Complexity in Dynamical Systems
Moore, Cristopher David
The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.
Managing Complex Dynamical Systems
Cox, John C.; Webster, Robert L.; Curry, Jeanie A.; Hammond, Kevin L.
2011-01-01
Management commonly engages in a variety of research designed to provide insight into the motivation and relationships of individuals, departments, organizations, etc. This paper demonstrates how the application of concepts associated with the analysis of complex systems applied to such data sets can yield enhanced insights for managerial action.
Management of complex dynamical systems
MacKay, R. S.
2018-02-01
Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.
Combinations of complex dynamical systems
Pilgrim, Kevin M
2003-01-01
This work is a research-level monograph whose goal is to develop a general combination, decomposition, and structure theory for branched coverings of the two-sphere to itself, regarded as the combinatorial and topological objects which arise in the classification of certain holomorphic dynamical systems on the Riemann sphere. It is intended for researchers interested in the classification of those complex one-dimensional dynamical systems which are in some loose sense tame. The program is motivated by the dictionary between the theories of iterated rational maps and Kleinian groups.
Dynamics of complex quantum systems
Akulin, Vladimir M
2014-01-01
This book gathers together a range of similar problems that can be encountered in different fields of modern quantum physics and that have common features with regard to multilevel quantum systems. The main motivation was to examine from a uniform standpoint various models and approaches that have been developed in atomic, molecular, condensed matter, chemical, laser and nuclear physics in various contexts. The book should help senior-level undergraduate, graduate students and researchers putting particular problems in these fields into a broader scientific context and thereby taking advantage of well-established techniques used in adjacent fields. This second edition has been expanded to include substantial new material (e.g. new sections on Dynamic Localization and on Euclidean Random Matrices and new chapters on Entanglement, Open Quantum Systems, and Coherence Protection). It is based on the author’s lectures at the Moscow Institute of Physics and Technology, at the CNRS Aimé Cotton Laboratory, and on ...
The Self as a Complex Dynamic System
Mercer, Sarah
2011-01-01
This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…
Complex and adaptive dynamical systems a primer
Gros, Claudius
2007-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Complex and Adaptive Dynamical Systems A Primer
Gros, Claudius
2011-01-01
We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...
Design tools for complex dynamic security systems.
Energy Technology Data Exchange (ETDEWEB)
Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III (.; ); Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.
2007-01-01
The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.
Controlling Complex Systems and Developing Dynamic Technology
Avizienis, Audrius Victor
In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit
System crash as dynamics of complex networks.
Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim
2016-10-18
Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.
The self as a complex dynamic system
Directory of Open Access Journals (Sweden)
Sarah Mercer
2011-04-01
Full Text Available This article explores the potential offered by complexity theories for understanding language learners’ sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual perspective that may inform future studies into the self and possibly other individual learner differences. The article concludes by critically considering the merits of a complexity perspective but also reflecting on the challenges it poses for research.
Complex and adaptive dynamical systems a primer
Gros, Claudius
2013-01-01
Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...
Modular interdependency in complex dynamical systems.
Watson, Richard A; Pollack, Jordan B
2005-01-01
Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability.
Automated design of complex dynamic systems.
Directory of Open Access Journals (Sweden)
Michiel Hermans
Full Text Available Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems.
Nonlinear Dynamics, Chaotic and Complex Systems
Infeld, E.; Zelazny, R.; Galkowski, A.
2011-04-01
Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet
Complex and adaptive dynamical systems a primer
Gros, Claudius
2015-01-01
This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...
Imura, Jun-ichi; Ueta, Tetsushi
2015-01-01
This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.
System dynamics in complex psychiatric treatment organizations.
Rosenheck, R
1988-05-01
One of the major challenges facing contemporary psychiatry is the coordination of diverse services through organizational integration. With increasing frequency, psychiatric treatment takes place in complex treatment systems composed of multiple inpatient and outpatient programs. Particularly in public health care systems serving the chronically ill, contemporary practice demands a broad spectrum of programs, often geographically dispersed, that include crisis intervention teams, day treatment programs, substance abuse units, social rehabilitation programs and halfway houses (Bachrach 1983; Turner and TenHoor 1978). Individualized treatment planning often requires that a particular patient participate in two or more specialized programs either simultaneously or in a specified sequence. As a consequence of this specialization, treatment fragmentation has emerged as a significant clinical problem, and continuity of care has been highlighted as a valuable but elusive ingredient of optimal treatment. This paper will describe the dynamic interactions that result when several such programs are united under a common organizational roof. Using a large VA Psychiatry Service as an example, I will outline the hierarchical structure characteristic of such an organization, as well as the persistent pulls toward both integration and fragmentation that influence its operation.
Nonlinear and Complex Dynamics in Real Systems
William Barnett; Apostolos Serletis; Demitre Serletis
2005-01-01
This paper was produced for the El-Naschie Symposium on Nonlinear Dynamics in Shanghai in December 2005. In this paper we provide a review of the literature with respect to fluctuations in real systems and chaos. In doing so, we contrast the order and organization hypothesis of real systems with nonlinear chaotic dynamics and discuss some techniques used in distinguishing between stochastic and deterministic behavior. Moreover, we look at the issue of where and when the ideas of chaos could p...
Dynamical systems examples of complex behaviour
Jost, Jürgen
2005-01-01
Our aim is to introduce, explain, and discuss the fundamental problems, ideas, concepts, results, and methods of the theory of dynamical systems and to show how they can be used in speci?c examples. We do not intend to give a comprehensive overview of the present state of research in the theory of dynamical systems, nor a detailed historical account of its development. We try to explain the important results, often neglecting technical re?nements 1 and, usually, we do not provide proofs. One of the basic questions in studying dynamical systems, i.e. systems that evolve in time, is the construction of invariants that allow us to classify qualitative types of dynamical evolution, to distinguish between qualitatively di?erent dynamics, and to studytransitions between di?erent types. Itis also important to ?nd out when a certain dynamic behavior is stable under small perturbations, as well as to understand the various scenarios of instability. Finally, an essential aspect of a dynamic evolution is the transformat...
Advances in dynamic network modeling in complex transportation systems
Ukkusuri, Satish V
2013-01-01
This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.
Applications of Nonlinear Dynamics Model and Design of Complex Systems
In, Visarath; Palacios, Antonio
2009-01-01
This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.
Complex, Dynamic Systems: A New Transdisciplinary Theme for Applied Linguistics?
Larsen-Freeman, Diane
2012-01-01
In this plenary address, I suggest that Complexity Theory has the potential to contribute a transdisciplinary theme to applied linguistics. Transdisciplinary themes supersede disciplines and spur new kinds of creative activity (Halliday 2001 [1990]). Investigating complex systems requires researchers to pay attention to system dynamics. Since…
Complex systems and networks dynamics, controls and applications
Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu
2016-01-01
This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...
Understanding Learner Agency as a Complex Dynamic System
Mercer, Sarah
2011-01-01
This paper attempts to contribute to a fuller understanding of the nature of language learner agency by considering it as a complex dynamic system. The purpose of the study was to explore detailed situated data to examine to what extent it is feasible to view learner agency through the lens of complexity theory. Data were generated through a…
Note on transmitted complexity for quantum dynamical systems
Watanabe, Noboru; Muto, Masahiro
2017-10-01
Transmitted complexity (mutual entropy) is one of the important measures for quantum information theory developed recently in several ways. We will review the fundamental concepts of the Kossakowski, Ohya and Watanabe entropy and define a transmitted complexity for quantum dynamical systems. This article is part of the themed issue `Second quantum revolution: foundational questions'.
Synchronization in Complex Networks of Nonlinear Dynamical Systems
Wu, Chai Wah
2007-01-01
This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ide
Effective control of complex turbulent dynamical systems through statistical functionals.
Majda, Andrew J; Qi, Di
2017-05-30
Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.
Complex systems dynamics in aging: new evidence, continuing questions.
Cohen, Alan A
2016-02-01
There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.
An introduction to complex systems society, ecology, and nonlinear dynamics
Fieguth, Paul
2017-01-01
This undergraduate text explores a variety of large-scale phenomena - global warming, ice ages, water, poverty - and uses these case studies as a motivation to explore nonlinear dynamics, power-law statistics, and complex systems. Although the detailed mathematical descriptions of these topics can be challenging, the consequences of a system being nonlinear, power-law, or complex are in fact quite accessible. This book blends a tutorial approach to the mathematical aspects of complex systems together with a complementary narrative on the global/ecological/societal implications of such systems. Nearly all engineering undergraduate courses focus on mathematics and systems which are small scale, linear, and Gaussian. Unfortunately there is not a single large-scale ecological or social phenomenon that is scalar, linear, and Gaussian. This book offers students insights to better understand the large-scale problems facing the world and to realize that these cannot be solved by a single, narrow academic field or per...
Complexity: Outline of the NWO strategic theme Dynamics of complex systems
Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; van der Maas, H.; Mulder, B.; Stam, K.; van Steen, M.; Zandee, L.
2008-01-01
Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide
Complexity : outline of the NWO strategic theme dynamics of complex systems
Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; Maas, van der H.; Mulder, B.; Stam, K.; Steen, van M.; Zandee, L.
2008-01-01
Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide
Modularity and the spread of perturbations in complex dynamical systems.
Kolchinsky, Artemy; Gates, Alexander J; Rocha, Luis M
2015-12-01
We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.
Introduction to turbulent dynamical systems in complex systems
Majda, Andrew J
2016-01-01
This volume is a research expository article on the applied mathematics of turbulent dynamical systems through the paradigm of modern applied mathematics. It involves the blending of rigorous mathematical theory, qualitative and quantitative modeling, and novel numerical procedures driven by the goal of understanding physical phenomena which are of central importance to the field. The contents cover general framework, concrete examples, and instructive qualitative models. Accessible open problems are mentioned throughout. Topics covered include: · Geophysical flows with rotation, topography, deterministic and random forcing · New statistical energy principles for general turbulent dynamical systems, with applications · Linear statistical response theory combined with information theory to cope with model errors · Reduced low order models · Recent mathematical strategies for online data assimilation of turbulent dynamical systems as well as rigorous results for finite ensemble Kalman filters The volume wi...
Dynamics of a Simple Quantum System in a Complex Environment
Bulgac, A; Kusnezov, D; Bulgac, Aurel; Dang, Gui Do; Kusnezov, Dimitri
1998-01-01
We present a theory for the dynamical evolution of a quantum system coupled to a complex many-body intrinsic system/environment. By modelling the intrinsic many-body system with parametric random matrices, we study the types of effective stochastic models which emerge from random matrix theory. Using the Feynman-Vernon path integral formalism, we derive the influence functional and obtain either analytical or numerical solutions for the time evolution of the entire quantum system. We discuss thoroughly the structure of the solutions for some representative cases and make connections to well known limiting results, particularly to Brownian motion, Kramers classical limit and the Caldeira-Leggett approach.
Micro-Level Affect Dynamics in Psychopathology Viewed From Complex Dynamical System Theory
Wichers, M.; Wigman, J. T. W.; Myin-Germeys, I.
2015-01-01
This article discusses the role of moment-to-moment affect dynamics in mental disorder and aims to integrate recent literature on this topic in the context of complex dynamical system theory. First, we will review the relevance of temporal and contextual aspects of affect dynamics in relation to
Henry, Alastair
2016-01-01
Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…
Kinetics of the Dynamical Information Shannon Entropy for Complex Systems
International Nuclear Information System (INIS)
Yulmetyev, R.M.; Yulmetyeva, D.G.
1999-01-01
Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physical systems with non-Markovian property and memory in correlation approximation, and biological and physiological systems with sequences of the Markovian and non-Markovian random noises. For the stochastic processes, a description of the information entropy in terms of normalized time correlation functions is given. The influence and important role of two mutually dependent channels of the entropy change, correlation (creation or generation of correlations) and anti-correlation (decay or annihilation of correlation) is discussed. The method developed here is also used in analysis of the density fluctuations in liquid cesium obtained from slow neutron scattering data, fractal kinetics of the long-range fluctuation in the short-time human memory and chaotic dynamics of R-R intervals of human ECG. (author)
Control of complex dynamics and chaos in distributed parameter systems
Energy Technology Data Exchange (ETDEWEB)
Chakravarti, S.; Marek, M.; Ray, W.H. [Univ. of Wisconsin, Madison, WI (United States)
1995-12-31
This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in the complex quasi-periodic or chaotic spatiotemporal patterns.
Young Children's Knowledge About the Moon: A Complex Dynamic System
Venville, Grady J.; Louisell, Robert D.; Wilhelm, Jennifer A.
2012-08-01
The purpose of this research was to use a multidimensional theoretical framework to examine young children's knowledge about the Moon. The research was conducted in the interpretive paradigm and the design was a multiple case study of ten children between the ages of three and eight from the USA and Australia. A detailed, semi-structured interview was conducted with each child. In addition, each child's parents were interviewed to determine possible social and cultural influences on the child's knowledge. We sought evidence about how the social and cultural experiences of the children might have influenced the development of their ideas. From a cognitive perspective we were interested in whether the children's ideas were constructed in a theory like form or whether the knowledge was the result of gradual accumulation of fragments of isolated cultural information. Findings reflected the strong and complex relationship between individual children, their social and cultural milieu, and the way they construct ideas about the Moon and astronomy. Findings are presented around four themes including ontology, creatures and artefacts, animism, and permanence. The findings support a complex dynamic system view of students' knowledge that integrates the framework theory perspective and the knowledge in fragments perspective. An initial model of a complex dynamic system of young children's knowledge about the Moon is presented.
Complex analysis and dynamical systems new trends and open problems
Golberg, Anatoly; Jacobzon, Fiana; Shoikhet, David; Zalcman, Lawrence
2018-01-01
This book focuses on developments in complex dynamical systems and geometric function theory over the past decade, showing strong links with other areas of mathematics and the natural sciences. Traditional methods and approaches surface in physics and in the life and engineering sciences with increasing frequency – the Schramm‐Loewner evolution, Laplacian growth, and quadratic differentials are just a few typical examples. This book provides a representative overview of these processes and collects open problems in the various areas, while at the same time showing where and how each particular topic evolves. This volume is dedicated to the memory of Alexander Vasiliev.
Equation-free model reduction for complex dynamical systems
International Nuclear Information System (INIS)
Le Maitre, O. P.; Mathelin, L.; Le Maitre, O. P.
2010-01-01
This paper presents a reduced model strategy for simulation of complex physical systems. A classical reduced basis is first constructed relying on proper orthogonal decomposition of the system. Then, unlike the alternative approaches, such as Galerkin projection schemes for instance, an equation-free reduced model is constructed. It consists in the determination of an explicit transformation, or mapping, for the evolution over a coarse time-step of the projection coefficients of the system state on the reduced basis. The mapping is expressed as an explicit polynomial transformation of the projection coefficients and is computed once and for all in a pre-processing stage using the detailed model equation of the system. The reduced system can then be advanced in time by successive applications of the mapping. The CPU cost of the method lies essentially in the mapping approximation which is performed offline, in a parallel fashion, and only once. Subsequent application of the mapping to perform a time-integration is carried out at a low cost thanks to its explicit character. Application of the method is considered for the 2-D flow around a circular cylinder. We investigate the effectiveness of the reduced model in rendering the dynamics for both asymptotic state and transient stages. It is shown that the method leads to a stable and accurate time-integration for only a fraction of the cost of a detailed simulation, provided that the mapping is properly approximated and the reduced basis remains relevant for the dynamics investigated. (authors)
Complex dynamics in Josephson system with two external forcing terms
International Nuclear Information System (INIS)
Yang Jianping; Feng Wei; Jing Zhujun
2006-01-01
Josephson system with two external forcing terms is investigated. By applying Melnikov method, we prove that criterion of existence of chaos under periodic perturbation. By second-order averaging method and Melnikov method, we obtain the criterion of existence of chaos in averaged system under quasi-periodic perturbation for ω 2 =ω 1 +εν, and cannot prove the criterion of existence of chaos in averaged system under quasi-periodic perturbation for ω 2 =nω 1 +εν (n>=2 and n-bar N), where ν is not rational to ω 1 . We also study the effects of the parameters of system on dynamical behaviors by using numerical simulation. The numerical simulations, including bifurcation diagram of fixed points, bifurcation diagram of system in three- and two-dimensional space, homoclinic and heteroclinic bifurcation surface, Maximum Lyapunov exponent, phase portraits, Poincare map, are also plotted to illustrate theoretical analysis, and to expose the complex dynamical behaviors, including the period-n (n=1,2,5,7) orbits in different chaotic regions, cascades of period-doubling bifurcation from period-1, 2 and 5 orbits, reverse period-doubling bifurcation, onset of chaos which occurs more than once for two given external frequencies and chaos suddenly converting to periodic orbits, transient chaos with complex periodic windows and crisis, reverse period-5 bubble, non-attracting chaotic set and nice attracting chaotic set. In particular, we observe that the system can leave chaotic region to periodic motion by adjusting damping α, amplitude f 1 and frequency ω 2 of external forcing which can be considered as a control strategy
Complex dynamics in Duffing system with two external forcings
International Nuclear Information System (INIS)
Jing Zhujun; Wang Ruiqi
2005-01-01
Duffing's equation with two external forcing terms have been discussed. The threshold values of chaotic motion under the periodic and quasi-periodic perturbations are obtained by using second-order averaging method and Melnikov's method. Numerical simulations not only show the consistence with the theoretical analysis but also exhibit the interesting bifurcation diagrams and the more new complex dynamical behaviors, including period-n (n=2,3,6,8) orbits, cascades of period-doubling and reverse period doubling bifurcations, quasi-periodic orbit, period windows, bubble from period-one to period-two, onset of chaos, hopping behavior of chaos, transient chaos, chaotic attractors and strange non-chaotic attractor, crisis which depends on the frequencies, amplitudes and damping. In particular, the second frequency plays a very important role for dynamics of the system, and the system can leave chaotic region to periodic motions by adjusting some parameter which can be considered as an control strategy of chaos. The computation of Lyapunov exponents confirm the dynamical behaviors
Neonatal Feeding Behavior as a Complex Dynamical System.
