Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.Ho...Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.However,solving the Hamilton-Jacobi-Bellman(HJB)equations for nonlinear systems requires precise and complicated dynamics.Moreover,the research and application of IRL in continuous-time(CT)systems must be further improved.To develop the IRL of a CT nonlinear system,a data-based adaptive neural dynamic programming(ANDP)method is proposed to investigate the optimal control problem of uncertain CT multi-input systems such that the knowledge of the dynamics in the HJB equation is unnecessary.First,the multi-input model is approximated using a neural network(NN),which can be utilized to design an integral reinforcement signal.Subsequently,two criterion networks and one action network are constructed based on the integral reinforcement signal.A nonzero-sum Nash equilibrium can be reached by learning the optimal strategies of the multi-input model.In this scheme,the NN weights are constantly updated using an adaptive algorithm.The weight convergence and the system stability are analyzed in detail.The optimal control problem of a multi-input nonlinear CT system is effectively solved using the ANDP scheme,and the results are verified by a simulation study.展开更多
A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the expl...A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the explaination of the underlying mechanism for these fingerprints is still limited.In this paper,we propose the differential form of the memristor function,and we disclose the dynamical mechanism of the memristor according to the differential form.The symmetry of the curve is only determined by the driven signal,and the shrinking loop area results from the shrinking area enclosed by driven signal and the time coordinate axis.Significantly,we find the condition for the phase transition of a memristor,and the resistance switches between the positive resistance,local zero resistance,and local negative resistance.This phase transition is confirmed in the HP memristor.These results advance the understanding of the dynamics mechanism and phase transition of a memristor.展开更多
Biological neurons exhibit a double-membrane structure and perform specialized functions.Replicating the doublemembrane architecture in artificial neurons to mimic biological neuronal functions is a compelling researc...Biological neurons exhibit a double-membrane structure and perform specialized functions.Replicating the doublemembrane architecture in artificial neurons to mimic biological neuronal functions is a compelling research challenge.In this study,we propose a multifunctional neural circuit composed of two capacitors,two linear resistors,a phototube cell,a nonlinear resistor,and a memristor.The phototube and charge-controlled memristor serve as sensors for external light and electric field signals,respectively.By applying Kirchhoff's and Helmholtz's laws,we derive the system's nonlinear dynamical equations and energy function.We further investigate the circuit's dynamics using methods from nonlinear dynamics.Our results show that the circuit can exhibit both periodic and chaotic patterns under stimulation by external light and electric fields.展开更多
Dynamical decoupling(DD),usually implemented by sophisticated sequences of instantaneous control pulses,is a well-established quantum control technique for quantum information and quantum sensing.In practice,the pulse...Dynamical decoupling(DD),usually implemented by sophisticated sequences of instantaneous control pulses,is a well-established quantum control technique for quantum information and quantum sensing.In practice,the pulses are inevitably imperfect with many systematic errors that may influence the performances of DD.In particular,Rabi error and detuning are primary systemic errors arising from finite pulse duration,incorrect time control,and frequency instability.Here,we propose a phase-modulated DD with staggered global phases for the basic units of the pulse sequences to suppress these systemic errors.By varying the global phases appended to the pulses in the dynamical decoupling unit alternatively with 0 orπ,our protocol can significantly reduce the influences of Rabi error and detuning.Our protocol is general and can be combined with the most existing DD sequences such as universal DD,knill DD,XY,etc.As an example,we further apply our method to quantum lock-in detection for measuring time-dependent alternating signals.Our study paves the way for a simple and feasible way to realize robust dynamical decoupling sequences,which can be applicable for various quantum sensing scenarios.展开更多
The recent discovery of type-Ⅶboron-carbon clathrates with calculated superconducting transition temperatures approaching~100 K has sparked interest in exploring new conventional superconductors that may be stabilize...The recent discovery of type-Ⅶboron-carbon clathrates with calculated superconducting transition temperatures approaching~100 K has sparked interest in exploring new conventional superconductors that may be stabilized at ambient pressure.The electronic structure of the clathrate is highly tunable based on the ability to substitute different metal atoms within the cages,which may also be large enough to host small molecules.Here we introduce molecular hydrogen(H_(2))within the clathrate cages and investigate its impact on electron-phonon coupling interactions and the superconducting transition temperature(T_(c)).Our approach involves combining molecular hydrogen with the new diamond-like covalent framework,resulting in a hydrogen-encapsulated clathrate,(H_(2))B_(3)C_(3).A notable characteristic of(H_(2))B_(3)C_(3)is the dynamic behavior of the H_(2)molecules,which exhibit nearly free rotations within the B-C cages,resulting in a dynamic structure that remains cubic on average.The static structure of(H_(2))B_(3)C_(3)(a snapshot in its dynamic trajectory)is calculated to be dynamically stable at ambient and low pressures.Topological analysis of the electron density reveals weak van der Waals interactions between molecular hydrogen and the B-C cages,marginally influencing the electronic structure of the material.The electron count and electronic structure calculations indicate that(H_(2))B_(3)C_(3)is a hole conductor,in which H_(2)molecules donate a portion of their valence electron density to the metallic cage framework.Electron-phonon coupling calculation using the Migdal-Eliashberg theory predicts that(H_(2))B_(3)C_(3)possesses a T_(c) of 46 K under ambient pressure.These results indicate potential for additional light-element substitutions within the type-Ⅶclathrate framework and suggest the possibility of molecular hydrogen as a new approach to optimizing the electronic structures of this new class of superconducting materials.展开更多
Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assist...Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assistance of InSAR in the North China Plain,which served as the research area.Moreover,the GNSS result was used to correct the InSAR result for the vertical deformation field,which has a relatively unified deformation reference.By integrating the vertical deformation field with the national elevation control point,an analysis and evaluation of changes in the National Elevation Datum were conducted.In addition,a regional remeasurement scheme was formulated to achieve dynamic updates and mainte-nance of the National Elevation Datum on a regional scale.Through data acquisition and processing,we successfully improved reliability within the main subsidence areas for future use.As a result,updating the elevation values utilize a regional update method,and a dynamic and economical technical process to update the National Elevation Datum is shown in the study.展开更多
The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous flui...The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.展开更多
Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This r...Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This review synthesizes the theoretical advancements,computational approaches,emerging challenges,and possible research directions in the field.Firstly,we briefly review the fundamental theory of continuous-time optimal control,including Pontryagin's maximum principle(PMP)and dynamic programming principle(DPP).Secondly,we present the foundational results in optimal impulse control,including necessary conditions and sufficient conditions.Thirdly,we systematize impulse game methodologies,from Nash equilibrium existence theory to the connection between Nash equilibrium and systems stability.Fourthly,we summarize the numerical algorithms including the intelligent computation approaches.Finally,we examine the new trends and challenges in theory and applications as well as computational considerations.展开更多
We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an a...We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an asymmetry in its structure,which is caused by the differences in the sizes and the coupling positions of the giant atoms.The system achieves different types of EPR steering and the reversal of one-way EPR steering by modulating parameters.Furthermore,the symmetry and asymmetry of the system structure,in their responses to parameter modulation,both reveal the asymmetry of EPR steering.In this process,we discover that with the increase in temperature,different types of steering can be transferred from Casimir photons to giant atoms.We also achieve the monogamy of the multipartite system.These results provide important assistance for secure quantum communication,and further intuitively validating the asymmetry of EPR steering from multiple perspectives.展开更多
To address the disk-halo degeneracy problem,we investigate the nearby barred spiral galaxy NGC 1097.We construct mass models using 3.6 and 4.5μm near-infrared photometric images from the S^(4)G survey,constrained by ...To address the disk-halo degeneracy problem,we investigate the nearby barred spiral galaxy NGC 1097.We construct mass models using 3.6 and 4.5μm near-infrared photometric images from the S^(4)G survey,constrained by rotation curves derived from CO(J=2–1)data from the PHANGS-ALMA survey.These models serve as inputs for a suite of hydrodynamic simulations,where we systematically test the influence of key parameters including the disk mass scaling factor(f_(M)),bar pattern speed(Ω_(b)),and gas sound speed(c_(s)).By comparing the CO(2–1)kinematic maps in the bar region with those from the simulations,we perform a standardχ^(2)analysis to identify the best-fit model.The best-fit model reproduces the observed morphological and kinematic gas features of the galaxy,indicating that NGC 1097 likely hosts a maximal disk with a slowly rotating bar.We also test the influence of a boxy/peanut-shaped(B/P)bulge by incorporating a double-peaked vertical density profile into the model.This B/P structure tends to weaken the bar’s non-axisymmetric potential and necessitate a higher bar pattern speed to reproduce the observed gas morphology.展开更多
We investigate dynamical quantum phase transitions(DQPTs)in Marko-vian open quantum systems using a variational quantum simulation(VQS)algorithm based on quantum state diffusion(QSD).This approach reformulates the Lin...We investigate dynamical quantum phase transitions(DQPTs)in Marko-vian open quantum systems using a variational quantum simulation(VQS)algorithm based on quantum state diffusion(QSD).This approach reformulates the Lindblad master equation as an ensemble of pure-state trajectories,enabling efficient simula-tion of dissipative quantum dynam-ics with effectively reduced quantum resources.Focusing on the one-di-mensional transverse-field Ising mod-el(TFIM),we simulate quench dynamics under both local and global Lindblad dissipation.The QSD-VQS algorithm accurately captures the nonanalytic cusps in the Loschmidt rate function,and reveals their modulation by dissipation strength and system size.Notably,DQPTs are gradually suppressed under strong local dissipation,while they persist under strong global dissipation due to collective environmental effects.Benchmarking against exact Lindblad solutions confirms the high accuracy and scalability of our method.展开更多
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
