bridge model considering random parameters,were performed to test the performance of the proposed method in terms of accuracy and efficiency.Numerical results show that the accuracy and efficiency of the proposed method are better than those of the existing precise integration method,the Newmark-βmethod and the Wilson-θmethod.
基金Project supported by the National Natural Science Foundation for Distinguished Young Scholars of China(Grant No.11125419)the National Natural Science Foundation of China(Grant No.10925525)+1 种基金the Funds for the Leading Talents of Fujian ProvinceChina
文摘The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statistics of stochastic channel dynamics in Hodgkin–Huxley neurons. Here, we introduce a modified gate-based Langevin approach with rescaled noise strength to simulate stochastic channel dynamics. The rescaled independent gate and identical gate Langevin approaches improve the statistical results for the mean membrane voltage, inter-spike interval, and spike amplitude.
基金Project supported by the Guangzhou Science and Technology Project(Grant No.20210202710)Scientific Research Project of Guangzhou University(Grant No.YG2020010)。
文摘We propose a novel rumor propagation model with guidance mechanism in hetero geneous complex networks.Firstly,the sharp threshold of rumor propagation,global stability of the information-equilibrium and information-prevailingequilibrium under R_(0)<1 and R_(0)>1 is carried out by Lyapunov method and LaSalle's invariant principle.Next,we design an aperiodically intermittent stochastic stabilization method to suppress the rumor propagation.By using the Ito formula and exponential martingale inequality,the expression of the minimum control intensity is calculated.This method can effectively stabilize the rumor propagation by choosing a suitable perturb intensity and a perturb time ratio,while minimizing the control cost.Finally,numerical examples are given to illustrate the analysis and method of the paper.
基金financially supported by the National Natural Science Foun-dation of China[Grant Nos.301070603,11572158]。
文摘This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion(PCE).The uncertainty parameters with sufficient information are regarded as stochastic variables,whereas the interval variables are used to treat the uncertainty parameters with limited stochastic knowledge.In this method,the PCE model is constructed through the Galerkin projection method,in which the sparse grid strategy is used to generate the integral points and the corresponding integral weights.Through the sampling in PCE,the original dynamic systems with hybrid stochastic and interval parameters can be transformed into deterministic dynamic systems,without changing their expressions.The yielded PCE model is utilized as a computationally efficient,surrogate model,and the supremum and infimum of the dynamic responses over all time iteration steps can be easily approximated through Monte Carlo simulation and percentile difference.A numerical example and an artillery exterior ballistic dynamics model are used to illustrate the feasibility and efficiency of this approach.The numerical results indicate that the dynamic response bounds obtained by the PCE approach almost match the results of the direct Monte Carlo simulation,but the computational efficiency of the PCE approach is much higher than direct Monte Carlo simulation.Moreover,the proposed method also exhibits fine precision even in high-dimensional uncertainty analysis problems.
文摘The research on spatial epidemic models is a topic of considerable recent interest. In another hand, the advances in computer technology have stimulated the development of stochastic models. Metapopulation models are spatial designs that involve movements of individuals between distinct subpopulations. The purpose of the present work has been to develop stochastic models in order to study the transmission dynamics and control of infectious diseases in metapopulations. The authors studied Susceptible-Infected-Susceptible （SIS） and Susceptible-lnfected-Recovered （SIR） epidemic schemes, using the Gillespie algorithm, Computational numerical simulations were carried in order to explore the models. The results obtained show how the dynamics of transmission and the application of control measures within each subpopulation may affect all subpopulations of the system. They also show how the distribution of control measures among subpopulations affects the efficacy of these strategies. The dynamics of the stochastic models developed in the current study follow the trends observed in the classic deterministic designs. Also, the present models exhibit fluctuating behavior. This work highlights the importance of the spatial distribution of the population in spread and control of infectious diseases. In addition, it shows how chance could play an important role in these scenarios.