Goldfield, Eugene C; Perez, Jennifer; Engstler, Katherine
2017-04-01
The requirements of evidence-based practice in 2017 are motivating new theoretical foundations and methodological tools for characterizing neonatal feeding behavior. Toward that end, this article offers a complex dynamical systems perspective. A set of critical concepts from this perspective frames challenges faced by speech-language pathologists and allied professionals: when to initiate oral feeds, how to determine the robustness of neonatal breathing during feeding and appropriate levels of respiratory support, what instrumental assessments of swallow function to use with preterm neonates, and whether or not to introduce thickened liquids. In the near future, we can expect vast amounts of new data to guide evidence-based practice. But unless practitioners are able to frame these issues in a systems context larger than the individual child, the availability of "big data" will not be effectively translated to clinical practice. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Emergence of dynamical order synchronization phenomena in complex systems
Manrubia, Susanna C; Zanette, Damián H
2004-01-01
Synchronization processes bring about dynamical order and lead tospontaneous development of structural organization in complex systemsof various origins, from chemical oscillators and biological cells tohuman societies and the brain. This book provides a review and adetailed theoretical analysis of synchronization phenomena in complexsystems with different architectures, composed of elements withperiodic or chaotic individual dynamics. Special attention is paid tostatistical concepts, such as nonequilibrium phase transitions, orderparameters and dynamical glasses.
Integrated health management and control of complex dynamical systems
Tolani, Devendra K.
2005-11-01
A comprehensive control and health management strategy for human-engineered complex dynamical systems is formulated for achieving high performance and reliability over a wide range of operation. Results from diverse research areas such as Probabilistic Robust Control (PRC), Damage Mitigating/Life Extending Control (DMC), Discrete Event Supervisory (DES) Control, Symbolic Time Series Analysis (STSA) and Health and Usage Monitoring System (HUMS) have been employed to achieve this goal. Continuous-domain control modules at the lower level are synthesized by PRC and DMC theories, whereas the upper-level supervision is based on DES control theory. In the PRC approach, by allowing different levels of risk under different flight conditions, the control system can achieve the desired trade off between stability robustness and nominal performance. In the DMC approach, component damage is incorporated in the control law to reduce the damage rate for enhanced structural durability. The DES controller monitors the system performance and, based on the mission requirements (e.g., performance metrics and level of damage mitigation), switches among various lower-level controllers. The core idea is to design a framework where the DES controller at the upper-level, mimics human intelligence and makes appropriate decisions to satisfy mission requirements, enhance system performance and structural durability. Recently developed tools in STSA have been used for anomaly detection and failure prognosis. The DMC deals with the usage monitoring or operational control part of health management, where as the issue of health monitoring is addressed by the anomaly detection tools. The proposed decision and control architecture has been validated on two test-beds, simulating the operations of rotorcraft dynamics and aircraft propulsion.
Carleson, Lennart
1993-01-01
Complex dynamics is today very much a focus of interest. Though several fine expository articles were available, by P. Blanchard and by M. Yu. Lyubich in particular, until recently there was no single source where students could find the material with proofs. For anyone in our position, gathering and organizing the material required a great deal of work going through preprints and papers and in some cases even finding a proof. We hope that the results of our efforts will be of help to others who plan to learn about complex dynamics and perhaps even lecture. Meanwhile books in the field a. re beginning to appear. The Stony Brook course notes of J. Milnor were particularly welcome and useful. Still we hope that our special emphasis on the analytic side will satisfy a need. This book is a revised and expanded version of notes based on lectures of the first author at UCLA over several \\Vinter Quarters, particularly 1986 and 1990. We owe Chris Bishop a great deal of gratitude for supervising the production of cour...
Quantum Dynamical Behaviour in Complex Systems - A Semiclassical Approach
Energy Technology Data Exchange (ETDEWEB)
Ananth, Nandini [Univ. of California, Berkeley, CA (United States)
2008-01-01
One of the biggest challenges in Chemical Dynamics is describing the behavior of complex systems accurately. Classical MD simulations have evolved to a point where calculations involving thousands of atoms are routinely carried out. Capturing coherence, tunneling and other such quantum effects for these systems, however, has proven considerably harder. Semiclassical methods such as the Initial Value Representation (SC-IVR) provide a practical way to include quantum effects while still utilizing only classical trajectory information. For smaller systems, this method has been proven to be most effective, encouraging the hope that it can be extended to deal with a large number of degrees of freedom. Several variations upon the original idea of the SCIVR have been developed to help make these larger calculations more tractable; these range from the simplest, classical limit form, the Linearized IVR (LSC-IVR) to the quantum limit form, the Exact Forward-Backward version (EFB-IVR). In this thesis a method to tune between these limits is described which allows us to choose exactly which degrees of freedom we wish to treat in a more quantum mechanical fashion and to what extent. This formulation is called the Tuning IVR (TIVR). We further describe methodology being developed to evaluate the prefactor term that appears in the IVR formalism. The regular prefactor is composed of the Monodromy matrices (jacobians of the transformation from initial to finial coordinates and momenta) which are time evolved using the Hessian. Standard MD simulations require the potential surfaces and their gradients, but very rarely is there any information on the second derivative. We would like to be able to carry out the SC-IVR calculation without this information too. With this in mind a finite difference scheme to obtain the Hessian on-the-fly is proposed. Wealso apply the IVR formalism to a few problems of current interest. A method to obtain energy eigenvalues accurately for complex
Self-organization of complex networks as a dynamical system.
Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio
2015-01-01
To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.
Complex systems approach to fire dynamics and climate change impacts
Pueyo, S.
2012-04-01
I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire
Optimal interdependence enhances the dynamical robustness of complex systems
Singh, Rishu Kumar; Sinha, Sitabhra
2017-08-01
Although interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more likely to survive over long times. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the global dynamics comprising disjoint sets ("islands") of stable activity.
Complexity and Dynamical Depth
Directory of Open Access Journals (Sweden)
Terrence Deacon
2014-07-01
Full Text Available We argue that a critical difference distinguishing machines from organisms and computers from brains is not complexity in a structural sense, but a difference in dynamical organization that is not well accounted for by current complexity measures. We propose a measure of the complexity of a system that is largely orthogonal to computational, information theoretic, or thermodynamic conceptions of structural complexity. What we call a system’s dynamical depth is a separate dimension of system complexity that measures the degree to which it exhibits discrete levels of nonlinear dynamical organization in which successive levels are distinguished by local entropy reduction and constraint generation. A system with greater dynamical depth than another consists of a greater number of such nested dynamical levels. Thus, a mechanical or linear thermodynamic system has less dynamical depth than an inorganic self-organized system, which has less dynamical depth than a living system. Including an assessment of dynamical depth can provide a more precise and systematic account of the fundamental difference between inorganic systems (low dynamical depth and living systems (high dynamical depth, irrespective of the number of their parts and the causal relations between them.
Classification of time series patterns from complex dynamic systems
Energy Technology Data Exchange (ETDEWEB)
Schryver, J.C.; Rao, N.
1998-07-01
An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.
Optimizing Technology-Oriented Constructional Paramour's of complex dynamic systems
International Nuclear Information System (INIS)
Novak, S.M.
1998-01-01
Creating optimal vibro systems requires sequential solving of a few problems: selecting the basic pattern of dynamic actions, synthesizing the dynamic active systems, optimizing technological, technical, economic and design parameters. This approach is illustrated by an example of a high-efficiency vibro system synthesized for forming building structure components. When using only one single source to excite oscillations, resonance oscillations are imparted to the product to be formed in the horizontal and vertical planes. In order to obtain versatile and dynamically optimized parameters, a factor is introduced into the differential equations of the motion, accounting for the relationship between the parameters, which determine the frequency characteristics of the system and the parameter variation range. This results in obtaining non-sophisticated mathematical models of the system under investigation, convenient for optimization and for engineering design and calculations as well
Foundations of Complex Systems Nonlinear Dynamics, Statistical Physics, and Prediction
Nicolis, Gregoire
2007-01-01
Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, h
Nonlinear dynamics and complexity
Luo, Albert; Fu, Xilin
2014-01-01
This important collection presents recent advances in nonlinear dynamics including analytical solutions, chaos in Hamiltonian systems, time-delay, uncertainty, and bio-network dynamics. Nonlinear Dynamics and Complexity equips readers to appreciate this increasingly main-stream approach to understanding complex phenomena in nonlinear systems as they are examined in a broad array of disciplines. The book facilitates a better understanding of the mechanisms and phenomena in nonlinear dynamics and develops the corresponding mathematical theory to apply nonlinear design to practical engineering.
Stochastic dynamics of complex systems: from glasses to evolution (series on complexity science)
Sibani, Paolo
2013-01-01
Dynamical evolution over long time scales is a prominent feature of all the systems we intuitively think of as complex - for example, ecosystems, the brain or the economy. In physics, the term ageing is used for this type of slow change, occurring over time scales much longer than the patience, or indeed the lifetime, of the observer. The main focus of this book is on the stochastic processes which cause ageing, and the surprising fact that the ageing dynamics of systems which are very different at the microscopic level can be treated in similar ways. The first part of this book provides the necessary mathematical and computational tools and the second part describes the intuition needed to deal with these systems. Some of the first few chapters have been covered in several other books, but the emphasis and selection of the topics reflect both the authors' interests and the overall theme of the book. The second part contains an introduction to the scientific literature and deals in some detail with the desc...
RG-Whitham dynamics and complex Hamiltonian systems
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A. Gorsky
2015-06-01
Full Text Available Inspired by the Seiberg–Witten exact solution, we consider some aspects of the Hamiltonian dynamics with the complexified phase space focusing at the renormalization group (RG-like Whitham behavior. We show that at the Argyres–Douglas (AD point the number of degrees of freedom in Hamiltonian system effectively reduces and argue that anomalous dimensions at AD point coincide with the Berry indexes in classical mechanics. In the framework of Whitham dynamics AD point turns out to be a fixed point. We demonstrate that recently discovered Dunne–Ünsal relation in quantum mechanics relevant for the exact quantization condition exactly coincides with the Whitham equation of motion in the Ω-deformed theory.
Thermodynamic aspects of information transfer in complex dynamical systems
Cafaro, Carlo; Ali, Sean Alan; Giffin, Adom
2016-02-01
From the Horowitz-Esposito stochastic thermodynamical description of information flows in dynamical systems [J. M. Horowitz and M. Esposito, Phys. Rev. X 4, 031015 (2014), 10.1103/PhysRevX.4.031015], it is known that while the second law of thermodynamics is satisfied by a joint system, the entropic balance for the subsystems is adjusted by a term related to the mutual information exchange rate between the two subsystems. In this article, we present a quantitative discussion of the conceptual link between the Horowitz-Esposito analysis and the Liang-Kleeman work on information transfer between dynamical system components [X. S. Liang and R. Kleeman, Phys. Rev. Lett. 95, 244101 (2005), 10.1103/PhysRevLett.95.244101]. In particular, the entropic balance arguments employed in the two approaches are compared. Notwithstanding all differences between the two formalisms, our work strengthens the Liang-Kleeman heuristic balance reasoning by showing its formal analogy with the recent Horowitz-Esposito thermodynamic balance arguments.
On modulated complex non-linear dynamical systems
International Nuclear Information System (INIS)
Mahmoud, G.M.; Mohamed, A.A.; Rauh, A.
1999-01-01
This paper is concerned with the development of an approximate analytical method to investigate periodic solutions and their stability in the case of modulated non-linear dynamical systems whose equation of motion is describe. Such differential equations appear, for example, in problems of colliding particle beams in high-energy accelerators or one-mass systems with two or more degrees of freedom, e.g. rotors. The significance of periodic solutions lies on the fact that all non-periodic responses, if convergent, would approach to periodic solutions at the steady-state conditions. The example shows a good agreement between numerical and analytical results for small values of ε. The effect of the periodic modulation on the stability of the 2π-periodic solutions is discussed
[Origination of Pareto distribution in complex dynamic systems].
Chernavskiĭ, D S; Nikitin, A P; Chernavskaia, O D
2008-01-01
The Pareto distribution, whose probability density function can be approximated at sufficiently great chi as rho(chi) - chi(-alpha), where alpha > or = 2, is of crucial importance from both the theoretical and practical point of view. The main reason is its qualitative distinction from the normal (Gaussian) distribution. Namely, the probability of high deviations appears to be significantly higher. The conception of the universal applicability of the Gauss law remains to be widely distributed despite the lack of objective confirmation of this notion in a variety of application areas. The origin of the Pareto distribution in dynamic systems located in the gaussian noise field is considered. A simple one-dimensional model is discussed where the system response in a rather wide interval of the variable can be quite precisely approximated by this distribution.
Study of Complexities in Bouncing Ball Dynamical System
Directory of Open Access Journals (Sweden)
Lal Mohan SAHA
2016-04-01
Full Text Available Evolutionary motions in a bouncing ball system consisting of a ball having a free fall in the Earth’s gravitational field have been studied systematically. Because of nonlinear form of the equations of motion, evolutions show chaos for certain set of parameters for certain initial conditions. Bifurcation diagram has been drawn to study regular and chaotic behavior. Numerical calculations have been performed to calculate Lyapunov exponents, topological entropies and correlation dimension as measures of complexity. Numerical results are shown through interesting graphics.
Small System dynamics models for big issues : Triple jump towards real-world complexity
Pruyt, E.
2013-01-01
System Dynamics (SD) is a method to describe, model, simulate and analyze dynamically complex issues and/or systems in terms of the processes, information, organizational boundaries and strategies. Quantitative SD modeling, simulation and analysis facilitates the (re)design of systems and design of
Automated sensitivity analysis: New tools for modeling complex dynamic systems
International Nuclear Information System (INIS)
Pin, F.G.
1987-01-01
Sensitivity analysis is an established methodology used by researchers in almost every field to gain essential insight in design and modeling studies and in performance assessments of complex systems. Conventional sensitivity analysis methodologies, however, have not enjoyed the widespread use they deserve considering the wealth of information they can provide, partly because of their prohibitive cost or the large initial analytical investment they require. Automated systems have recently been developed at ORNL to eliminate these drawbacks. Compilers such as GRESS and EXAP now allow automatic and cost effective calculation of sensitivities in FORTRAN computer codes. In this paper, these and other related tools are described and their impact and applicability in the general areas of modeling, performance assessment and decision making for radioactive waste isolation problems are discussed
Directory of Open Access Journals (Sweden)
Jian Liu
Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Liu, Jian; Liu, Kexin; Liu, Shutang
2017-01-01
In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.
Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof
2018-01-01
We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.
