Emergence refers to the existence or formation of collective behaviors in complex systems.Here,we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evol...Emergence refers to the existence or formation of collective behaviors in complex systems.Here,we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evolution of complex system.In this framework,the statistical ensemble composed of M microstates of a complex system with N agents is defined by the normalized N×M matrix A,whose columns represent microstates and order of row is consist with the time.The ensemble matrix A can be decomposed as■,where r=min(N,M),eigenvalueσIbehaves as the probability amplitude of the eigen microstate U_I so that■and U_I evolves following V_I.In a disorder complex system,there is no dominant eigenvalue and eigen microstate.When a probability amplitudeσIbecomes finite in the thermodynamic limit,there is a condensation of the eigen microstate UIin analogy to the Bose–Einstein condensation of Bose gases.This indicates the emergence of U_I and a phase transition in complex system.Our framework has been applied successfully to equilibrium threedimensional Ising model,climate system and stock markets.We anticipate that our eigen microstate method can be used to study non-equilibrium complex systems with unknown orderparameters,such as phase transitions of collective motion and tipping points in climate systems and ecosystems.展开更多
Living systems are full of astonishing diversity and complexity of life.Despite differences in the length scales and cognitive abilities of these systems,collective motion of large groups of individuals can emerge.It ...Living systems are full of astonishing diversity and complexity of life.Despite differences in the length scales and cognitive abilities of these systems,collective motion of large groups of individuals can emerge.It is of great importance to seek for the fundamental principles of collective motion,such as phase transitions and their natures.Via an eigen microstate approach,we have found a discontinuous transition of density and a continuous transition of velocity in the Vicsek models of collective motion,which are identified by the finite-size scaling form of order-parameter.At strong noise,living systems behave like gas.With the decrease of noise,the interactions between the particles of a living system become stronger and make them come closer.The living system experiences then a discontinuous gas-liquid like transition of density.The even stronger interactions at smaller noise make the velocity directions of the particles become ordered and there is a continuous phase transition of collective motion in addition.展开更多
Powdery mildew is a major disease of strawberry.It harms both plants and fruits,seriously affecting the quality and yield of strawberry.This article briefly introduces the harms and occurrence regularity of powdery mi...Powdery mildew is a major disease of strawberry.It harms both plants and fruits,seriously affecting the quality and yield of strawberry.This article briefly introduces the harms and occurrence regularity of powdery mildew in strawberry and summarizes the corresponding control measures,with a view to providing a certain scientific reference for the prevention and treatment of the disease.展开更多
The Earth’s climate system operates across multiple scales,driven by intricate interactions among natural processes and human activities.Understanding these dynamics is crucial for predicting future climate scenarios...The Earth’s climate system operates across multiple scales,driven by intricate interactions among natural processes and human activities.Understanding these dynamics is crucial for predicting future climate scenarios(days to decades)and their impacts on global environments and societies.These interactions span across atmospheric circulation,ocean currents,geological processes,and biological systems,influencing global climate variability and regional weather patterns[1].展开更多
The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback loops.This study employs a theoret...The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback loops.This study employs a theoretical framework and the Eigen Microstate(EM)approach of statistical physics to examine global surface temperature variations since 1948,as revealed by a global reanalysis.We identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates,and El Niño.Our analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades,highlighting the critical roles of hemispheric differences,land-sea contrasts,and tropical climate fluctuations in a warming world.Additionally,we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6)under three future climate scenarios to perform a comparative analysis of the changes in each EM contribution.The results indicate that under future warming scenarios,tropical climate fluctuations will become increasingly dominant,while traditional hemispheric and monsoonal patterns may decline.This shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based perspective.Our study provides a new perspective on understanding and addressing global climate change,enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.展开更多
Climate and physics are closely related. The governing equa- tions for both the atmosphere and ocean are the Navier-Stokes equations, which describe and quantify the physics of fluids. However, the atmosphere and ocea...Climate and physics are closely related. The governing equa- tions for both the atmosphere and ocean are the Navier-Stokes equations, which describe and quantify the physics of fluids. However, the atmosphere and ocean are very complex due to the interaction of many processes, not necessarily physi- cal, and due to the need to model processes that are smaller than the grid resolution. In spite of this complexity, physi- cists have successfully addressed a wide swath of it using ad- vanced statistical physics methods and techniques. Climate science has been benefited from the physics discipline and vice versa where the ＂chaos＂ theory is an excellent example for the interdisciplinary approach as it was basically discov- ered by Lorenz [ 1 ] through his simple model of the atmos- phere.展开更多
Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques.Results reveal that different phase transitions belonging to the same universality class can be identifi...Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques.Results reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different NNs.Based on this finding,we proposed the universality class of machine learning for critical phenomena.Furthermore,we investigated and discussed the NNs of different universality classes.Our research contributes to machine learning by relating the NNs with the universality class.展开更多
基金supported by the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.QYZD-SSW-SYS019)。
文摘Emergence refers to the existence or formation of collective behaviors in complex systems.Here,we develop a theoretical framework based on the eigen microstate theory to analyze the emerging phenomena and dynamic evolution of complex system.In this framework,the statistical ensemble composed of M microstates of a complex system with N agents is defined by the normalized N×M matrix A,whose columns represent microstates and order of row is consist with the time.The ensemble matrix A can be decomposed as■,where r=min(N,M),eigenvalueσIbehaves as the probability amplitude of the eigen microstate U_I so that■and U_I evolves following V_I.In a disorder complex system,there is no dominant eigenvalue and eigen microstate.When a probability amplitudeσIbecomes finite in the thermodynamic limit,there is a condensation of the eigen microstate UIin analogy to the Bose–Einstein condensation of Bose gases.This indicates the emergence of U_I and a phase transition in complex system.Our framework has been applied successfully to equilibrium threedimensional Ising model,climate system and stock markets.We anticipate that our eigen microstate method can be used to study non-equilibrium complex systems with unknown orderparameters,such as phase transitions of collective motion and tipping points in climate systems and ecosystems.