We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron...We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron hopping parameters,the strong-coupling pseudogap in the two-dimensional Hubbard model can be either enhanced or suppressed in the doped Mott insulator regime.We find that in underdoped cases,the closing of pseudogap leads to a significant enhancement of superconductivity,indicating competition between the two in the underdoped regime.In contrast,at large dopings,suppressing the pseudogap is accompanied by a concurrent decrease in the superconducting transition temperature Tc,which can be attributed to a reduction in antiferromagnetic correlations behind both the pseudogap and superconductivity.We elucidate this evolving relationship between pseudogap and superconductivity across different doping regimes.展开更多
Purpose–The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system.This paper aims to define and substantiate the ass...Purpose–The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system.This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice.The key principles and approacheswill be proposed,and their applications to high-speed trains in Chinawill be presented.Design/methodology/approach–First,the structural integrity and dynamical integrity of high-speed trains are defined,and their relationship is introduced.Then,the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided.Finally,the principles and approaches for assessing the dynamical integrity of highspeed trains are presented and a novel operational assessment method is further presented.Findings–Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system.For assessing the structural integrity of structural components,an open-loop analysis considering both normal and abnormal vehicle conditions is needed.For assessing the structural integrity of dynamical components,a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed.The analysis of vehicle system dynamics should follow the principles of complete objects,conditions and indices.Numerical,experimental and operational approaches should be combined to achieve effective assessments.Originality/value–The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects,better lifespan management of train components and better maintenance decision-making for high-speed trains.展开更多
Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments.In the past several decades,earthquake triggering has attracted increasing attention of scholars in relation t...Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments.In the past several decades,earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering,earthquake prediction,and the desire to use the mechanism of earthquake triggering to reduce,prevent,or trigger earthquakes.Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes.In the past several decades,some models have been developed,including static,dynamic,quasi‐static,and other models.Some reviews have been published,but explosiontriggered seismicity was not included.In recent years,some new results on earthquake triggering have emerged.Therefore,this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area.Instead of a complete review of the relevant literature,this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.展开更多
The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown th...The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.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
In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three...In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.展开更多
We introduce and study the relation between Pesin-Pitskel topological pressure on an arbitrary subset and measure theoretic pressure of Borel probability measure for nonautonomous dynamical systems,which is an extensi...We introduce and study the relation between Pesin-Pitskel topological pressure on an arbitrary subset and measure theoretic pressure of Borel probability measure for nonautonomous dynamical systems,which is an extension of the classical definition of Bowen topological entropy.We show that the Pesin-Pitskel topological pressure can be determined by the local pressures of measures in nonautonomous case and establish a variational principle for Pesin-Pitskel topological pressure on compact subsets in the context of nonautonomous dynamical systems.展开更多
Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring ...Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management.However,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism.When the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression accurately.In addition,DT update algorithms are difficult to be integrated simultaneously by current methods.This paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism.The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating.Furthermore,the Independence Principle for the abnormal detection is proposed to refine the theory of DT.Events at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend.The interaction and collaboration between different loop models are also discussed.Finally,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed method.The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.展开更多
文摘Integral reinforcement learning(IRL)is an effective tool for solving optimal control problems of nonlinear systems,and it has been widely utilized in optimal controller design for solving discrete-time nonlinearity.However,solving the Hamilton-Jacobi-Bellman(HJB)equations for nonlinear systems requires precise and complicated dynamics.Moreover,the research and application of IRL in continuous-time(CT)systems must be further improved.To develop the IRL of a CT nonlinear system,a data-based adaptive neural dynamic programming(ANDP)method is proposed to investigate the optimal control problem of uncertain CT multi-input systems such that the knowledge of the dynamics in the HJB equation is unnecessary.First,the multi-input model is approximated using a neural network(NN),which can be utilized to design an integral reinforcement signal.Subsequently,two criterion networks and one action network are constructed based on the integral reinforcement signal.A nonzero-sum Nash equilibrium can be reached by learning the optimal strategies of the multi-input model.In this scheme,the NN weights are constantly updated using an adaptive algorithm.The weight convergence and the system stability are analyzed in detail.The optimal control problem of a multi-input nonlinear CT system is effectively solved using the ANDP scheme,and the results are verified by a simulation study.