Complex dynamic and static structures in interconnected particle systems
International Nuclear Information System (INIS)
Kristiansen, Kai de Lange
2004-01-01
Observations in the magnetic hole system under different conditions have generated many different patterns and dynamical phenomena which have generated even more ideas on how to attack and analyze them on a firm physical basis. Some of these problems are described in paper 4. In this thesis we have studied the dynamics of the few body system. The braid theory provides a compact description of this motion and enables a better real-time analysis with a minimum of information needed for computation. Also the amount of data to store on disks can then be reduced. Another aspect is that braid theory provides new topological invariants which can bring new light on the phenomena under study. The world lines from the few body system can also be closed into a knot. In knot theory several invariant quantities have been developed the last two decades, where the Jones polynomial is one powerful invariant, as pointed out in Appendix B. The diffusive processes of a few body systems can take super diffusive behaviour, as shown in paper 3. Apparently intermittent states of the same system display a large variety of different modes. By analyzing these modes using rank-ordering statistics, we find that they obey the so-called Zipf-Mandelbrot relation, as discussed in papers 1, 2, 3 and 4. Numerical calculations based on Stokes' drag and magnetic dipole-dipole interactions resemble the behaviour of the experiments well. In sections 3.2 and A.1 we presented a possible derivation of the exponent γ in the Zipf-Mandelbrot relation. The derived values of γ are within the same order of magnitude as the values of γ obtained in the experiments. However, the derived values of γ have high uncertainties. These uncertainties may be reduced with a more refined definition of the work of a mode. This refinement has to take into account the correlation between the modes. The physical meaning behind the exponent γ and the correction term ζ in the Zipf-Mandelbrot relation is not fully understood
Complex dynamic and static structures in interconnected particle systems
Energy Technology Data Exchange (ETDEWEB)
Kristiansen, Kai de Lange
2004-07-01
Observations in the magnetic hole system under different conditions have generated many different patterns and dynamical phenomena which have generated even more ideas on how to attack and analyze them on a firm physical basis. Some of these problems are described in paper 4. In this thesis we have studied the dynamics of the few body system. The braid theory provides a compact description of this motion and enables a better real-time analysis with a minimum of information needed for computation. Also the amount of data to store on disks can then be reduced. Another aspect is that braid theory provides new topological invariants which can bring new light on the phenomena under study. The world lines from the few body system can also be closed into a knot. In knot theory several invariant quantities have been developed the last two decades, where the Jones polynomial is one powerful invariant, as pointed out in Appendix B. The diffusive processes of a few body systems can take super diffusive behaviour, as shown in paper 3. Apparently intermittent states of the same system display a large variety of different modes. By analyzing these modes using rank-ordering statistics, we find that they obey the so-called Zipf-Mandelbrot relation, as discussed in papers 1, 2, 3 and 4. Numerical calculations based on Stokes' drag and magnetic dipole-dipole interactions resemble the behaviour of the experiments well. In sections 3.2 and A.1 we presented a possible derivation of the exponent {gamma} in the Zipf-Mandelbrot relation. The derived values of {gamma} are within the same order of magnitude as the values of {gamma} obtained in the experiments. However, the derived values of {gamma} have high uncertainties. These uncertainties may be reduced with a more refined definition of the work of a mode. This refinement has to take into account the correlation between the modes. The physical meaning behind the exponent {gamma} and the correction term {zeta} in the Zipf
Software complex for developing dynamically packed program system for experiment automation
International Nuclear Information System (INIS)
Baluka, G.; Salamatin, I.M.
1985-01-01
Software complex for developing dynamically packed program system for experiment automation is considered. The complex includes general-purpose programming systems represented as the RT-11 standard operating system and specially developed problem-oriented moduli providing execution of certain jobs. The described complex is realized in the PASKAL' and MAKRO-2 languages and it is rather flexible to variations of the technique of the experiment
Early signatures of regime shifts in complex dynamical systems
Indian Academy of Sciences (India)
2015-02-05
Feb 5, 2015 ... journal of. February 2015 ... populations, financial markets, complex diseases and gene circuits. ... A recent exhaustive analysis of recorded ecosystem shifts points to an approach- .... The quantitative estimation of these.
Holomorphic Dynamical Systems in the Complex Plane: An Introduction
DEFF Research Database (Denmark)
Branner, Bodil
1995-01-01
The paper reviews some basic properties of Julia sets of polynomials and the Mandelbrot set. In particular we emphasize the concept of normal families, the importance of repelling periodic points. The paper is the first one in a series of three papers about Holomorphic Dynamics in the Proceedings...
Return-to-Work Within a Complex and Dynamic Organizational Work Disability System
Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J.
2015-01-01
Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, an...
Complex Dynamics in Physiological Systems: From Heart to Brain
Dana, Syamal K; Kurths, Jürgen
2009-01-01
Nonlinear dynamics has become an important field of research in recent years in many areas of the natural sciences. In particular, it has potential applications in biology and medicine; nonlinear data analysis has helped to detect the progress of cardiac disease, physiological disorders, for example episodes of epilepsy, and others. This book focuses on the current trends of research concerning the prediction of sudden cardiac death and the onset of epileptic seizures, using the nonlinear analysis based on ECG and EEG data. Topics covered include the analysis of cardiac models and neural models. The book is a collection of recent research papers by leading physicists, mathematicians, cardiologists and neurobiologists who are actively involved in using the concepts of nonlinear dynamics to explore the functional behaviours of heart and brain under normal and pathological conditions. This collection is intended for students in physics, mathematics and medical sciences, and researchers in interdisciplinary areas...
Dynamic analysis of complex tube systems in heat exchangers
International Nuclear Information System (INIS)
Kouba, J.; Dvorak, P.
1985-01-01
Using a computation model, a dynamic analysis was made of tube assemblies of heat exchanger bundles by the finite element method. The algorithm is presented for determining the frequency mode properties, based on the Sturm sequences combined with inverse vector iteration. The results obtained using the method are compared with those obtained by analytical solution and by the transfer matrix method, this for the cases of both eigenvibrations and resonance vibrations. The results are in very good agreement. For the first four eigenfrequencies, the calculation error is less than 1.5% as against the analytical solution. (J.B.). 4 tabs., 8 figs., 5 refs
Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems
Ivancevic, Vladimir G.; Reid, Darryn J.
We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: quote>Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)...quote> We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.
Koorehdavoudi, Hana; Bogdan, Paul
2016-06-01
Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.
Controllability of complex networks for sustainable system dynamics
Successful implementation of sustainability ideas in ecosystem management requires a basic understanding of the often non-linear and non-intuitive relationships among different dimensions of sustainability, particularly the system-wide implications of human actions. This basic un...
Data based identification and prediction of nonlinear and complex dynamical systems
Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso
2016-07-01
The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical
Data based identification and prediction of nonlinear and complex dynamical systems
Energy Technology Data Exchange (ETDEWEB)
Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)
2016-07-12
The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear
Data based identification and prediction of nonlinear and complex dynamical systems
International Nuclear Information System (INIS)
Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso
2016-01-01
The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear
Planning and complexity : Engaging with temporal dynamics, uncertainty and complex adaptive systems
Sengupta, Ulysses; Rauws, Ward S.; de Roo, Gert
2016-01-01
The nature of complex systems as a transdisciplinary collection of concepts from physics and economics to sociology and ecology provides an evolving field of inquiry (Laszlo and Krippner, 1998) for urban planning and urban design. As a result, planning theory has assimilated multiple concepts from
Planning and complexity : Engaging with temporal dynamics, uncertainty and complex adaptive systems
Sengupta, Ulysses; Rauws, Ward S.; de Roo, Gert
The nature of complex systems as a transdisciplinary collection of concepts from physics and economics to sociology and ecology provides an evolving field of inquiry (Laszlo and Krippner, 1998) for urban planning and urban design. As a result, planning theory has assimilated multiple concepts from
Stabilizing simulations of complex stochastic representations for quantum dynamical systems
Energy Technology Data Exchange (ETDEWEB)
Perret, C; Petersen, W P, E-mail: wpp@math.ethz.ch [Seminar for Applied Mathematics, ETH, Zurich (Switzerland)
2011-03-04
Path integral representations of quantum dynamics can often be formulated as stochastic differential equations (SDEs). In a series of papers, Corney and Drummond (2004 Phys. Rev. Lett. 93 260401), Deuar and Drummond (2001 Comput. Phys. Commun. 142 442-5), Drummond and Gardnier (1980 J. Phys. A: Math. Gen. 13 2353-68), Gardiner and Zoller (2004 Quantum Noise: A Handbook of Markovian and Non-Markovian Quantum Stochastic Methods with Applications to Quantum Optics (Springer Series in Synergetics) 3rd edn (Berlin: Springer)) and Gilchrist et al (1997 Phys. Rev. A 55 3014-32) and their collaborators have derived SDEs from coherent states representations for density matrices. Computationally, these SDEs are attractive because they seem simple to simulate. They can be quite unstable, however. In this paper, we consider some of the instabilities and propose a few remedies. Particularly, because the variances of the simulated paths typically grow exponentially, the processes become de-localized in relatively short times. Hence, the issues of boundary conditions and stable integration methods become important. We use the Bose-Einstein Hamiltonian as an example. Our results reveal that it is possible to significantly extend integration times and show the periodic structure of certain functionals.
Optimal Control and Forecasting of Complex Dynamical Systems
Grigorenko, Ilya
2006-01-01
This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance. The theory presented here can be efficiently applied to various problems, such as the determination of the optimal shape of a laser pulse to induce certain excitations in quantum systems, the optimal design of nanostructured materials and devices, or the control of chaotic systems and minimization of the forecast error for a given forecasting model (for example, artificial neural networks). Starting from a brief review of the history of variational calcul
Dynamics in Complex Coacervates
Perry, Sarah
Understanding the dynamics of a material provides detailed information about the self-assembly, structure, and intermolecular interactions present in a material. While rheological methods have long been used for the characterization of complex coacervate-based materials, it remains a challenge to predict the dynamics for a new system of materials. Furthermore, most work reports only qualitative trends exist as to how parameters such as charge stoichiometry, ionic strength, and polymer chain length impact self-assembly and material dynamics, and there is little information on the effects of polymer architecture or the organization of charges within a polymer. We seek to link thermodynamic studies of coacervation phase behavior with material dynamics through a carefully-controlled, systematic study of coacervate linear viscoelasticity for different polymer chemistries. We couple various methods of characterizing the dynamics of polymer-based complex coacervates, including the time-salt superposition methods developed first by Spruijt and coworkers to establish a more mechanistic strategy for comparing the material dynamics and linear viscoelasticity of different systems. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support of this research.
International Nuclear Information System (INIS)
Choi, Kwang Sik; Choi, Young Sung; Han, Kyu Hyun; Kim, Do Hyoung
2007-01-01
The methodology being used today for assuring nuclear safety is based on analytic approaches. In the 21st century, holistic approaches are increasingly used over traditional analytic method that is based on reductionism. Presently, it leads to interest in complexity theory or system dynamics. In this paper, we review global academic trends, social environments, concept of nuclear safety and regulatory frameworks for nuclear safety. We propose a new safety paradigm and also regulatory approach using holistic approach and system dynamics now in fashion
Bifurcation and complex dynamics of a discrete-time predator-prey system involving group defense
Directory of Open Access Journals (Sweden)
S. M. Sohel Rana
2015-09-01
Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system involving group defense. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamical behaviors, including phase portraits, period-7, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors.
Jetha, Arif; Pransky, Glenn; Hettinger, Lawrence J
2016-01-01
Work disability (WD) is characterized by variable and occasionally undesirable outcomes. The underlying determinants of WD outcomes include patterns of dynamic relationships among health, personal, organizational and regulatory factors that have been challenging to characterize, and inadequately represented by contemporary WD models. System dynamics modeling (SDM) methodology applies a sociotechnical systems thinking lens to view WD systems as comprising a range of influential factors linked by feedback relationships. SDM can potentially overcome limitations in contemporary WD models by uncovering causal feedback relationships, and conceptualizing dynamic system behaviors. It employs a collaborative and stakeholder-based model building methodology to create a visual depiction of the system as a whole. SDM can also enable researchers to run dynamic simulations to provide evidence of anticipated or unanticipated outcomes that could result from policy and programmatic intervention. SDM may advance rehabilitation research by providing greater insights into the structure and dynamics of WD systems while helping to understand inherent complexity. Challenges related to data availability, determining validity, and the extensive time and technical skill requirements for model building may limit SDM's use in the field and should be considered. Contemporary work disability (WD) models provide limited insight into complexity associated with WD processes. System dynamics modeling (SDM) has the potential to capture complexity through a stakeholder-based approach that generates a simulation model consisting of multiple feedback loops. SDM may enable WD researchers and practitioners to understand the structure and behavior of the WD system as a whole, and inform development of improved strategies to manage straightforward and complex WD cases.
Reza Kalantari; Javad Gholami
2017-01-01
This longitudinal case study explored Iranian EFL learners’ lexical complexity (LC) through the lenses of Dynamic Systems Theory (DST). Fifty independent essays written by five intermediate to advanced female EFL learners in a TOEFL iBT preparation course over six months constituted the corpus of this study. Three Coh-Metrix indices (Graesser, McNamara, Louwerse, & Cai, 2004; McNamara & Graesser, 2012), three Lexical Complexity Analyzer indices (Lu, 2010, 2012; Lu & Ai, 2011...
Identification of Complex Dynamical Systems with Neural Networks (2/2)
CERN. Geneva
2016-01-01
The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...
Identification of Complex Dynamical Systems with Neural Networks (1/2)
CERN. Geneva
2016-01-01
The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...
Marek, Michael W.; Wu, Wen-Chi Vivian
2014-01-01
This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…
Sagis, L.M.C.; Öttinger, H.C.
2013-01-01
In this paper we present a general model for the dynamic behavior of multiphase systems in which the bulk phases and interfaces have a complex microstructure (for example, immiscible polymer blends with added compatibilizers, or polymer stabilized emulsions with thickening agents dispersed in the
Cameron, Lynne
2015-01-01
Complex dynamic systems (CDS) theory offers a powerful metaphorical model of applied linguistic processes, allowing holistic descriptions of situated phenomena, and addressing the connectedness and change that often characterise issues in our field. A recent study of Kenyan conflict transformation illustrates application of a CDS perspective. Key…
Logic-based hierarchies for modeling behavior of complex dynamic systems with applications
International Nuclear Information System (INIS)
Hu, Y.S.; Modarres, M.
2000-01-01
Most complex systems are best represented in the form of a hierarchy. The Goal Tree Success Tree and Master Logic Diagram (GTST-MLD) are proven powerful hierarchic methods to represent complex snap-shot of plant knowledge. To represent dynamic behaviors of complex systems, fuzzy logic is applied to replace binary logic to extend the power of GTST-MLD. Such a fuzzy-logic-based hierarchy is called Dynamic Master Logic Diagram (DMLD). This chapter discusses comparison of the use of GTST-DMLD when applied as a modeling tool for systems whose relationships are modeled by either physical, binary logical or fuzzy logical relationships. This is shown by applying GTST-DMLD to the Direct Containment Heating (DCH) phenomenon at pressurized water reactors which is an important safety issue being addressed by the nuclear industry. (orig.)
a Statistical Dynamic Approach to Structural Evolution of Complex Capital Market Systems
Shao, Xiao; Chai, Li H.
As an important part of modern financial systems, capital market has played a crucial role on diverse social resource allocations and economical exchanges. Beyond traditional models and/or theories based on neoclassical economics, considering capital markets as typical complex open systems, this paper attempts to develop a new approach to overcome some shortcomings of the available researches. By defining the generalized entropy of capital market systems, a theoretical model and nonlinear dynamic equation on the operations of capital market are proposed from statistical dynamic perspectives. The US security market from 1995 to 2001 is then simulated and analyzed as a typical case. Some instructive results are discussed and summarized.
Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise
Liu, Feng; Li, Yaguang
A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.
DEFF Research Database (Denmark)
Simonsen, Jakob Grue
2009-01-01
We consider the computational complexity of languages of symbolic dynamical systems. In particular, we study complexity hierarchies and membership of the non-uniform class P/poly. We prove: 1.For every time-constructible, non-decreasing function t(n)=@w(n), there is a symbolic dynamical system...... with language decidable in deterministic time O(n^2t(n)), but not in deterministic time o(t(n)). 2.For every space-constructible, non-decreasing function s(n)=@w(n), there is a symbolic dynamical system with language decidable in deterministic space O(s(n)), but not in deterministic space o(s(n)). 3.There...... are symbolic dynamical systems having hard and complete languages under @?"m^l^o^g^s- and @?"m^p-reduction for every complexity class above LOGSPACE in the backbone hierarchy (hence, P-complete, NP-complete, coNP-complete, PSPACE-complete, and EXPTIME-complete sets). 4.There are decidable languages of symbolic...
Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems
Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.
2018-01-01
The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.
Optimal system size for complex dynamics in random neural networks near criticality
Energy Technology Data Exchange (ETDEWEB)
Wainrib, Gilles, E-mail: wainrib@math.univ-paris13.fr [Laboratoire Analyse Géométrie et Applications, Université Paris XIII, Villetaneuse (France); García del Molino, Luis Carlos, E-mail: garciadelmolino@ijm.univ-paris-diderot.fr [Institute Jacques Monod, Université Paris VII, Paris (France)
2013-12-15
In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices.
Optimal system size for complex dynamics in random neural networks near criticality
International Nuclear Information System (INIS)
Wainrib, Gilles; García del Molino, Luis Carlos
2013-01-01
In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices
Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen
2015-03-01
The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.
International Nuclear Information System (INIS)
Zheng, Z.C.; Xie, G.; Du, Q.H.