基金Project supported by the Fundamental Research Funds for the Central Universities,China(Grant No.2019XD-A10)the National Natural Science Foundation of China(Grant No.71731002)。
文摘Living systems are full of astonishing diversity and complexity of life.Despite differences in the length scales and cognitive abilities of these systems,collective motion of large groups of individuals can emerge.It is of great importance to seek for the fundamental principles of collective motion,such as phase transitions and their natures.Via an eigen microstate approach,we have found a discontinuous transition of density and a continuous transition of velocity in the Vicsek models of collective motion,which are identified by the finite-size scaling form of order-parameter.At strong noise,living systems behave like gas.With the decrease of noise,the interactions between the particles of a living system become stronger and make them come closer.The living system experiences then a discontinuous gas-liquid like transition of density.The even stronger interactions at smaller noise make the velocity directions of the particles become ordered and there is a continuous phase transition of collective motion in addition.
基金Natural Science Foundation of Hebei Province(C2018301047)Foundation for High-level Talents in Hebei Province(A201802016)+3 种基金Scientific and Technological Research and Development Plan Project of Hebei Province(16226313D-4)Innovation Project of Hebei Academy of Agriculture and Forestry Sciences(C19C0701-03)Innovative Team Building Project of Hebei Academy of Agriculture and Forestry Sciences(F20E06001-2)Youth Foundation of Hebei Academy of Agriculture and Forestry Sciences(2018100103).
文摘Powdery mildew is a major disease of strawberry.It harms both plants and fruits,seriously affecting the quality and yield of strawberry.This article briefly introduces the harms and occurrence regularity of powdery mildew in strawberry and summarizes the corresponding control measures,with a view to providing a certain scientific reference for the prevention and treatment of the disease.
基金supported by the National Natural Science Foundation of China(12275020,12135003,and 12205025)the National Key Research and Development Program of China(2023YFE0109000)the Fundamental Research Funds for the Central Universities。
文摘The Earth’s climate system operates across multiple scales,driven by intricate interactions among natural processes and human activities.Understanding these dynamics is crucial for predicting future climate scenarios(days to decades)and their impacts on global environments and societies.These interactions span across atmospheric circulation,ocean currents,geological processes,and biological systems,influencing global climate variability and regional weather patterns[1].
基金supported by the National Natural Science Foundation of China(Grant Nos.42450183,12275020,12135003,12205025,and42461144209)the National Key Research and Development Program of China(Grant No.2023YFE0109000)supported by the Fundamental Research Funds for the Central Universities。
文摘The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback loops.This study employs a theoretical framework and the Eigen Microstate(EM)approach of statistical physics to examine global surface temperature variations since 1948,as revealed by a global reanalysis.We identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates,and El Niño.Our analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades,highlighting the critical roles of hemispheric differences,land-sea contrasts,and tropical climate fluctuations in a warming world.Additionally,we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6)under three future climate scenarios to perform a comparative analysis of the changes in each EM contribution.The results indicate that under future warming scenarios,tropical climate fluctuations will become increasingly dominant,while traditional hemispheric and monsoonal patterns may decline.This shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based perspective.Our study provides a new perspective on understanding and addressing global climate change,enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.
基金supported by the MULTIPLEX EU Project(Grant No. 317532)the Israel Science Foundation,ONR and DTRA+1 种基金the National Natural Science Foundation of China(Grant No.1121403)the fellowship program funded by the Planning and Budgeting Committee of the Council for Higher Education of Israel
文摘Climate and physics are closely related. The governing equa- tions for both the atmosphere and ocean are the Navier-Stokes equations, which describe and quantify the physics of fluids. However, the atmosphere and ocean are very complex due to the interaction of many processes, not necessarily physi- cal, and due to the need to model processes that are smaller than the grid resolution. In spite of this complexity, physi- cists have successfully addressed a wide swath of it using ad- vanced statistical physics methods and techniques. Climate science has been benefited from the physics discipline and vice versa where the ＂chaos＂ theory is an excellent example for the interdisciplinary approach as it was basically discov- ered by Lorenz [ 1 ] through his simple model of the atmos- phere.
基金supported by the National Natural Science Foundation of China(Grant Nos.12135003,and 12275020)。
文摘Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning techniques.Results reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different NNs.Based on this finding,we proposed the universality class of machine learning for critical phenomena.Furthermore,we investigated and discussed the NNs of different universality classes.Our research contributes to machine learning by relating the NNs with the universality class.