基金supported by the National Natural Science Foundation of China under Grant Nos.62071496,62061008the Research and Innovation Project of Graduate of Central South University under Grant No.2023ZZTS0168.
文摘A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the explaination of the underlying mechanism for these fingerprints is still limited.In this paper,we propose the differential form of the memristor function,and we disclose the dynamical mechanism of the memristor according to the differential form.The symmetry of the curve is only determined by the driven signal,and the shrinking loop area results from the shrinking area enclosed by driven signal and the time coordinate axis.Significantly,we find the condition for the phase transition of a memristor,and the resistance switches between the positive resistance,local zero resistance,and local negative resistance.This phase transition is confirmed in the HP memristor.These results advance the understanding of the dynamics mechanism and phase transition of a memristor.
基金Project supported by the Gansu Provincial Department of Education University Teacher Innovation Fund Project(Grant No.2024A-168)the Qingyang Science and Technology Plan Project(Grant No.QY-STK-2024B-193)the Horizontal Research Project of Longdong University(Grant No.HXZK2422)。
文摘Biological neurons exhibit a double-membrane structure and perform specialized functions.Replicating the doublemembrane architecture in artificial neurons to mimic biological neuronal functions is a compelling research challenge.In this study,we propose a multifunctional neural circuit composed of two capacitors,two linear resistors,a phototube cell,a nonlinear resistor,and a memristor.The phototube and charge-controlled memristor serve as sensors for external light and electric field signals,respectively.By applying Kirchhoff's and Helmholtz's laws,we derive the system's nonlinear dynamical equations and energy function.We further investigate the circuit's dynamics using methods from nonlinear dynamics.Our results show that the circuit can exhibit both periodic and chaotic patterns under stimulation by external light and electric fields.
基金Project supported by the National Key Research and Development Program of China(Grant No.2022YFA1404104)the National Natural Science Foundation of China(Grant Nos.92476201,12025509,12305022,and 12475029)+1 种基金the Key-Area Research and Development Program of Guangdong Province,China(Grant No.2019B030330001)Guangdong Provincial Quantum Science Strategic Initiative Fund(Grant Nos.GDZX2305006 and GDZX2405002)。
文摘Dynamical decoupling(DD),usually implemented by sophisticated sequences of instantaneous control pulses,is a well-established quantum control technique for quantum information and quantum sensing.In practice,the pulses are inevitably imperfect with many systematic errors that may influence the performances of DD.In particular,Rabi error and detuning are primary systemic errors arising from finite pulse duration,incorrect time control,and frequency instability.Here,we propose a phase-modulated DD with staggered global phases for the basic units of the pulse sequences to suppress these systemic errors.By varying the global phases appended to the pulses in the dynamical decoupling unit alternatively with 0 orπ,our protocol can significantly reduce the influences of Rabi error and detuning.Our protocol is general and can be combined with the most existing DD sequences such as universal DD,knill DD,XY,etc.As an example,we further apply our method to quantum lock-in detection for measuring time-dependent alternating signals.Our study paves the way for a simple and feasible way to realize robust dynamical decoupling sequences,which can be applicable for various quantum sensing scenarios.