1987-01-01
Because of the existence of nonlinear characteristics in practical engineering structures, such as large steam turbine-foundation system and offshore platform, it is necessary to predict nonlinear dynamic responses for these very large and complex structural systems subjected extreme load. Due to the limited storage and high executing cost of computers, there are still some difficulties in the analysis for such systems although the traditional finite element methods provide basic available methods to the problems. The dynamic substructure methods, which were developed as a branch of general structural dynamics in the past more than 20 years and have been widely used from aircraft, space vehicles to other mechanical and civil engineering structures, present a powerful method to the analysis of very large structural systems. The key to success is due to the considerable reduction in the number of degrees of freedom while not changing the physical essence of the problems investigated. The dynamic substructure method has been extended to nonlinear system and applicated to the analysis of nonlinear dynamic response of an offshore platform by Z.C. Zheng, et al. (1983, 1985a, b, c). In this paper, the method is presented to analyze dynamic responses of the systems contained intrinsic nonlinearities and with nonlinear attachments and nonlinear supports of nuclear structural systems. The efficiency of the method becomes more clear for nonlinear dynamic problems due to the adoption of iterating processes. For simplicity, the analysis procedure is demonstrated briefly. The generalized substructure method of nonlinear systems is similar to linear systems, only the nonlinear terms are treated as pseudo-forces. Interface coordinates are classified into two categories, the connecting interface coordinates which connect with each other directly in the global system and the linking interface coordinates which link to each other through attachments. (orig./GL)
The Modeling and Complexity of Dynamical Systems by Means of Computation and Information Theories
Directory of Open Access Journals (Sweden)
Robert Logozar
2011-12-01
Full Text Available We present the modeling of dynamical systems and finding of their complexity indicators by the use of concepts from computation and information theories, within the framework of J. P. Crutchfield's theory of ε-machines. A short formal outline of the ε-machines is given. In this approach, dynamical systems are analyzed directly from the time series that is received from a properly adjusted measuring instrument. The binary strings are parsed through the parse tree, within which morphologically and probabilistically unique subtrees or morphs are recognized as system states. The outline and precise interrelation of the information-theoretic entropies and complexities emanating from the model is given. The paper serves also as a theoretical foundation for the future presentation of the DSA program that implements the ε-machines modeling up to the stochastic finite automata level.
Bifurcation and complex dynamics of a discrete-time predator-prey system
Directory of Open Access Journals (Sweden)
S. M. Sohel Rana
2015-06-01
Full Text Available In this paper, we investigate the dynamics of a discrete-time predator-prey system of Holling-I type in the closed first quadrant R+2. The existence and local stability of positive fixed point of the discrete dynamical system is analyzed algebraically. It is shown that the system undergoes a flip bifurcation and a Neimark-Sacker bifurcation in the interior of R+2 by using bifurcation theory. It has been found that the dynamical behavior of the model is very sensitive to the parameter values and the initial conditions. Numerical simulation results not only show the consistence with the theoretical analysis but also display the new and interesting dynamic behaviors, including phase portraits, period-9, 10, 20-orbits, attracting invariant circle, cascade of period-doubling bifurcation from period-20 leading to chaos, quasi-periodic orbits, and sudden disappearance of the chaotic dynamics and attracting chaotic set. In particular, we observe that when the prey is in chaotic dynamic, the predator can tend to extinction or to a stable equilibrium. The Lyapunov exponents are numerically computed to characterize the complexity of the dynamical behaviors. The analysis and results in this paper are interesting in mathematics and biology.
Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A
2010-12-01
The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.
Bountis, Tassos
2012-01-01
This book introduces and explores modern developments in the well established field of Hamiltonian dynamical systems. It focuses on high degree-of-freedom systems and the transitional regimes between regular and chaotic motion. The role of nonlinear normal modes is highlighted and the importance of low-dimensional tori in the resolution of the famous FPU paradox is emphasized. Novel powerful numerical methods are used to study localization phenomena and distinguish order from strongly and weakly chaotic regimes. The emerging hierarchy of complex structures in such regimes gives rise to particularly long-lived patterns and phenomena called quasi-stationary states, which are explored in particular in the concrete setting of one-dimensional Hamiltonian lattices and physical applications in condensed matter systems. The self-contained and pedagogical approach is blended with a unique balance between mathematical rigor, physics insights and concrete applications. End of chapter exercises and (more demanding) res...
Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Hui Li
2017-01-01
Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.
SACS2: Dynamic and Formal Safety Analysis Method for Complex Safety Critical System
International Nuclear Information System (INIS)
Koh, Kwang Yong; Seong, Poong Hyun
2009-01-01
Fault tree analysis (FTA) is one of the most widely used safety analysis technique in the development of safety critical systems. However, over the years, several drawbacks of the conventional FTA have become apparent. One major drawback is that conventional FTA uses only static gates and hence can not capture dynamic behaviors of the complex system precisely. Although several attempts such as dynamic fault tree (DFT), PANDORA, formal fault tree (FFT) and so on, have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. Second drawback of conventional FTA is its lack of rigorous semantics. Because it is informal in nature, safety analysis results heavily depend on an analyst's ability and are error-prone. Finally reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and timeconsuming for the complex systems. In this paper, we propose a new safety analysis method for complex safety critical system in qualitative manner. We introduce several temporal gates based on timed computational tree logic (TCTL) which can represent quantitative notion of time. Then, we translate the information of the fault trees into UPPAAL query language and the reasoning process is automatically done by UPPAAL which is the model checker for time critical system
International Nuclear Information System (INIS)
Peng, Weiwen; Li, Yan-Feng; Mi, Jinhua; Yu, Le; Huang, Hong-Zhong
2016-01-01
Degradation analysis is critical to reliability assessment and operational management of complex systems. Two types of assumptions are often adopted for degradation analysis: (1) single degradation indicator and (2) constant external factors. However, modern complex systems are generally characterized as multiple functional and suffered from multiple failure modes due to dynamic operating conditions. In this paper, Bayesian degradation analysis of complex systems with multiple degradation indicators under dynamic conditions is investigated. Three practical engineering-driven issues are addressed: (1) to model various combinations of degradation indicators, a generalized multivariate hybrid degradation process model is proposed, which subsumes both monotonic and non-monotonic degradation processes models as special cases, (2) to study effects of external factors, two types of dynamic covariates are incorporated jointly, which include both environmental conditions and operating profiles, and (3) to facilitate degradation based reliability analysis, a serial of Bayesian strategy is constructed, which covers parameter estimation, factor-related degradation prediction, and unit-specific remaining useful life assessment. Finally, degradation analysis of a type of heavy machine tools is presented to demonstrate the application and performance of the proposed method. A comparison of the proposed model with a traditional model is studied as well in the example. - Highlights: • A generalized multivariate hybrid degradation process model is introduced. • Various types of dependent degradation processes can be modeled coherently. • The effects of environmental conditions and operating profiles are investigated. • Unit-specific RUL assessment is implemented through a two-step Bayesian method.
Modeling Networks and Dynamics in Complex Systems: from Nano-Composites to Opinion Formation
Shi, Feng
Complex networks are ubiquitous in systems of physical, biological, social or technological origin. Components in those systems range from as large as cities in power grids, to as small as molecules in metabolic networks. Since the dawn of network science, significant attention has focused on the implications of dynamics in establishing network structure and the impact of structural properties on dynamics on those networks. The first part of the thesis follows this direction, studying the network formed by conductive nanorods in nano-materials, and focuses on the electrical response of the composite to the structure change of the network. New scaling laws for the shear-induced anisotropic percolation are introduced and a robust exponential tail of the current distribution across the network is identified. These results are relevant especially to "active" composite materials where materials are exposed to mechanical loading and strain deformations. However, in many real-world networks the evolution of the network topology is tied to the states of the vertices and vice versa. Networks that exhibit such a feedback are called adaptive or coevolutionary networks. The second part of the thesis examines two closely related variants of a simple, abstract model for coevolution of a network and the opinions of its members. As a representative model for adaptive networks, it displays the feature of self-organization of the system into a stable configuration due to the interplay between the network topology and the dynamics on the network. This simple model yields interesting dynamics and the slight change in the rewiring strategy results in qualitatively different behaviors of the system. In conclusion, the dissertation aims to develop new network models and tools which enable insights into the structure and dynamics of various systems, and seeks to advance network algorithms which provide approaches to coherently articulated questions in real-world complex systems such as
Dynamic complexity of a two-prey one-predator system with impulsive effect
International Nuclear Information System (INIS)
Zhang Yujuan; Xiu Zhilong; Chen Lansun
2005-01-01
In this paper, we investigate the dynamic complexity of a two-prey one-predator system with impulsive perturbation on predator at fixed moments. With the increase of the predation rate for the super competitor, the system displays complicated phenomena including a sequence of direct and inverse cascade of periodic-doubling, chaos, and symmetry breaking bifurcation. Moreover, we discuss the effect of the period of releasing predator on the dynamical behaviors of the unforced continuous system, and find that periodically releasing predator at fixed moments change the properties of the unforced continuous system. We suggest a highly effective method in pest control. The target pest population can be driven to extinction and the non-target pest (or harmless insect) can be permanent by choosing impulsive period, while classical method cannot emulate
Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.
Weber, Bruce H
2011-03-01
Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.
Controlling collective dynamics in complex minority-game resource-allocation systems
Zhang, Ji-Qiang; Huang, Zi-Gang; Dong, Jia-Qi; Huang, Liang; Lai, Ying-Cheng
2013-05-01
Resource allocation takes place in various kinds of real-world complex systems, such as traffic systems, social services institutions or organizations, or even ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Accompanying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving the majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, the majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical, and political systems.
Data-Driven Modeling of Complex Systems by means of a Dynamical ANN
Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.
2017-12-01
The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).
Spaiser, Viktoria; Hedström, Peter; Ranganathan, Shyam; Jansson, Kim; Nordvik, Monica K.; Sumpter, David J. T.
2018-01-01
It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena…
Complex dynamics in three-well duffing system with two external forcings
International Nuclear Information System (INIS)
Jing Zhujun; Huang Jicai; Deng Jin
2007-01-01
Three-well duffing system with two external forcing terms is investigated. The criterion of existence of chaos under the periodic perturbation is given by using Melnikov's method. By using second-order averaging method and Melnikov's method we proved the criterion of existence of chaos in averaged systems under quasi-periodic perturbation for ω 2 = nω 1 + εν, n = 1, 3, 5, and cannot prove the criterion of existence of chaos in second-order averaged system under quasi-periodic perturbation for ω 2 = nω 1 + εν, n = 2, 4, 6, 7, 8, 9, 10, 11, 12, where ν is not rational to ω 1 , but can show the occurrence of chaos in original system by numerical simulation. Numerical simulations including heteroclinic and homoclinic bifurcation surfaces, bifurcation diagrams, maximum Lyapunov exponents and Poincare map are given to illustrate the theoretical analysis, and to expose the more new complex dynamical behaviors. We show that cascades of period-doubling bifurcations from period-one to four orbits, cascades of interlocking period-doubling bifurcations from period-two orbits of two sets, from quasi-periodicity leading to chaos, onset of chaos which occurs more than one, interleaving occurrences of chaotic behavior and invariant torus, transient chaos with complex period windows and interior crisis, chaos converting to torus, different kind of chaotic attractors. Our results shows that the dynamical behaviors are different from the dynamics of duffing equation with two-well and two external forcings
Fuchs, Armin
2013-01-01
With many areas of science reaching across their boundaries and becoming more and more interdisciplinary, students and researchers in these fields are confronted with techniques and tools not covered by their particular education. Especially in the life- and neurosciences quantitative models based on nonlinear dynamics and complex systems are becoming as frequently implemented as traditional statistical analysis. Unfamiliarity with the terminology and rigorous mathematics may discourage many scientists to adopt these methods for their own work, even though such reluctance in most cases is not justified.This book bridges this gap by introducing the procedures and methods used for analyzing nonlinear dynamical systems. In Part I, the concepts of fixed points, phase space, stability and transitions, among others, are discussed in great detail and implemented on the basis of example elementary systems. Part II is devoted to specific, non-trivial applications: coordination of human limb movement (Haken-Kelso-Bunz ...
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Directory of Open Access Journals (Sweden)
Zhong Yi Wan
Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more
Data-assisted reduced-order modeling of extreme events in complex dynamical systems.
Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis
2018-01-01
The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in
NATO Advanced Research Workshop on Recent advances in Nonlinear Dynamics and Complex System Physics
Casati, Giulio; Complex Phenomena in Nanoscale Systems
2009-01-01
Nanoscale physics has become one of the rapidly developing areas of contemporary physics because of its direct relevance to newly emerging area, nanotechnologies. Nanoscale devices and quantum functional materials are usually constructed based on the results of fundamental studies on nanoscale physics. Therefore studying physical phenomena in nanosized systems is of importance for progressive development of nanotechnologies. In this context study of complex phenomena in such systems and using them for controlling purposes is of great practical importance. Namely, such studies are brought together in this book, which contains 27 papers on various aspects of nanoscale physics and nonlinear dynamics.
The emergence of learning-teaching trajectories in education: a complex dynamic systems approach.
Steenbeek, Henderien; van Geert, Paul
2013-04-01
In this article we shall focus on learning-teaching trajectories ='successful' as well as 'unsuccessful' ones - as emergent and dynamic phenomena resulting from the interactions in the entire educational context, in particular the interaction between students and teachers viewed as processes of intertwining self-, other- and co-regulation. The article provides a review of the educational research literature on action regulation in learning and teaching, and interprets this literature in light of the theory of complex dynamic systems. Based on this reinterpretation of the literature, two dynamic models are proposed, one focusing on the short-term dynamics of learning-teaching interactions as they take place in classrooms, the other focusing on the long-term dynamics of interactions in a network of variables encompassing concerns, evaluations, actions and action effects (such as learning) students and teachers. The aim of presenting these models is to demonstrate, first, the possibility of transforming existing educational theory into dynamic models and, second, to provide some suggestions as to how such models can be used to further educational theory and practice.
A complex, nonlinear dynamic systems perspective on Ayurveda and Ayurvedic research.
Rioux, Jennifer
2012-07-01
The fields of complexity theory and nonlinear dynamic systems (NDS) are relevant for analyzing the theory and practice of Ayurvedic medicine from a Western scientific perspective. Ayurvedic definitions of health map clearly onto the tenets of both systems and complexity theory and focus primarily on the preservation of organismic equanimity. Health care research informed by NDS and complexity theory would prioritize (1) ascertaining patterns reflected in whole systems as opposed to isolating components; (2) relationships and dynamic interaction rather than static end-points; (3) transitions, change and cumulative effects, consistent with delivery of therapeutic packages in the reality of the clinical setting; and (4) simultaneously exploring both local and global levels of healing phenomena. NDS and complexity theory are useful in examining nonlinear transitions between states of health and illness; the qualitative nature of shifts in health status; and looking at emergent properties and behaviors stemming from interactions between organismic and environmental systems. Complexity and NDS theory also demonstrate promise for enhancing the suitability of research strategies applied to Ayurvedic medicine through utilizing core concepts such as initial conditions, emergent properties, fractal patterns, and critical fluctuations. In the Ayurvedic paradigm, multiple scales and their interactions are addressed simultaneously, necessitating data collection on change patterns that occur on continuums of both time and space, and are viewed as complementary rather than isolated and discrete. Serious consideration of Ayurvedic clinical understandings will necessitate new measurement options that can account for the relevance of both context and environmental factors, in terms of local biology and the processual features of the clinical encounter. Relevant research design issues will need to address clinical tailoring strategies and provide mechanisms for mapping patterns of
Wilds, Roy; Kauffman, Stuart A.; Glass, Leon
2008-09-01
We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.
International Nuclear Information System (INIS)
Ali, S A; Kim, D-H; Cafaro, C; Giffin, A
2012-01-01
Information geometric techniques and inductive inference methods hold great promise for solving computational problems of interest in classical and quantum physics, especially with regard to complexity characterization of dynamical systems in terms of their probabilistic description on curved statistical manifolds. In this paper, we investigate the possibility of describing the macroscopic behavior of complex systems in terms of the underlying statistical structure of their microscopic degrees of freedom by the use of statistical inductive inference and information geometry. We review the maximum relative entropy formalism and the theoretical structure of the information geometrodynamical approach to chaos on statistical manifolds M S . Special focus is devoted to a description of the roles played by the sectional curvature K M S , the Jacobi field intensity J M S and the information geometrodynamical entropy S M S . These quantities serve as powerful information-geometric complexity measures of information-constrained dynamics associated with arbitrary chaotic and regular systems defined on M S . Finally, the application of such information-geometric techniques to several theoretical models is presented.
Directory of Open Access Journals (Sweden)
V. Gontar
1997-01-01
Full Text Available A new theoretical foundation for the discrete dynamics of physicochemical systems is presented. Based on the analogy between the π-theorem of the theory of dimensionality, the second law of thermodynamics and the stoichiometry of complex physicochemical reactions, basic dynamic equations and an extreme principle were formulated. The meaning of discrete time and space in the proposed equations is discussed. Some results of numerical calculations are presented to demonstrate the potential of the proposed approach to the mathematical simulation of spatiotemporal physicochemical reaction dynamics.
Directory of Open Access Journals (Sweden)
Tinggui Chen
2013-01-01
Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.
Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells.