基金supported by National Natural Science Foundation of China (No. 60774010, 10971256, and 60974028)Jiangsu"Six Top Talents" (No. 07-A-020)+2 种基金Natural Science Foundation of Jiangsu Province (No. BK2009083)Program for Fundamental Research of Natural Sciences in Universities of Jiangsu Province(No.07KJB510114)Natural Science Foundation of Xuzhou Normal University (No. 08XLB20)
文摘This paper considers a concrete stochastic nonlinear system with stochastic unmeasurable inverse dynamics. Motivated by the concept of integral input-to-state stability （iISS） in deterministic systems and stochastic input-to-state stability （SISS） in stochastic systems, a concept of stochastic integral input-to-state stability （SiISS） using Lyapunov functions is first introduced. A constructive strategy is proposed to design a dynamic output feedback control law, which drives the state to the origin almost surely while keeping all other closed-loop signals almost surely bounded. At last, a simulation is given to verify the effectiveness of the control law.
基金Program for New Century Excellent Talents in University of China (NCET-05-0607)National Natural Science Fou-ndation of China (No.60774010)Project for Fundamental Research of Natural Sciences in Universities of Jingsu Province (No.07KJB510114)
文摘In this paper, for a class of high-order stochastic nonlinear systems with zero dynamics which are neither necessarily feedback linearizable nor affine in the control input, the problem of state feedback stabilization is investigated for the first time. Under some weaker assumptions, a smooth state feedback controller is designed, which ensures that the closed-loop system has an almost surely unique solution on [0,∞）, the equilibrium at the origin of the closed-loop system is globally asymptotically stable in probability, and all the states can be regulated to the origin almost surely. A simulation example demonstrates the control scheme.
基金Project supported by the National Key Research and Development Program of China(Grant No.2021YFE0194400)the National Natural Science Foundation of China(Grant Nos.52272314 and 52131202)+1 种基金the Fund for Humanities and Social Science from the Ministry of Education of China(Grant No.21YJCZH116)the Public Welfare Scientific Research Project(Grant No.LGF22E080007)。
文摘The law of vehicle movement has long been studied under the umbrella of microscopic traffic flow models,especially the car-following(CF)models.These models of the movement of vehicles serve as the backbone of traffic flow analysis,simulation,autonomous vehicle development,etc.Two-dimensional(2D)vehicular movement is basically stochastic and is the result of interactions between a driver's behavior and a vehicle's characteristics.Current microscopic models either neglect 2D noise,or overlook vehicle dynamics.The modeling capabilities,thus,are limited,so that stochastic lateral movement cannot be reproduced.The present research extends an intelligent driver model(IDM)by explicitly considering both vehicle dynamics and 2D noises to formulate a stochastic 2D IDM model,with vehicle dynamics based on the stochastic differential equation(SDE)theory.Control inputs from the vehicle include the steer rate and longitudinal acceleration,both of which are developed based on an idea from a traditional intelligent driver model.The stochastic stability condition is analyzed on the basis of Lyapunov theory.Numerical analysis is used to assess the two cases:(i)when a vehicle accelerates from a standstill and(ii)when a platoon of vehicles follow a leader with a stop-and-go speed profile,the formation of congestion and subsequent dispersion are simulated.The results show that the model can reproduce the stochastic 2D trajectories of the vehicle and the marginal distribution of lateral movement.The proposed model can be used in both a simulation platform and a behavioral analysis of a human driver in traffic flow.
文摘Molecular dynamics with the stochastic process provides a convenient way to compute structural and thermodynamic properties of chemical, biological, and materials systems. It is demonstrated that the virtual dynamics case that we proposed for the Langevin equation [J. Chem. Phys. 147, 184104 （2017）] in principle exists in other types of stochastic thermostats as well. The recommended ＂middle＂ scheme [J. Chem. Phys. 147, 034109 （2017）] of the Andersen thermostat is investigated as an example. As shown by both analytic and numerical results, while the real and virtual dynamics cases approach the same plateau of the characteristic correlation time in the high collision frequency limit, the accuracy and efficiency of sampling are relatively insensitive to the value of the collision frequency in a broad range. After we compare the behaviors of the Andersen thermostat to those of Langevin dynamics, a heuristic schematic representation thermostatting processes with molecular is proposed for understanding efficient stochastic dynamics.