基金supported by Carnegie Canada and Natural Sciences and Engineering Research Council of Canada(NSERC)support from the U.S.Department of Energy(DOE),Office of Science,Basic Energy Sciences,under Award No.DESC0020683。
文摘The recent discovery of type-Ⅶboron-carbon clathrates with calculated superconducting transition temperatures approaching~100 K has sparked interest in exploring new conventional superconductors that may be stabilized at ambient pressure.The electronic structure of the clathrate is highly tunable based on the ability to substitute different metal atoms within the cages,which may also be large enough to host small molecules.Here we introduce molecular hydrogen(H_(2))within the clathrate cages and investigate its impact on electron-phonon coupling interactions and the superconducting transition temperature(T_(c)).Our approach involves combining molecular hydrogen with the new diamond-like covalent framework,resulting in a hydrogen-encapsulated clathrate,(H_(2))B_(3)C_(3).A notable characteristic of(H_(2))B_(3)C_(3)is the dynamic behavior of the H_(2)molecules,which exhibit nearly free rotations within the B-C cages,resulting in a dynamic structure that remains cubic on average.The static structure of(H_(2))B_(3)C_(3)(a snapshot in its dynamic trajectory)is calculated to be dynamically stable at ambient and low pressures.Topological analysis of the electron density reveals weak van der Waals interactions between molecular hydrogen and the B-C cages,marginally influencing the electronic structure of the material.The electron count and electronic structure calculations indicate that(H_(2))B_(3)C_(3)is a hole conductor,in which H_(2)molecules donate a portion of their valence electron density to the metallic cage framework.Electron-phonon coupling calculation using the Migdal-Eliashberg theory predicts that(H_(2))B_(3)C_(3)possesses a T_(c) of 46 K under ambient pressure.These results indicate potential for additional light-element substitutions within the type-Ⅶclathrate framework and suggest the possibility of molecular hydrogen as a new approach to optimizing the electronic structures of this new class of superconducting materials.
基金supported by the Scientific and Technological Innovation Project of SHASG(SCK2022-01)National Key Research and Development Program of China(2016YFC0803109)。
文摘Land subsidence significantly impacts the accuracy of the National Elevation Datum in China.In order to solve this issue,a dynamic and economical way was proposed to update the National Elevation Datum with the assistance of InSAR in the North China Plain,which served as the research area.Moreover,the GNSS result was used to correct the InSAR result for the vertical deformation field,which has a relatively unified deformation reference.By integrating the vertical deformation field with the national elevation control point,an analysis and evaluation of changes in the National Elevation Datum were conducted.In addition,a regional remeasurement scheme was formulated to achieve dynamic updates and mainte-nance of the National Elevation Datum on a regional scale.Through data acquisition and processing,we successfully improved reliability within the main subsidence areas for future use.As a result,updating the elevation values utilize a regional update method,and a dynamic and economical technical process to update the National Elevation Datum is shown in the study.
基金supported by National Key Research and Development Program of China under Grant 2024YFE0210800National Natural Science Foundation of China under Grant 62495062Beijing Natural Science Foundation under Grant L242017.
文摘The Dynamical Density Functional Theory(DDFT)algorithm,derived by associating classical Density Functional Theory(DFT)with the fundamental Smoluchowski dynamical equation,describes the evolution of inhomo-geneous fluid density distributions over time.It plays a significant role in studying the evolution of density distributions over time in inhomogeneous systems.The Sunway Bluelight II supercomputer,as a new generation of China’s developed supercomputer,possesses powerful computational capabilities.Porting and optimizing industrial software on this platform holds significant importance.For the optimization of the DDFT algorithm,based on the Sunway Bluelight II supercomputer and the unique hardware architecture of the SW39000 processor,this work proposes three acceleration strategies to enhance computational efficiency and performance,including direct parallel optimization,local-memory constrained optimization for CPEs,and multi-core groups collaboration and communication optimization.This method combines the characteristics of the program’s algorithm with the unique hardware architecture of the Sunway Bluelight II supercomputer,optimizing the storage and transmission structures to achieve a closer integration of software and hardware.For the first time,this paper presents Sunway-Dynamical Density Functional Theory(SW-DDFT).Experimental results show that SW-DDFT achieves a speedup of 6.67 times within a single-core group compared to the original DDFT implementation,with six core groups(a total of 384 CPEs),the maximum speedup can reach 28.64 times,and parallel efficiency can reach 71%,demonstrating excellent acceleration performance.