Tan, Chris Soon Heng; Go, Ka Diam; Bisteau, Xavier; Dai, Lingyun; Yong, Chern Han; Prabhu, Nayana; Ozturk, Mert Burak; Lim, Yan Ting; Sreekumar, Lekshmy; Lengqvist, Johan; Tergaonkar, Vinay; Kaldis, Philipp; Sobota, Radoslaw M; Nordlund, Pär
2018-03-09
Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Universal dynamics of complex adaptive systems: Gauge theory of things alive
International Nuclear Information System (INIS)
Mack, G.
1994-04-01
A universal dynamics of objects and their relations - a kind of ''universal chemistry'' - is discussed which satisfies general principles of locality and relativity. Einsteins theory of gravitation and the gauge theory of elementary particles are prototypes, but complex adaptive systems - anything that is alive in the widest sense - fall under the same paradigma. Frustration and gauge symmetry arise naturally in this context. Besides a nondissipative deterministic dynamics, which is thought to operate at a fundamental levle, a Thermo-Dynamics in sense of Prigogine is introduced by adding a diffusion process. It introduces irreversibility and entropy production. It equilibrates the chaotic local model of the time development (only) and is designed to be undetectable under continued observation with given finite measuring accuracy. Compositeness and the development of structure can be described in this framework. The existence of a critical equilibrium state may be postulated which is invariant under the dynamics. But it is usually not reached in a finite time from a given starting configuration, because local dynamics suffers from critical slowing down, especially in the presence of frustration. (orig.)
Local difference measures between complex networks for dynamical system model evaluation.
Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen
2015-01-01
A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node
Complex dynamics of a Holling type II prey-predator system with state feedback control
International Nuclear Information System (INIS)
Jiang Guirong; Lu Qishao; Qian Linning
2007-01-01
The complex dynamics of a Holling type II prey-predator system with impulsive state feedback control is studied in both theoretical and numerical ways. The sufficient conditions for the existence and stability of semi-trivial and positive periodic solutions are obtained by using the Poincare map and the analogue of the Poincare criterion. The qualitative analysis shows that the positive periodic solution bifurcates from the semi-trivial solution through a fold bifurcation. The bifurcation diagrams, Lyapunov exponents, and phase portraits are illustrated by an example, in which the chaotic solutions appear via a cascade of period-doubling bifurcations. The superiority of the state feedback control strategy is also discussed
A probabilistic technique for the assessment of complex dynamic system resilience
Balchanos, Michael Gregory
In the presence of operational uncertainty, one of the greatest challenges in systems engineering is to ensure system effectiveness, mission capability and survivability for large scale, complex system architectures. Historic events such as the 2003 Northeastern Blackout, and the 2005 Hurricane Katrina, have underlined the great importance of system safety, and survivability. With safety management currently applied on a reactive basis to emerging incidents and risk challenges, there is a paradigm shift from passive, reactive and diagnosis-based approaches to the development of architectures that will autonomously manage safety and survivability through active, proactive and prognosis-based engineering solutions. The shift aims to bring safety considerations early in the engineering design process, in order to reduce retrofitting and additional safety certification costs, increase flexibility in risk management, and essentially make safety be "built-in" the design. As a possible enabling research direction, resilience engineering is an emerging discipline, pertinent to safety management, which offers alternative insights on the design of more safe and survivable system architectures. Conceptually, resilience engineering brings new perspectives on the understanding of system safety, accidents, failures, performance degradations and risk. A resilient system can "absorb" the impact of change due to unexpected disturbances, while it "adapts" to change, in order to maintain the system's physical integrity and capability to carry on with its mission. The leading hypothesis advocates that if a complex dynamic system is more resilient, then it would be more survivable, thus more effective, despite the unexpected disturbances that could affect its normal operating conditions. For investigating the impact of more resilient systems on survivability and safety, a framework for theoretical resilience estimations has been formulated. It constitutes the basis for quantitative
International Nuclear Information System (INIS)
Kim, Do Hun; Mun, Tae Hun; Kim, Dong Hwan
1999-02-01
This book introduces systems thinking and conceptual tool and modeling tool of dynamics system such as tragedy of single thinking, accessible way of system dynamics, feedback structure and causal loop diagram analysis, basic of system dynamics modeling, causal loop diagram and system dynamics modeling, information delay modeling, discovery and application for policy, modeling of crisis of agricultural and stock breeding products, dynamic model and lesson in ecosystem, development and decadence of cites and innovation of education forward system thinking.
Cerbino, Roberto; Cicuta, Pietro
2017-09-01
Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.
International Nuclear Information System (INIS)
Lu, Yunfan; Wang, Jun; Niu, Hongli
2015-01-01
An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model
Energy Technology Data Exchange (ETDEWEB)
Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli
2015-06-12
An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.
Return-to-Work Within a Complex and Dynamic Organizational Work Disability System.
Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J
2016-09-01
Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, and frontline supervisors and workers participated in model building sessions. Participants were asked questions that elicited information about the structure of the work disability system and were translated into feedback loops. To parameterize the model, participants were asked to estimate the shape and magnitude of the relationship between key model components. Data from published literature were also accessed to supplement participant estimates. Data were entered into a model created in the software program Vensim. Simulations were conducted to examine how financial incentives and light duty work disability-related policies, utilized by the participating companies, influenced RTW likelihood and preparedness. Results The SDMs were multidimensional, including individual attitudinal characteristics, health factors, and organizational components. Among the causal pathways uncovered, psychosocial components including workplace social support, supervisor and co-worker pressure, and supervisor-frontline worker communication impacted RTW likelihood and preparedness. Interestingly, SDM simulations showed that work disability-related policies in both companies resulted in a diminishing or opposing impact on RTW preparedness and likelihood. Conclusion SDM provides a novel systems view of RTW. Policy and psychosocial component relationships within the system have important implications for RTW, and may contribute to unanticipated outcomes.
Qi, Di
Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are
Directory of Open Access Journals (Sweden)
Reza Kalantari
2017-10-01
Full Text Available This longitudinal case study explored Iranian EFL learners’ lexical complexity (LC through the lenses of Dynamic Systems Theory (DST. Fifty independent essays written by five intermediate to advanced female EFL learners in a TOEFL iBT preparation course over six months constituted the corpus of this study. Three Coh-Metrix indices (Graesser, McNamara, Louwerse, & Cai, 2004; McNamara & Graesser, 2012, three Lexical Complexity Analyzer indices (Lu, 2010, 2012; Lu & Ai, 2011, and four Vocabprofile indices (Cobb, 2000 were selected to measure different dimensions of LC. Results of repeated measures analysis of variance (RM ANOVA indicated an improvement with regard to only lexical sophistication. Positive and significant relationships were found between time and mean values in Academic Word List and Beyond-2000 as indicators of lexical sophistication. The remaining seven indices of LC, falling short of significance, tended to flatten over the course of this writing program. Correlation analyses among LC indices indicated that lexical density enjoyed positive correlations with lexical sophistication. However, lexical diversity revealed no significant correlations with both lexical density and lexical sophistication. This study suggests that DST perspective specifies a viable foundation for analyzing lexical complexity
Evaluating the effect of smoking cessation treatment on a complex dynamical system.
Bekiroglu, Korkut; Russell, Michael A; Lagoa, Constantino M; Lanza, Stephanie T; Piper, Megan E
2017-11-01
To understand the dynamic relations among tobacco withdrawal symptoms to inform the development of effective smoking cessation treatments. Dynamical system models from control engineering are introduced and utilized to evaluate complex treatment effects. We demonstrate how dynamical models can be used to examine how distinct withdrawal-related processes are related over time and how treatment influences these relations. Intensive longitudinal data from a randomized placebo-controlled smoking cessation trial (N=1504) are used to estimate a dynamical model of withdrawal-related processes including momentary craving, negative affect, quitting self-efficacy, and cessation fatigue for each of six treatment conditions (nicotine patch, nicotine lozenge, bupropion, patch + lozenge, bupropion + lozenge, and placebo). Estimation and simulation results show that (1) withdrawal measurements are interrelated over time, (2) nicotine patch + nicotine lozenge showed reduced cessation fatigue and enhanced self-efficacy in the long-term while bupropion + nicotine lozenge was more effective at reducing negative affect and craving, and (3) although nicotine patch + nicotine lozenge had a better initial effect on cessation fatigue and self-efficacy, nicotine lozenge had a stronger effect on negative affect and nicotine patch had a stronger impact on craving. This approach can be used to provide new evidence illustrating (a) the total impact of treatment conditions (via steady state values) and (b) the total initial impact (via rate of initial change values) on smoking-related outcomes for separate treatment conditions, noting that the conditions that produce the largest change may be different than the conditions that produce the fastest change. Copyright © 2017 Elsevier B.V. All rights reserved.
Automation of multi-agent control for complex dynamic systems in heterogeneous computational network
Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan
2017-01-01
The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.
Dynamics of Defects and Dopants in Complex Systems: Si and Oxide Surfaces and Interfaces
Kirichenko, Taras; Yu, Decai; Banarjee, Sanjay; Hwang, Gyeong
2004-10-01
Fabrication of forthcoming nanometer scale electronic devices faces many difficulties including formation of extremely shallow and highly doped junctions. At present, ultra-low-energy ion implantation followed by high-temperature thermal annealing is most widely used to fabricate such ultra-shallow junctions. In the process, a great challenge lies in achieving precise control of redistribution and electrical activation of dopant impurities. Native defects (such as vacancies and interstitials) generated during implantation are known to be mainly responsible for the TED and also influence significantly the electrical activation/deactivation. Defect-dopant dynamics is rather well understood in crystalline Si and SiO2. However, little is known about their diffusion and annihilation (or precipitation) at the surfaces and interfaces, despite its growing importance in determining junction profiles as device dimensions get smaller. In this talk, we will present our density functional theory calculation results on the atomic and electronic structure and dynamical behavior of native defects and dopant-defect complexes in disordered/strained Si and oxide systems, such as i) clean and absorbent-modified Si(100) surface and subsurface layers, ii) amorphous-crystalline Si interfaces and iii) amorphous SiO2/Si interfaces. The fundamental understanding and data is essential in developing a comprehensive kinetic model for junction formation, which would contribute greatly in improving current process technologies.
Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.
2014-07-01
In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.
Seeing the System: Dynamics and Complexity of Technology Integration in Secondary Schools
Howard, Sarah K.; Thompson, Kate
2016-01-01
This paper introduces system dynamics modeling to understand, visualize and explore technology integration in schools, through the development of a theoretical model of technology-related change in teachers' practice. Technology integration is a dynamic social practice, within the social system of education. It is difficult, if not nearly…
Making System Dynamics Cool II : New Hot Teaching and Testing Cases of Increasing Complexity
Pruyt, E.
2010-01-01
This follow-up paper presents several actual cases for testing and teaching System Dynamics. The cases were developed between April 2009 and January 2010 for the Introductory System Dynamics courses at Delft University of Technology in the Netherlands. They can be used for teaching and testing
Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems
Lymperopoulos , Ilias; Lekakos , George
2013-01-01
Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...
International Nuclear Information System (INIS)
Antonini, C; Persico, G; Rowe, A L
2008-01-01
Among the measurement and control systems of gas turbine engines, a recent new issue is the possibility of performing unsteady pressure measurements to detect flow anomalies in an engine or to evaluate loads on aerodynamic surfaces. A possible answer to this demand could be extending the use of well known and widely used transmission line systems, which have been applied so far to steady monitoring, to unsteady measurements thanks to proper dynamic modeling and compensation. Despite the huge number of models existing in the literature, a novel method has been developed, which is at the same time easy-to-handle, flexible and capable of reproducing the actual physics of the problem. Furthermore, the new model is able to deal with arbitrary complex networks of lines and cavities, and thus its applicability is not limited to series-connected systems. The main objectives of this paper are to show the derivation of the model, its validation against experimental tests and example of its applicability
Coarse-graining complex dynamics
DEFF Research Database (Denmark)
Sibani, Paolo
2013-01-01
Continuous Time Random Walks (CTRW) are widely used to coarse-grain the evolution of systems jumping from a metastable sub-set of their configuration space, or trap, to another via rare intermittent events. The multi-scaled behavior typical of complex dynamics is provided by a fat...... macroscopic variables all produce identical long time relaxation behaviors. Hence, CTRW shed no light on the link between microscopic and macroscopic dynamics. We then highlight how a more recent approach, Record Dynamics (RD) provides a viable alternative, based on a very different set of physical ideas......: while CTRW make use of a renewal process involving identical traps of infinite size, RD embodies a dynamical entrenchment into a hierarchy of traps which are finite in size and possess different degrees of meta-stability. We show in particular how RD produces the stretched exponential, power...
2011-01-01
The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...
Janssen, M.; Voort, H. van der; Veenstra, A.F.E. van
2015-01-01
Many large transformation projects do not result in the outcomes desired or envisioned by the stakeholders. This type of project is characterised by dynamics which are both caused by and result of uncertainties and unexpected behaviour. In this paper a complex adaptive system (CAS) view was adopted
Light, John M; Jason, Leonard A; Stevens, Edward B; Callahan, Sarah; Stone, Ariel
2016-03-01
The complex system conception of group social dynamics often involves not only changing individual characteristics, but also changing within-group relationships. Recent advances in stochastic dynamic network modeling allow these interdependencies to be modeled from data. This methodology is discussed within a context of other mathematical and statistical approaches that have been or could be applied to study the temporal evolution of relationships and behaviors within small- to medium-sized groups. An example model is presented, based on a pilot study of five Oxford House recovery homes, sober living environments for individuals following release from acute substance abuse treatment. This model demonstrates how dynamic network modeling can be applied to such systems, examines and discusses several options for pooling, and shows how results are interpreted in line with complex system concepts. Results suggest that this approach (a) is a credible modeling framework for studying group dynamics even with limited data, (b) improves upon the most common alternatives, and (c) is especially well-suited to complex system conceptions. Continuing improvements in stochastic models and associated software may finally lead to mainstream use of these techniques for the study of group dynamics, a shift already occurring in related fields of behavioral science.
Malek, Ziga; Verburg, P.H.
In the Mediterranean region, land systems have been shaped gradually through centuries. They provide services to a large and growing population in a region that is among the most vulnerable to future global change. The spatial extent and distribution of Mediterranean land systems is, however,
Gessner, Manuel; Breuer, Heinz-Peter
2013-04-01
We obtain exact analytic expressions for a class of functions expressed as integrals over the Haar measure of the unitary group in d dimensions. Based on these general mathematical results, we investigate generic dynamical properties of complex open quantum systems, employing arguments from ensemble theory. We further generalize these results to arbitrary eigenvalue distributions, allowing a detailed comparison of typical regular and chaotic systems with the help of concepts from random matrix theory. To illustrate the physical relevance and the general applicability of our results we present a series of examples related to the fields of open quantum systems and nonequilibrium quantum thermodynamics. These include the effect of initial correlations, the average quantum dynamical maps, the generic dynamics of system-environment pure state entanglement and, finally, the equilibration of generic open and closed quantum systems.
International Nuclear Information System (INIS)
Upadhyay, Ranjit Kumar; Kumari, Nitu; Rai, Vikas
2009-01-01
In this paper, dynamical complexities in two reaction-diffusion (RD) model systems are explored. A spatial heterogeneity in the form of linear spatial gradient in the reproductive growth rate of the phytoplankton is incorporated in both the model systems. Extra mortality of the zooplankton due to toxin production by the phytoplankton is included in the second reaction diffusion model system. Effect of toxin production and spatial heterogeneity in the model systems are studied. Toxin production does not seem to have an appreciable effect on the asymptotic dynamics of the model systems. On the other hand, spatial heterogeneity does influence the dynamics. In particular, it increases the frequency of occurrence of chaos as evident from two dimensional parameter scans. Both these model systems display short term recurrent chaos [Rai V. Chaos in natural populations: edge or wedge? Ecol Complex 2004;1: 127-38] as they reside on 'edges of chaos' (EOC) [Rai V, Upadhyay RK. Evolving to the edge of chaos: chance or necessity? Chaos, Solitons and Fractals 2006;30:1074-87]. This suggests that the ecological systems have a tendency to evolve to EOC. The study corroborates the inferences drawn from an earlier study by Rai and Upadhyay [Rai V, Upadhyay RK. Evolving to the edge of chaos: chance or necessity? Chaos, Solitons and Fractals 2006;30:1074-87]. The system's dynamics is largely unpredictable and admits bursts of short-term predictability.
Sternberg, Shlomo
2010-01-01
Celebrated mathematician Shlomo Sternberg, a pioneer in the field of dynamical systems, created this modern one-semester introduction to the subject for his classes at Harvard University. Its wide-ranging treatment covers one-dimensional dynamics, differential equations, random walks, iterated function systems, symbolic dynamics, and Markov chains. Supplementary materials offer a variety of online components, including PowerPoint lecture slides for professors and MATLAB exercises.""Even though there are many dynamical systems books on the market, this book is bound to become a classic. The the
Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji
2017-01-01
We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…
Understanding the Online Informal Learning of English as a Complex Dynamic System: An Emic Approach
Sockett, Geoffrey
2013-01-01
Research into the online informal learning of English has already shown it to be a widespread phenomenon involving a range of comprehension and production activities such as viewing original version television series, listening to music on demand and social networking with other English users. Dynamic systems theory provides a suitable framework…
Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.