文摘Optimal impulse control and impulse games provide the cutting-edge frameworks for modeling systems where control actions occur at discrete time points,and optimizing objectives under discontinuous interventions.This review synthesizes the theoretical advancements,computational approaches,emerging challenges,and possible research directions in the field.Firstly,we briefly review the fundamental theory of continuous-time optimal control,including Pontryagin's maximum principle(PMP)and dynamic programming principle(DPP).Secondly,we present the foundational results in optimal impulse control,including necessary conditions and sufficient conditions.Thirdly,we systematize impulse game methodologies,from Nash equilibrium existence theory to the connection between Nash equilibrium and systems stability.Fourthly,we summarize the numerical algorithms including the intelligent computation approaches.Finally,we examine the new trends and challenges in theory and applications as well as computational considerations.
基金Project supported by the Education Department of Jilin Province,China(Grant No.JJKH20231291KJ)。
文摘We design dynamical Casimir arrays(DCA)consisting of giant atoms and coupled resonator waveguides(CRWs)to investigate the Einstein–Podolsky–Rosen(EPR)steering at finite temperatures.Our designed system exhibits an asymmetry in its structure,which is caused by the differences in the sizes and the coupling positions of the giant atoms.The system achieves different types of EPR steering and the reversal of one-way EPR steering by modulating parameters.Furthermore,the symmetry and asymmetry of the system structure,in their responses to parameter modulation,both reveal the asymmetry of EPR steering.In this process,we discover that with the increase in temperature,different types of steering can be transferred from Casimir photons to giant atoms.We also achieve the monogamy of the multipartite system.These results provide important assistance for secure quantum communication,and further intuitively validating the asymmetry of EPR steering from multiple perspectives.
基金supported by the National Natural Science Foundation of China under grant Nos.12103032,12025302,11773052 and 11761131016(NSFC-DFG)the“111”Project of the Ministry of Education of China under grant No.B20019+1 种基金the China Manned Space Project under grant No.CMS-CSST-2025-A11support from a Newton Advanced Fellowship awarded by the Royal Society and the Newton Fund。
文摘To address the disk-halo degeneracy problem,we investigate the nearby barred spiral galaxy NGC 1097.We construct mass models using 3.6 and 4.5μm near-infrared photometric images from the S^(4)G survey,constrained by rotation curves derived from CO(J=2–1)data from the PHANGS-ALMA survey.These models serve as inputs for a suite of hydrodynamic simulations,where we systematically test the influence of key parameters including the disk mass scaling factor(f_(M)),bar pattern speed(Ω_(b)),and gas sound speed(c_(s)).By comparing the CO(2–1)kinematic maps in the bar region with those from the simulations,we perform a standardχ^(2)analysis to identify the best-fit model.The best-fit model reproduces the observed morphological and kinematic gas features of the galaxy,indicating that NGC 1097 likely hosts a maximal disk with a slowly rotating bar.We also test the influence of a boxy/peanut-shaped(B/P)bulge by incorporating a double-peaked vertical density profile into the model.This B/P structure tends to weaken the bar’s non-axisymmetric potential and necessitate a higher bar pattern speed to reproduce the observed gas morphology.
基金supported by the National Natural Science Foundation of China(Nos.22273122,T2350009)the Guangdong Provincial Natural Science Foundation(No.2024A1515011504)computational resources and services provided by the national supercomputer center in Guangzhou.
文摘We investigate dynamical quantum phase transitions(DQPTs)in Marko-vian open quantum systems using a variational quantum simulation(VQS)algorithm based on quantum state diffusion(QSD).This approach reformulates the Lindblad master equation as an ensemble of pure-state trajectories,enabling efficient simula-tion of dissipative quantum dynam-ics with effectively reduced quantum resources.Focusing on the one-di-mensional transverse-field Ising mod-el(TFIM),we simulate quench dynamics under both local and global Lindblad dissipation.The QSD-VQS algorithm accurately captures the nonanalytic cusps in the Loschmidt rate function,and reveals their modulation by dissipation strength and system size.Notably,DQPTs are gradually suppressed under strong local dissipation,while they persist under strong global dissipation due to collective environmental effects.Benchmarking against exact Lindblad solutions confirms the high accuracy and scalability of our method.
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 by the National Natural Science Foundation of China(Grant Nos.12274472,12494594,12494591,and 92165204)National Key Research and Development Program of China(Grant No.2022YFA1402802)+2 种基金Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices(Grant No.2022B1212010008)Guangdong Fundamental Research Center for Magnetoelectric Physics(Grant No.2024B0303390001)Guangdong Provincial Quantum Science Strategic Initiative(Grant No.GDZX2401010)。
文摘We investigate the interplay between the pseudogap state and d-wave superconductivity in the two-dimensional doped Hubbard model by employing an eight-site cluster dynamical mean-field theory method.By tuning electron hopping parameters,the strong-coupling pseudogap in the two-dimensional Hubbard model can be either enhanced or suppressed in the doped Mott insulator regime.We find that in underdoped cases,the closing of pseudogap leads to a significant enhancement of superconductivity,indicating competition between the two in the underdoped regime.In contrast,at large dopings,suppressing the pseudogap is accompanied by a concurrent decrease in the superconducting transition temperature Tc,which can be attributed to a reduction in antiferromagnetic correlations behind both the pseudogap and superconductivity.We elucidate this evolving relationship between pseudogap and superconductivity across different doping regimes.
基金This work was partly funded by the National Key R&D Project of China(2021YFB3400704)China State Railway Group(K2022J004 and N2023J011)China Railway Chengdu Group(CJ23018).
文摘Purpose–The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system.This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice.The key principles and approacheswill be proposed,and their applications to high-speed trains in Chinawill be presented.Design/methodology/approach–First,the structural integrity and dynamical integrity of high-speed trains are defined,and their relationship is introduced.Then,the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided.Finally,the principles and approaches for assessing the dynamical integrity of highspeed trains are presented and a novel operational assessment method is further presented.Findings–Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system.For assessing the structural integrity of structural components,an open-loop analysis considering both normal and abnormal vehicle conditions is needed.For assessing the structural integrity of dynamical components,a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed.The analysis of vehicle system dynamics should follow the principles of complete objects,conditions and indices.Numerical,experimental and operational approaches should be combined to achieve effective assessments.Originality/value–The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects,better lifespan management of train components and better maintenance decision-making for high-speed trains.
基金supported by the National Natural Science Foundation of China(NSFC grants No.12172036,51774018)the Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT,IRT_17R06)+2 种基金the Russian Foundation for Basic Research,Grant Number 20‐55‐53032Russian State Task number 1021052706247‐7‐1.5.4the Government of Perm Krai,research project No.С‐26/628.
文摘Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments.In the past several decades,earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering,earthquake prediction,and the desire to use the mechanism of earthquake triggering to reduce,prevent,or trigger earthquakes.Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes.In the past several decades,some models have been developed,including static,dynamic,quasi‐static,and other models.Some reviews have been published,but explosiontriggered seismicity was not included.In recent years,some new results on earthquake triggering have emerged.Therefore,this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area.Instead of a complete review of the relevant literature,this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0606703)the National Natural Science Foundation of China(Grant No.41975116)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.Y202025)。
文摘The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.
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 jointly by the National Natural Science Foundation of China (Grant No.42075170)the National Key Research and Development Program of China (2022YFF0802503)+2 种基金the Jiangsu Collaborative Innovation Center for Climate Changea Chinese University Direct Grant(Grant No. 4053331)supported by the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulator Facility”(EarthLab)
文摘In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.
基金Supported by NSFC(Nos.11971236,11901419)the Foundation in Higher Education Institutions of Henan Province(No.23A110020)。
文摘We introduce and study the relation between Pesin-Pitskel topological pressure on an arbitrary subset and measure theoretic pressure of Borel probability measure for nonautonomous dynamical systems,which is an extension of the classical definition of Bowen topological entropy.We show that the Pesin-Pitskel topological pressure can be determined by the local pressures of measures in nonautonomous case and establish a variational principle for Pesin-Pitskel topological pressure on compact subsets in the context of nonautonomous dynamical systems.
基金co-supported by the National Natural Science Foundation of China(Nos.U223321251875014)+1 种基金the Beijing Natural Science Foundation,China(No.L221008)the China Scholarship Council(No.202106020001).
文摘Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management.However,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism.When the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression accurately.In addition,DT update algorithms are difficult to be integrated simultaneously by current methods.This paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism.The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating.Furthermore,the Independence Principle for the abnormal detection is proposed to refine the theory of DT.Events at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend.The interaction and collaboration between different loop models are also discussed.Finally,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed method.The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.