2018-03-01
In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.
Directory of Open Access Journals (Sweden)
Naors Y. anadalsaleem
2017-03-01
Full Text Available The dynamic optimization procedure for -dimensional vector function of a system, the state of which is interpreted as adaptable immune cell, is considered Using the results of the theory of artificial immune systems. The procedures for estimate of monitoring results are discussed. The procedure for assessing the entropy is recommended as a general recursive estimation algorithm. The results are focused on solving the optimization problems of cognitive selection of suitable physical resources, what expands the scope of Electromagnetic compatibility.
Complex dynamics and switching transients in periodically forced Filippov prey–predator system
International Nuclear Information System (INIS)
Tang, Guangyao; Qin, Wenjie; Tang, Sanyi
2014-01-01
Highlights: •We develop a Filippov prey–predator model with periodic forcing. •The sliding mode dynamics and its domain have been investigated. •The existence and stability of sliding periodic solution have been discussed. •The complex dynamics are addressed through bifurcation analyses. •Switching transients and their biological implications have been discussed. - Abstract: By employing threshold policy control (TPC) in combination with the definition of integrated pest management (IPM), a Filippov prey–predator model with periodic forcing has been proposed and studied, and the periodic forcing is affected by assuming a periodic variation in the intrinsic growth rate of the prey. This study aims to address how the periodic forcing and TPC affect the pest control. To do this, the sliding mode dynamics and sliding mode domain have been addressed firstly by using Utkin’s equivalent control method, and then the existence and stability of sliding periodic solution are investigated. Furthermore, the complex dynamics including multiple attractors coexistence, period adding sequences and chaotic solutions with respect to bifurcation parameters of forcing amplitude and economic threshold (ET) have been investigated numerically in more detail. Finally the switching transients associated with pest outbreaks and their biological implications have been discussed. Our results indicate that the sliding periodic solution could be globally stable, and consequently the prey or pest population can be controlled such that its density falls below the economic injury level (EIL). Moreover, the switching transients have both advantages and disadvantages concerning pest control, and the magnitude and frequency of switching transients depend on the initial values of both populations, forcing amplitude and ET
International Nuclear Information System (INIS)
Bertolotto, D.
2011-11-01
The current doctoral research is focused on the development and validation of a coupled computational tool, to combine the advantages of computational fluid dynamics (CFD) in analyzing complex flow fields and of state-of-the-art system codes employed for nuclear power plant (NPP) simulations. Such a tool can considerably enhance the analysis of NPP transient behavior, e.g. in the case of pressurized water reactor (PWR) accident scenarios such as Main Steam Line Break (MSLB) and boron dilution, in which strong coolant flow asymmetries and multi-dimensional mixing effects strongly influence the reactivity of the reactor core, as described in Chap. 1. To start with, a literature review on code coupling is presented in Chap. 2, together with the corresponding ongoing projects in the international community. Special reference is made to the framework in which this research has been carried out, i.e. the Paul Scherrer Institute's (PSI) project STARS (Steady-state and Transient Analysis Research for the Swiss reactors). In particular, the codes chosen for the coupling, i.e. the CFD code ANSYS CFX V11.0 and the system code US-NRC TRACE V5.0, are part of the STARS codes system. Their main features are also described in Chap. 2. The development of the coupled tool, named CFX/TRACE from the names of the two constitutive codes, has proven to be a complex and broad-based task, and therefore constraints had to be put on the target requirements, while keeping in mind a certain modularity to allow future extensions to be made with minimal efforts. After careful consideration, the coupling was defined to be on-line, parallel and with non-overlapping domains connected by an interface, which was developed through the Parallel Virtual Machines (PVM) software, as described in Chap. 3. Moreover, two numerical coupling schemes were implemented and tested: a sequential explicit scheme and a sequential semi-implicit scheme. Finally, it was decided that the coupling would be single
Gilstrap, Donald L.
2009-01-01
This article provides a historiographical analysis of major leadership and organizational development theories that have shaped our thinking about how we lead and administrate academic libraries. Drawing from behavioral, cognitive, systems, and complexity theories, this article discusses major theorists and research studies appearing over the past…
The dynamical complexity of a Ivlev-type prey-predator system with impulsive effect
International Nuclear Information System (INIS)
Wang Hailing; Wang Weiming
2008-01-01
Based on the classical predator-prey system with Ivlev-type functional response, an impulsive differential equations to model the process of periodic perturbations on the predator at different fixed time is established. It proves that there exists a locally asymptotically stable prey-eradication periodic solution when the impulse period is less than some critical value, and otherwise, the system can be permanent. Numerical results show that the system considered has more complicated dynamics. such as quasi-periodic oscillation, narrow periodic window, wide periodic window, chaotic bands, symmetry-breaking pitchfork bifurcation and crises, etc
A dynamic predictive maintenance policy for complex multi-component systems
International Nuclear Information System (INIS)
Van Horenbeek, Adriaan; Pintelon, Liliane
2013-01-01
The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings
Nonlinear and Complex Dynamics in Economics
William Barnett; Apostolos Serletis; Demitre Serletis
2012-01-01
This paper is an up-to-date survey of the state-of-the-art in dynamical systems theory relevant to high levels of dynamical complexity, characterizing chaos and near chaos, as commonly found in the physical sciences. The paper also surveys applications in economics and �finance. This survey does not include bifurcation analyses at lower levels of dynamical complexity, such as Hopf and transcritical bifurcations, which arise closer to the stable region of the parameter space. We discuss the...
Complexity of Economical Systems
Directory of Open Access Journals (Sweden)
G. P. Pavlos
2015-01-01
Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.
Theory and simulation of cavity quantum electro-dynamics in multi-partite quantum complex systems
Energy Technology Data Exchange (ETDEWEB)
Alidoosty Shahraki, Moslem; Khorasani, Sina; Aram, Mohammad Hasan [Sharif University of Technology, School of Electrical Engineering, Tehran (Iran, Islamic Republic of)
2014-05-15
The cavity quantum electrodynamics of various complex systems is here analyzed using a general versatile code developed in this research. Such quantum multi-partite systems normally consist of an arbitrary number of quantum dots in interaction with an arbitrary number of cavity modes. As an example, a nine-partition system is simulated under different coupling regimes, consisting of eight emitters interacting with one cavity mode. Two-level emitters (e.g. quantum dots) are assumed to have an arrangement in the form of a linear chain, defining the mutual dipole-dipole interactions. It was observed that plotting the system trajectory in the phase space reveals a chaotic behavior in the so-called ultrastrong-coupling regime. This result is mathematically confirmed by detailed calculation of the Kolmogorov entropy, as a measure of chaotic behavior. In order to study the computational complexity of our code, various multi-partite systems consisting of one to eight quantum dots in interaction with one cavity mode were solved individually. Computation run times and the allocated memory for each system were measured. (orig.)
How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems
Tan, Lei; Zheng, Bo; Chen, Jun-Jie; Jiang, Xiong-Fei
2015-01-01
What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time. PMID:25723154
How volatilities nonlocal in time affect the price dynamics in complex financial systems.
Directory of Open Access Journals (Sweden)
Lei Tan
Full Text Available What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time.
Boccara, Nino
2010-01-01
Modeling Complex Systems, 2nd Edition, explores the process of modeling complex systems, providing examples from such diverse fields as ecology, epidemiology, sociology, seismology, and economics. It illustrates how models of complex systems are built and provides indispensable mathematical tools for studying their dynamics. This vital introductory text is useful for advanced undergraduate students in various scientific disciplines, and serves as an important reference book for graduate students and young researchers. This enhanced second edition includes: . -recent research results and bibliographic references -extra footnotes which provide biographical information on cited scientists who have made significant contributions to the field -new and improved worked-out examples to aid a student’s comprehension of the content -exercises to challenge the reader and complement the material Nino Boccara is also the author of Essentials of Mathematica: With Applications to Mathematics and Physics (Springer, 2007).
Complex Dynamics in the Basal Ganglia: Health and Disease Beyond the Motor System.
Andres, Daniela S; Darbin, Olivier
2018-01-01
The rate and oscillatory hypotheses are the two main current frameworks of basal ganglia pathophysiology. Both hypotheses have emerged from research on movement disorders sharing similar conceptualizations. These pathological conditions are classified either as hypokinetic or hyperkinetic, and the electrophysiological hallmarks of basal ganglia dysfunction are categorized as prokinetic or antikinetic. Although nonmotor symptoms, including neurobehavioral symptoms, are a key manifestation of basal ganglia dysfunction, they are uncommonly accounted for in these models. In patients with Parkinson's disease, the broad spectrum of motor symptoms and neurobehavioral symptoms challenges the concept that basal ganglia disorders can be classified into two categories. The profile of symptoms of basal ganglia dysfunction is best characterized by a breakdown of information processing, accompanied at an electrophysiological level by complex alterations of spiking activity from basal ganglia neurons. The authors argue that the dynamics of the basal ganglia circuit cannot be fully characterized by linear properties such as the firing rate or oscillatory activity. In fact, the neuronal spiking stream of the basal ganglia circuit is irregular but has temporal structure. In this context, entropy was introduced as a measure of probabilistic irregularity in the temporal organization of neuronal activity of the basal ganglia, giving place to the entropy hypothesis of basal ganglia pathology. Obtaining a quantitative characterization of irregularity of spike trains from basal ganglia neurons is key to elaborating a new framework of basal ganglia pathophysiology.
Dynamic and interacting complex networks
Dickison, Mark E.
This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible
Morecroft, John
System dynamics is an approach for thinking about and simulating situations and organisations of all kinds and sizes by visualising how the elements fit together, interact and change over time. This chapter, written by John Morecroft, describes modern system dynamics which retains the fundamentals developed in the 1950s by Jay W. Forrester of the MIT Sloan School of Management. It looks at feedback loops and time delays that affect system behaviour in a non-linear way, and illustrates how dynamic behaviour depends upon feedback loop structures. It also recognises improvements as part of the ongoing process of managing a situation in order to achieve goals. Significantly it recognises the importance of context, and practitioner skills. Feedback systems thinking views problems and solutions as being intertwined. The main concepts and tools: feedback structure and behaviour, causal loop diagrams, dynamics, are practically illustrated in a wide variety of contexts from a hot water shower through to a symphony orchestra and the practical application of the approach is described through several real examples of its use for strategic planning and evaluation.
International Nuclear Information System (INIS)
Schreckenberg, M
2004-01-01
This book by Nino Boccara presents a compilation of model systems commonly termed as 'complex'. It starts with a definition of the systems under consideration and how to build up a model to describe the complex dynamics. The subsequent chapters are devoted to various categories of mean-field type models (differential and recurrence equations, chaos) and of agent-based models (cellular automata, networks and power-law distributions). Each chapter is supplemented by a number of exercises and their solutions. The table of contents looks a little arbitrary but the author took the most prominent model systems investigated over the years (and up until now there has been no unified theory covering the various aspects of complex dynamics). The model systems are explained by looking at a number of applications in various fields. The book is written as a textbook for interested students as well as serving as a comprehensive reference for experts. It is an ideal source for topics to be presented in a lecture on dynamics of complex systems. This is the first book on this 'wide' topic and I have long awaited such a book (in fact I planned to write it myself but this is much better than I could ever have written it!). Only section 6 on cellular automata is a little too limited to the author's point of view and one would have expected more about the famous Domany-Kinzel model (and more accurate citation!). In my opinion this is one of the best textbooks published during the last decade and even experts can learn a lot from it. Hopefully there will be an actualization after, say, five years since this field is growing so quickly. The price is too high for students but this, unfortunately, is the normal case today. Nevertheless I think it will be a great success! (book review)
Pol, Rafel; Hristovski, Robert; Medina, Daniel; Balague, Natalia
2018-04-19
A better understanding of how sports injuries occur in order to improve their prevention is needed for medical, economic, scientific and sports success reasons. This narrative review aims to explain the mechanisms that underlie the occurrence of sports injuries, and an innovative approach for their prevention on the basis of complex dynamic systems approach. First, we explain the multilevel organisation of living systems and how function of the musculoskeletal system may be impaired. Second, we use both, a constraints approach and a connectivity hypothesis to explain why and how the susceptibility to sports injuries may suddenly increase. Constraints acting at multiple levels and timescales replace the static and linear concept of risk factors, and the connectivity hypothesis brings an understanding of how the accumulation of microinjuries creates a macroscopic non-linear effect, that is, how a common motor action may trigger a severe injury. Finally, a recap of practical examples and challenges for the future illustrates how the complex dynamic systems standpoint, changing the way of thinking about sports injuries, offers innovative ideas for improving sports injury prevention. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Dynamic complexities of a Holling II two-prey one-predator system with impulsive effect
International Nuclear Information System (INIS)
Song Xinyu; Li Yongfeng
2007-01-01
In this paper, we investigate the dynamic behaviors of a Holling II two-prey one-predator system with impulsive effect concerning biological control and chemical control strategies-periodic releasing natural enemies and spraying pesticide (or harvesting pests) at fixed time. By using the Floquet theory of linear periodic impulsive equation and small-amplitude perturbation we show that there exists a globally asymptotically stable two-prey eradication periodic solution when the impulsive period is less than some critical value. Further, we prove that the system is permanent if the impulsive period is larger than some critical value, and meanwhile the conditions for the extinction of one of the two prey and permanence of the remaining two species are given. Finally, numerical simulation shows that there exists a stable positive periodic solution with a maximum value no larger than a given level. Thus, we can use the stability of the positive periodic solution and its period to control insect pests at acceptably low levels
Lee, Hyung B.; Ghia, Urmila; Bayyuk, Sami; Oberkampf, William L.; Roy, Christopher J.; Benek, John A.; Rumsey, Christopher L.; Powers, Joseph M.; Bush, Robert H.; Mani, Mortaza
2016-01-01
Computational fluid dynamics (CFD) and other advanced modeling and simulation (M&S) methods are increasingly relied on for predictive performance, reliability and safety of engineering systems. Analysts, designers, decision makers, and project managers, who must depend on simulation, need practical techniques and methods for assessing simulation credibility. The AIAA Guide for Verification and Validation of Computational Fluid Dynamics Simulations (AIAA G-077-1998 (2002)), originally published in 1998, was the first engineering standards document available to the engineering community for verification and validation (V&V) of simulations. Much progress has been made in these areas since 1998. The AIAA Committee on Standards for CFD is currently updating this Guide to incorporate in it the important developments that have taken place in V&V concepts, methods, and practices, particularly with regard to the broader context of predictive capability and uncertainty quantification (UQ) methods and approaches. This paper will provide an overview of the changes and extensions currently underway to update the AIAA Guide. Specifically, a framework for predictive capability will be described for incorporating a wide range of error and uncertainty sources identified during the modeling, verification, and validation processes, with the goal of estimating the total prediction uncertainty of the simulation. The Guide's goal is to provide a foundation for understanding and addressing major issues and concepts in predictive CFD. However, this Guide will not recommend specific approaches in these areas as the field is rapidly evolving. It is hoped that the guidelines provided in this paper, and explained in more detail in the Guide, will aid in the research, development, and use of CFD in engineering decision-making.
Birkhoff, George D
1927-01-01
His research in dynamics constitutes the middle period of Birkhoff's scientific career, that of maturity and greatest power. -Yearbook of the American Philosophical Society The author's great book€¦is well known to all, and the diverse active modern developments in mathematics which have been inspired by this volume bear the most eloquent testimony to its quality and influence. -Zentralblatt MATH In 1927, G. D. Birkhoff wrote a remarkable treatise on the theory of dynamical systems that would inspire many later mathematicians to do great work. To a large extent, Birkhoff was writing about his o
Ratliff, Eric A; Kaduri, Pamela; Masao, Frank; Mbwambo, Jessie K K; McCurdy, Sheryl A
2016-04-01
Contrary to popular belief, policies on drug use are not always based on scientific evidence or composed in a rational manner. Rather, decisions concerning drug policies reflect the negotiation of actors' ambitions, values, and facts as they organize in different ways around the perceived problems associated with illicit drug use. Drug policy is thus best represented as a complex adaptive system (CAS) that is dynamic, self-organizing, and coevolving. In this analysis, we use a CAS framework to examine how harm reduction emerged around heroin trafficking and use in Tanzania over the past thirty years (1985-present). This account is an organizational ethnography based on of the observant participation of the authors as actors within this system. We review the dynamic history and self-organizing nature of harm reduction, noting how interactions among system actors and components have coevolved with patterns of heroin us, policing, and treatment activities over time. Using a CAS framework, we describe harm reduction as a complex process where ambitions, values, facts, and technologies interact in the Tanzanian sociopolitical environment. We review the dynamic history and self-organizing nature of heroin policies, noting how the interactions within and between competing prohibitionist and harm reduction policies have changed with patterns of heroin use, policing, and treatment activities over time. Actors learn from their experiences to organize with other actors, align their values and facts, and implement new policies. Using a CAS approach provides researchers and policy actors a better understanding of patterns and intricacies in drug policy. This knowledge of how the system works can help improve the policy process through adaptive action to introduce new actors, different ideas, and avenues for communication into the system. Copyright © 2015 Elsevier B.V. All rights reserved.
Blume, Steffen O P; Sansavini, Giovanni
2017-12-01
Complex dynamical systems face abrupt transitions into unstable and catastrophic regimes. These critical transitions are triggered by gradual modifications in stressors, which push the dynamical system towards unstable regimes. Bifurcation analysis can characterize such critical thresholds, beyond which systems become unstable. Moreover, the stochasticity of the external stressors causes small-scale fluctuations in the system response. In some systems, the decomposition of these signal fluctuations into precursor signals can reveal early warning signs prior to the critical transition. Here, we present a dynamical analysis of a power system subjected to an increasing load level and small-scale stochastic load perturbations. We show that the auto- and cross-correlations of bus voltage magnitudes increase, leading up to a Hopf bifurcation point, and further grow until the system collapses. This evidences a gradual transition into a state of "critical coupling," which is complementary to the established concept of "critical slowing down." Furthermore, we analyze the effects of the type of load perturbation and load characteristics on early warning signs and find that gradient changes in the autocorrelation provide early warning signs of the imminent critical transition under white-noise but not for auto-correlated load perturbations. Furthermore, the cross-correlation between all voltage magnitude pairs generally increases prior to and beyond the Hopf bifurcation point, indicating "critical coupling," but cannot provide early warning indications. Finally, we show that the established early warning indicators are oblivious to limit-induced bifurcations and, in the case of the power system model considered here, only react to an approaching Hopf bifurcation.
Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko
2014-02-01
Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively
Ma, Junhai; Ren, Wenbo; Zhan, Xueli
2017-04-01
Based on the study of scholars at home and abroad, this paper improves the three-dimensional IS-LM model in macroeconomics, analyzes the equilibrium point of the system and stability conditions, focuses on the parameters and complex dynamic characteristics when Hopf bifurcation occurs in the three-dimensional IS-LM macroeconomics system. In order to analyze the stability of limit cycles when Hopf bifurcation occurs, this paper further introduces the first Lyapunov coefficient to judge the limit cycles, i.e. from a practical view of the business cycle. Numerical simulation results show that within the range of most of the parameters, the limit cycle of 3D IS-LM macroeconomics is stable, that is, the business cycle is stable; with the increase of the parameters, limit cycles becomes unstable, and the value range of the parameters in this situation is small. The research results of this paper have good guide significance for the analysis of macroeconomics system.
Complexified dynamical systems
International Nuclear Information System (INIS)
Bender, Carl M; Holm, Darryl D; Hook, Daniel W
2007-01-01
Many dynamical systems, such as the Lotka-Volterra predator-prey model and the Euler equations for the free rotation of a rigid body, are PT symmetric. The standard and well-known real solutions to such dynamical systems constitute an infinitessimal subclass of the full set of complex solutions. This paper examines a subset of the complex solutions that contains the real solutions, namely those having PT symmetry. The condition of PT symmetry selects out complex solutions that are periodic. (fast track communication)
SPASER as a complex system: femtosecond dynamics traced by ab-initio simulations
Gongora, J. S. Totero; Miroshnichenko, Andrey E.; Kivshar, Yuri S.; Fratalocchi, Andrea
2016-01-01
Integrating coherent light sources at the nanoscale with spasers is one of the most promising applications of plasmonics. A spaser is a nano-plasmonic counterpart of a laser, with photons replaced by surface plasmon polaritons and the resonant cavity replaced by a nanoparticle supporting localized plasmonic modes. Despite the large body of experimental and theoretical studies, the understanding of the fundamental properties of the spaser emission is still challenging. In this work, we investigated the ultrafast dynamics of the emission from a core-shell spaser by developing a rigorous first-principle numerical model. Our results show that the spaser is a highly nonlinear system with many interacting degrees of freedom, whose emission sustain a rich manifold of different spatial phases. In the regime of strong interaction we observed that the spaser emission manifests an irreversible ergodic evolution, where energy is equally shared among all the available degrees of freedom. Under this condition, the spaser generates ultrafast vortex lasing modes that are spinning on the femtosecond scale, acquiring the character of a nanoparticle with an effective spin. Interestingly, the spin orientation is defined by spontaneous symmetry breaking induced by quantum noise, which is a fundamental component of our ab-initio model. This opens up interesting possibilities of achieving unidirectional emission from a perfectly spherical nanoparticle, stimulating a broad range of applications for nano-plasmonic lasers as unidirectional couplers, random information sources and novel form of photonics neural-networks. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
SPASER as a complex system: femtosecond dynamics traced by ab-initio simulations
Gongora, J. S. Totero
2016-03-14
Integrating coherent light sources at the nanoscale with spasers is one of the most promising applications of plasmonics. A spaser is a nano-plasmonic counterpart of a laser, with photons replaced by surface plasmon polaritons and the resonant cavity replaced by a nanoparticle supporting localized plasmonic modes. Despite the large body of experimental and theoretical studies, the understanding of the fundamental properties of the spaser emission is still challenging. In this work, we investigated the ultrafast dynamics of the emission from a core-shell spaser by developing a rigorous first-principle numerical model. Our results show that the spaser is a highly nonlinear system with many interacting degrees of freedom, whose emission sustain a rich manifold of different spatial phases. In the regime of strong interaction we observed that the spaser emission manifests an irreversible ergodic evolution, where energy is equally shared among all the available degrees of freedom. Under this condition, the spaser generates ultrafast vortex lasing modes that are spinning on the femtosecond scale, acquiring the character of a nanoparticle with an effective spin. Interestingly, the spin orientation is defined by spontaneous symmetry breaking induced by quantum noise, which is a fundamental component of our ab-initio model. This opens up interesting possibilities of achieving unidirectional emission from a perfectly spherical nanoparticle, stimulating a broad range of applications for nano-plasmonic lasers as unidirectional couplers, random information sources and novel form of photonics neural-networks. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nigenda, Gustavo; González-Robledo, Luz María; Juárez-Ramírez, Clara; Adam, Taghreed
2016-05-13
In 2003, Mexico's Seguro Popular de Salud (SPS), was launched as an innovative financial mechanism implemented to channel new funds to provide health insurance to 50 million Mexicans and to reduce systemic financial inequities. The objective of this article is to understand the complexity and dynamics that contributed to the adaptation of the policy in the implementation stage, how these changes occurred, and why, from a complex and adaptive systems perspective. A complex adaptive systems (CAS) framework was used to carry out a secondary analysis of data obtained from four SPS's implementation evaluations. We first identified key actors, their roles, incentives and power, and their responses to the policy and guidelines. We then developed a causal loop diagram to disentangle the feedback dynamics associated with the modifications of the policy implementation which we then analyzed using a CAS perspective. Implementation variations were identified in seven core design features during the first 10 years of implementation period, and in each case, the SPS's central coordination introduced modifications in response to the reactions of the different actors. We identified several CAS phenomena associated with these changes including phase transitions, network emergence, resistance to change, history dependence, and feedback loops. Our findings generate valuable lessons to policy implementation processes, especially those involving a monetary component, where the emergence of coping mechanisms and other CAS phenomena inevitably lead to modifications of policies and their interpretation by those who implement them. These include the difficulty of implementing strategies that aim to pool funds through solidarity among beneficiaries where the rich support the poor when there are no incentives for the rich to do so. Also, how resistance to change and history dependence can pose significant challenges to implementing changes, where the local actors use their significant power
Gromek, Katherine Emily
A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.
Cognitive dynamics: complexity and creativity
Energy Technology Data Exchange (ETDEWEB)
Arecchi, F Tito [Dipartimento di Fisica, Universita di Firenze (Italy); Istituto Nazionale di Ottica Applicata, Florence (Italy)
2007-05-15
A scientific problem described within a given code is mapped by a corresponding computational problem. We call (algorithmic) complexity the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical system making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses. We call creativity the action of code changing, which is guided by hints not formalized within the previous code, whence not accessible to a computer. We call semantic complexity the number of different scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the context. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path towards a model building. Since this is a report on work in progress, we skip technicalities in order to stress the gist of the question, and provide
Cognitive dynamics: complexity and creativity
International Nuclear Information System (INIS)
Arecchi, F Tito
2007-01-01
A scientific problem described within a given code is mapped by a corresponding computational problem. We call (algorithmic) complexity the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical system making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses. We call creativity the action of code changing, which is guided by hints not formalized within the previous code, whence not accessible to a computer. We call semantic complexity the number of different scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the context. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path towards a model building. Since this is a report on work in progress, we skip technicalities in order to stress the gist of the question, and provide
Complex networks: Dynamics and security
Indian Academy of Sciences (India)
This paper presents a perspective in the study of complex networks by focusing on how dynamics may affect network security under attacks. ... Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona 85287, USA; Institute of Mathematics and Computer Science, University of Sao Paulo, Brazil ...
Product development projects dynamics and emergent complexity
Schlick, Christopher
2016-01-01
This book primarily explores two topics: the representation of simultaneous, cooperative work processes in product development projects with the help of statistical models, and the assessment of their emergent complexity using a metric from theoretical physics (Effective Measure Complexity, EMC). It is intended to promote more effective management of development projects by shifting the focus from the structural complexity of the product being developed to the dynamic complexity of the development processes involved. The book is divided into four main parts, the first of which provides an introduction to vector autoregression models, periodic vector autoregression models and linear dynamical systems for modeling cooperative work in product development projects. The second part presents theoretical approaches for assessing complexity in the product development environment, while the third highlights and explains closed-form solutions for the complexity metric EMC for vector autoregression models and linear dyn...
Improving the Complexity of the Lorenz Dynamics
Directory of Open Access Journals (Sweden)
María Pilar Mareca
2017-01-01
Full Text Available A new four-dimensional, hyperchaotic dynamic system, based on Lorenz dynamics, is presented. Besides, the most representative dynamics which may be found in this new system are located in the phase space and are analyzed here. The new system is especially designed to improve the complexity of Lorenz dynamics, which, despite being a paradigm to understand the chaotic dissipative flows, is a very simple example and shows great vulnerability when used in secure communications. Here, we demonstrate the vulnerability of the Lorenz system in a general way. The proposed 4D system increases the complexity of the Lorenz dynamics. The trajectories of the novel system include structures going from chaos to hyperchaos and chaotic-transient solutions. The symmetry and the stability of the proposed system are also studied. First return maps, Poincaré sections, and bifurcation diagrams allow characterizing the global system behavior and locating some coexisting structures. Numerical results about the first return maps, Poincaré cross sections, Lyapunov spectrum, and Kaplan-Yorke dimension demonstrate the complexity of the proposed equations.
Mechanisms and dynamics of cooperation and competition emergence in complex networked systems
Gianetto, David A.
Cooperative behavior is a pervasive phenomenon in human interactions and yet how it can evolve and become established, through the selfish process of natural selection, is an enduring puzzle. These behaviors emerge when agents interact in a structured manner; even so, the key structural factors that affect cooperation are not well understood. Moreover, the literature often considers cooperation a single attribute of primitive agents who do not react to environmental changes but real-world actors are more perceptive. The present work moves beyond these assumptions by evolving more realistic game participants, with memories of the past, on complex networks. Agents play repeated games with a three-part Markovian strategy that allows us to separate the cooperation phenomenon into trust, reciprocity, and forgiveness characteristics. Our results show that networks matter most when agents gain the most by acting in a selfish manner, irrespective of how much they may lose by cooperating; since the context provided by neighborhoods inhibits greedy impulses that agents otherwise succumb to in isolation. Network modularity is the most important driver of cooperation emergence in these high-stakes games. However, modularity fails to tell the complete story. Modular scale-free graphs impede cooperation when close coordination is required, partially due to the acyclic nature of scale-free network models. To achieve the highest cooperation in diverse social conditions, both high modularity, low connectivity within modules, and a rich network of long cycles become important. With these findings in hand, we study the influence of networks on coordination and competition within the federal health care insurance exchange. In this applied study, we show that systemic health care coordination is encouraged by the emergent insurance network. The network helps underpin the viability of the exchange and provides an environment of stronger competition once a critical-mass of insurers have
International Nuclear Information System (INIS)
Chang, Y.H.J.; Mosleh, A.
2007-01-01
This is the last in a series of five papers that discuss the Information Decision and Action in Crew (IDAC) context for human reliability analysis (HRA) and example application. The model is developed to probabilistically predict the responses of the control room operating crew in nuclear power plants during an accident, for use in probabilistic risk assessments (PRA). The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper describes a dynamic PRA computer simulation program, accident dynamics simulator (ADS), developed in part to implement the IDAC model. This paper also provides a detailed example of implementing a simpler version of IDAC, compared with the IDAC model discussed in the first four papers of this series, to demonstrate the practicality of integrating a detailed cognitive HRA model within a dynamic PRA framework
Hassmiller Lich, Kristen; Urban, Jennifer Brown; Frerichs, Leah; Dave, Gaurav
2017-02-01
Group concept mapping (GCM) has been successfully employed in program planning and evaluation for over 25 years. The broader set of systems thinking methodologies (of which GCM is one), have only recently found their way into the field. We present an overview of systems thinking emerging from a system dynamics (SD) perspective, and illustrate the potential synergy between GCM and SD. As with GCM, participatory processes are frequently employed when building SD models; however, it can be challenging to engage a large and diverse group of stakeholders in the iterative cycles of divergent thinking and consensus building required, while maintaining a broad perspective on the issue being studied. GCM provides a compelling resource for overcoming this challenge, by richly engaging a diverse set of stakeholders in broad exploration, structuring, and prioritization. SD provides an opportunity to extend GCM findings by embedding constructs in a testable hypothesis (SD model) describing how system structure and changes in constructs affect outcomes over time. SD can be used to simulate the hypothesized dynamics inherent in GCM concept maps. We illustrate the potential of the marriage of these methodologies in a case study of BECOMING, a federally-funded program aimed at strengthening the cross-sector system of care for youth with severe emotional disturbances. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Zhang, Xiulan; Bloom, Gerald; Xu, Xiaoxin; Chen, Lin; Liang, Xiaoyun; Wolcott, Sara J
2014-08-26
This paper explores the evolution of schemes for rural finance in China as a case study of the long and complex process of health system development. It argues that the evolution of these schemes has been the outcome of the response of a large number of agents to a rapidly changing context and of efforts by the government to influence this adaptation process and achieve public health goals. The study draws on several sources of data including a review of official policy documents and academic papers and in-depth interviews with key policy actors at national level and at a sample of localities. The study identifies three major transition points associated with changes in broad development strategy and demonstrates how the adaptation of large numbers of actors to these contextual changes had a major impact on the performance of the health system. Further, it documents how the Ministry of Health viewed its role as both an advocate for the interests of health facilities and health workers and as the agency responsible for ensuring that government health system objectives were met. It is argued that a major reason for the resilience of the health system and its ability to adapt to rapid economic and institutional change was the ability of the Ministry to provide overall strategy leadership. Additionally, it postulates that a number of interest groups have emerged, which now also seek to influence the pathway of health system development. This history illustrates the complex and political nature of the management of health system development and reform. The paper concludes that governments will need to increase their capacity to analyze the health sector as a complex system and to manage change processes.
Lasagabaster, David
2017-01-01
This paper describes a two-month longitudinal study in which five secondary education students learning English as a foreign language at school will be interviewed in order to analyse how their motivation varies during this period and what variables affect their motivational changes. The emphasis will thus be on motivation's dynamicity and…
Inferring network topology from complex dynamics
International Nuclear Information System (INIS)
Shandilya, Srinivas Gorur; Timme, Marc
2011-01-01
Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.
Dynamic behavior of polydisperse dust system in cryogenic gas discharge complex plasmas
Antipov, S.N.; Schepers, L.P.T.; Vasiliev, M.M.; Petrov, O.F.
2016-01-01
Complex (dusty) plasmas of micron-sized CeO2 polydisperse particles in dc glow discharges at 77 and ∼ 10 K were experimentally investigated. It was obtained that dust structure in cryogenic gas discharge plasma can be a mixture of two fractions (components) with completely different dust ordering
DEFF Research Database (Denmark)
Butts, Michael; Drews, Martin; Larsen, Morten Andreas Dahl
2014-01-01
the atmosphere and the groundwater via the land surface and can represent the lateral movement of water in both the surface and subsurface and their interactions, not normally accounted for in climate models. Meso-scale processes are important for climate in general and rainfall in particular. Hydrological......To improve our understanding of the impacts of feedback between the atmosphere and the terrestrial water cycle including groundwater and to improve the integration of water resource management modelling for climate adaption we have developed a dynamically coupled climate–hydrological modelling...... impacts are assessed at the catchment scale, the most important scale for water management. Feedback between groundwater, the land surface and the atmosphere occurs across a range of scales. Recognising this, the coupling was developed to allow dynamic exchange of water and energy at the catchment scale...
Odille, Fabrice G J; Jónsson, Stefán; Stjernqvist, Susann; Rydén, Tobias; Wärnmark, Kenneth
2007-01-01
A general mathematical model for the characterization of the dynamic (kinetically labile) association of supramolecular assemblies in solution is presented. It is an extension of the equal K (EK) model by the stringent use of linear algebra to allow for the simultaneous presence of an unlimited number of different units in the resulting assemblies. It allows for the analysis of highly complex dynamic equilibrium systems in solution, including both supramolecular homo- and copolymers without the recourse to extensive approximations, in a field in which other analytical methods are difficult. The derived mathematical methodology makes it possible to analyze dynamic systems such as supramolecular copolymers regarding for instance the degree of polymerization, the distribution of a given monomer in different copolymers as well as its position in an aggregate. It is to date the only general means to characterize weak supramolecular systems. The model was fitted to NMR dilution titration data by using the program Matlab, and a detailed algorithm for the optimization of the different parameters has been developed. The methodology is applied to a case study, a hydrogen-bonded supramolecular system, salen 4+porphyrin 5. The system is formally a two-component system but in reality a three-component system. This results in a complex dynamic system in which all monomers are associated to each other by hydrogen bonding with different association constants, resulting in homo- and copolymers 4n5m as well as cyclic structures 6 and 7, in addition to free 4 and 5. The system was analyzed by extensive NMR dilution titrations at variable temperatures. All chemical shifts observed at different temperatures were used in the fitting to obtain the DeltaH degrees and DeltaS degrees values producing the best global fit. From the derived general mathematical expressions, system 4+5 could be characterized with respect to above-mentioned parameters.
Complex Systems: An Introduction
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...
Energy Technology Data Exchange (ETDEWEB)
Woo, Tae Ho [Seoul National Univ. (Korea, Republic of). Dept. of Nuclear Engineering
2012-07-15
The power stabilization of the nuclear power plants (NPPs) is investigated in the aspect of the liquid metal coolant. The quantification of the risk analysis is performed by the system dynamics (SD) method which is processed by the feedback and accumulation complex algorithms. The Vensim software package is used for the simulations, which is supported by the Monte-Carlo method. There are 2 kinds of considerations as the economic and safety properties. The result shows the stability of the operations when the power can be decided. This shows the higher efficiency of the reactor. The failure frequency is 16/60 = 27%. In the event of Power Stabilized, the failure event is in the quite lower frequency rate. The commercial use of the reactor is important in the operations. (orig.)
Parisi, Alessandro; Argentiero, Ilenia; Fidelibus, Maria Dolores; Pellicani, Roberta; Spilotro, Giuseppe
2017-04-01
Considering a natural system without human-induced modifications, its resilience can be altered by many natural drivers (e.g. geological characteristics, climate) and their spatial modifications over time. Therefore, natural hazardous phenomena could shift natural system over tipping points in an easier or more difficult way. So long as natural system does not involve human settlements or transport infrastructures, natural system risk assessment could not be a basic topic. Nowadays, human activities have modified many natural systems forming, as a result, hybrid systems (both human and natural), in which natural and human-induced drivers modify hybrid systems vulnerability in order to decrease or increase their resilience: scientists define this new age Anthropocene. In this context, dynamic risk assessment of hybrid systems is required in order to avoid disaster when hazardous phenomena occur, but it is a quite complex issue. In fact, soft crisis emerging signals are difficult to identify because of wrong risk perception and lack of communication. Furthermore, natural and human-induced modifications are rarely registered and supervised by governments, so it is fairly difficult defining how systems resilience changes over time. Inhabitants of Ginosa (Taranto, South of Italy) had modified many old rock dwellings over thousand years since the Middle Ages. Indeed, they had built up three-storey houses on three hypogeum levels of rock dwellings along the ravine. The Matrice street collapse in Ginosa is an example of how natural and human-induced spatial modifications over time had led a soft crisis to evolve in a disaster, fortunately without fatalities. This research aim is to revisit events before the Matrice street collapse on the 21st January 2014. The will is to define the relationship between the hybrid system resilience and soft crisis variation over time and how human and natural drivers were involved in the shift.
Sels, Dries; Brosens, Fons
2013-10-01
The equation of motion for the reduced Wigner function of a system coupled to an external quantum system is presented for the specific case when the external quantum system can be modeled as a set of harmonic oscillators. The result is derived from the Wigner function formulation of the Feynman-Vernon influence functional theory. It is shown how the true self-energy for the equation of motion is connected with the influence functional for the path integral. Explicit expressions are derived in terms of the bare Wigner propagator. Finally, we show under which approximations the resulting equation of motion reduces to the Wigner-Boltzmann equation.
Simulations of Unsteady Effects and Dynamic Responses in Complex Valve Systems, Phase I
National Aeronautics and Space Administration — CFD based analyses are playing an increasingly important role in supporting experimental testing of rocket propulsion systems. The focus of this proposal is towards...
Adaptive learning and complex dynamics
International Nuclear Information System (INIS)
Gomes, Orlando
2009-01-01
In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.
On delta-modulated control: A simple system with complex dynamics
Energy Technology Data Exchange (ETDEWEB)
Xia Xiaohua [Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002 (South Africa)]. E-mail: xxia@postino.up.ac.za; Chen Guanrong [Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong (China)]. E-mail: gchen@ee.cityu.edu.hk
2007-08-15
In this paper, we investigate some interesting properties of a scalar system controlled by {delta}-modulated feedback. We show that there are three different cases. In the first case, there is a minimal global attractor which consists of only two points. The two points form either one 2-periodic orbit or two 1-periodic orbits (fixed points). We also characterize the attracting region for each of these two points. In the second case, the maximal stabilizable region is bounded, and there is a minimal local attractor inside this stabilizable region. In the third case, the maximal stabilizable set is a Cantor set, which is a repeller of the system, and the system is chaotic on the Cantor set.
Symbolic Dynamics and Grammatical Complexity
Hao, Bai-Lin; Zheng, Wei-Mou
The following sections are included: * Formal Languages and Their Complexity * Formal Language * Chomsky Hierarchy of Grammatical Complexity * The L-System * Regular Language and Finite Automaton * Finite Automaton * Regular Language * Stefan Matrix as Transfer Function for Automaton * Beyond Regular Languages * Feigenbaum and Generalized Feigenbaum Limiting Sets * Even and Odd Fibonacci Sequences * Odd Maximal Primitive Prefixes and Kneading Map * Even Maximal Primitive Prefixes and Distinct Excluded Blocks * Summary of Results
Varlataya, S. K.; Evdokimov, V. E.; Urzov, A. Y.
2017-11-01
This article describes a process of calculating a certain complex information security system (CISS) reliability using the example of the technospheric security management model as well as ability to determine the frequency of its maintenance using the system reliability parameter which allows one to assess man-made risks and to forecast natural and man-made emergencies. The relevance of this article is explained by the fact the CISS reliability is closely related to information security (IS) risks. Since reliability (or resiliency) is a probabilistic characteristic of the system showing the possibility of its failure (and as a consequence - threats to the protected information assets emergence), it is seen as a component of the overall IS risk in the system. As it is known, there is a certain acceptable level of IS risk assigned by experts for a particular information system; in case of reliability being a risk-forming factor maintaining an acceptable risk level should be carried out by the routine analysis of the condition of CISS and its elements and their timely service. The article presents a reliability parameter calculation for the CISS with a mixed type of element connection, a formula of the dynamics of such system reliability is written. The chart of CISS reliability change is a S-shaped curve which can be divided into 3 periods: almost invariable high level of reliability, uniform reliability reduction, almost invariable low level of reliability. Setting the minimum acceptable level of reliability, the graph (or formula) can be used to determine the period of time during which the system would meet requirements. Ideally, this period should not be longer than the first period of the graph. Thus, the proposed method of calculating the CISS maintenance frequency helps to solve a voluminous and critical task of the information assets risk management.
Rapid Mission Design for Dynamically Complex Environments
National Aeronautics and Space Administration — Designing trajectories in dynamically complex environments is very challenging and easily becomes an intractable problem. More complex planning implies potentially...
Directory of Open Access Journals (Sweden)
Mehdi Alirezaei
2017-01-01
Full Text Available Road accidents have the highest externality costs to society and to the economy, even when compared to the externality damages associated with air emissions and oil dependency. Road safety is one of the most complicated topics, which involves many interdependencies, and so, a sufficiently thorough analysis of roadway safety will require a novel system-based approach in which the associated feedback relationships and causal effects are given appropriate consideration. The factors affecting accident frequency and severity are highly dependent on economic parameters, environmental factors and weather conditions. In this study, we try to use a system dynamics modeling approach to model the climate change-road safety-economy nexus, thereby investigating the complex interactions among these important areas by tracking how they affect each other over time. For this purpose, five sub-models are developed to model each aspect of the overall nexus and to interact with each other to simulate the overall system. As a result, this comprehensive model can provide a platform for policy makers to test the effectiveness of different policy scenarios to reduce the negative consequences of traffic accidents and improve road safety.
Aedes ægypti control in urban areas: A systemic approach to a complex dynamic.
Carvalho, Marilia Sá; Honorio, Nildimar Alves; Garcia, Leandro Martin Totaro; Carvalho, Luiz Carlos de Sá
2017-07-01
The available strategy for controlling the diseases transmitted by Aedes ægypti (dengue fever, Zika, and chikungunya) relies on continued community participation. Despite slogans emphasizing how easy it should be, no country has achieved it since the seventies. To better investigate potentially sustainable interventions, we developed a systemic model based on a multidisciplinary approach, integrating as deeply as possible specialized knowledge and field experience. The resulting model is composed of 4 external and 8 internal subsystems and 31 relationships, consistent with the literature and checked over multiple iterations with specialists of the many areas. We analyzed the model and the main feedback loops responsible for the system's stability, searching for possible interventions that could shift the existing balance. We suggest the introduction of 1 more player, the local primary health care structure, with the potential to change the undesired equilibrium. The health agents in the areas are the first to detect disease cases, and they could stimulate individuals to inform about potential mosquitoes' breeding sites and bring timely information to the vector-control program. Triggering such an action could introduce changes in people's attitude through a positive feedback loop in the desired direction.
Dynamics of a complex quantum magnet
International Nuclear Information System (INIS)
Landry, James W.; Coppersmith, S. N.
2003-01-01
We have computed the low energy quantum states and low frequency dynamical susceptibility of complex quantum spin systems in the limit of strong interactions, obtaining exact results for system sizes enormously larger than accessible previously. The ground state is a complex superposition of a substantial fraction of all the classical ground states, and yet the dynamical susceptibility exhibits sharp resonances reminiscent of the behavior of single spins. These results show that strongly interacting quantum systems can organize to generate coherent excitations and shed light on recent experiments demonstrating that coherent excitations are present in a disordered spin liquid. The dependence of the energy spectra on system size differs qualitatively from that of the energy spectra of random undirected bipartite graphs with similar statistics, implying that strong interactions are giving rise to these unusual spectral properties
Samanta, Sudipta; Mukherjee, Sanchita
2018-01-28
The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.
Samanta, Sudipta; Mukherjee, Sanchita
2018-01-01
The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.
Stamovlasis, Dimitrios; Vaiopoulou, Julie
2017-07-01
The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.
Forecasting in Complex Systems
Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.
2014-12-01
Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification
How complex a dynamical network can be?
International Nuclear Information System (INIS)
Baptista, M.S.; Kakmeni, F. Moukam; Del Magno, Gianluigi; Hussein, M.S.
2011-01-01
Positive Lyapunov exponents measure the asymptotic exponential divergence of nearby trajectories of a dynamical system. Not only they quantify how chaotic a dynamical system is, but since their sum is an upper bound for the rate of information production, they also provide a convenient way to quantify the complexity of a dynamical network. We conjecture based on numerical evidences that for a large class of dynamical networks composed by equal nodes, the sum of the positive Lyapunov exponents is bounded by the sum of all the positive Lyapunov exponents of both the synchronization manifold and its transversal directions, the last quantity being in principle easier to compute than the latter. As applications of our conjecture we: (i) show that a dynamical network composed of equal nodes and whose nodes are fully linearly connected produces more information than similar networks but whose nodes are connected with any other possible connecting topology; (ii) show how one can calculate upper bounds for the information production of realistic networks whose nodes have parameter mismatches, randomly chosen; (iii) discuss how to predict the behavior of a large dynamical network by knowing the information provided by a system composed of only two coupled nodes.
Mitchell, Christine M.
1993-01-01
This chapter examines a class of human-computer interaction applications, specifically the design of human-computer interaction for the operators of complex systems. Such systems include space systems (e.g., manned systems such as the Shuttle or space station, and unmanned systems such as NASA scientific satellites), aviation systems (e.g., the flight deck of 'glass cockpit' airplanes or air traffic control) and industrial systems (e.g., power plants, telephone networks, and sophisticated, e.g., 'lights out,' manufacturing facilities). The main body of human-computer interaction (HCI) research complements but does not directly address the primary issues involved in human-computer interaction design for operators of complex systems. Interfaces to complex systems are somewhat special. The 'user' in such systems - i.e., the human operator responsible for safe and effective system operation - is highly skilled, someone who in human-machine systems engineering is sometimes characterized as 'well trained, well motivated'. The 'job' or task context is paramount and, thus, human-computer interaction is subordinate to human job interaction. The design of human interaction with complex systems, i.e., the design of human job interaction, is sometimes called cognitive engineering.
Complex Human Dynamics From Mind to Societies
Winkowska-Nowak, Katarzyna; Brée, David
2013-01-01
This book, edited and authored by a closely collaborating network of social scientists and psychologists, recasts typical research topics in these fields into the language of nonlinear, dynamic and complex systems. The aim is to provide scientists with different backgrounds - physics, applied mathematics and computer sciences - with the opportunity to apply the tools of their trade to an altogether new range of possible applications. At the same time, this book will serve as a first reference for a new generation of social scientists and psychologists wishing to familiarize themselves with the new methodology and the "thinking in complexity".
Complex Systems and Dependability
Zamojski, Wojciech; Sugier, Jaroslaw
2012-01-01
Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth
2013-01-01
This book offers a comprehensive picture of nonequilibrium phenomena in nanoscale systems. Written by internationally recognized experts in the field, this book strikes a balance between theory and experiment, and includes in-depth introductions to nonequilibrium fluctuation relations, nonlinear dynamics and transport, single molecule experiments, and molecular diffusion in nanopores. The authors explore the application of these concepts to nano- and biosystems by cross-linking key methods and ideas from nonequilibrium statistical physics, thermodynamics, stochastic theory, and dynamical s
Symbolic dynamics and description of complexity
International Nuclear Information System (INIS)
Hao Bailin.
1992-10-01
Symbolic dynamics provides a general framework to describe complexity of dynamical behaviour. After a discussion of the state of the filed special emphasis will be made on the role of transfer matrix (the Stefan matrix) both in deriving the grammar from known symbolic dynamics and in extracting the rules from experimental data. The block structure of the Stefan matrix may serve as another indicator of complexity of the associated dynamics. (author). 33 refs, 6 figs
Jeong, Bongwon; Cho, Hanna; Keum, Hohyun; Kim, Seok; Michael McFarland, D; Bergman, Lawrence A; King, William P; Vakakis, Alexander F
2014-11-21
Intentional utilization of geometric nonlinearity in micro/nanomechanical resonators provides a breakthrough to overcome the narrow bandwidth limitation of linear dynamic systems. In past works, implementation of intentional geometric nonlinearity to an otherwise linear nano/micromechanical resonator has been successfully achieved by local modification of the system through nonlinear attachments of nanoscale size, such as nanotubes and nanowires. However, the conventional fabrication method involving manual integration of nanoscale components produced a low yield rate in these systems. In the present work, we employed a transfer-printing assembly technique to reliably integrate a silicon nanomembrane as a nonlinear coupling component onto a linear dynamic system with two discrete microcantilevers. The dynamics of the developed system was modeled analytically and investigated experimentally as the coupling strength was finely tuned via FIB post-processing. The transition from the linear to the nonlinear dynamic regime with gradual change in the coupling strength was experimentally studied. In addition, we observed for the weakly coupled system that oscillation was asynchronous in the vicinity of the resonance, thus exhibiting a nonlinear complex mode. We conjectured that the emergence of this nonlinear complex mode could be attributed to the nonlinear damping arising from the attached nanomembrane.
Metrical and dynamical aspects in complex analysis
2017-01-01
The central theme of this reference book is the metric geometry of complex analysis in several variables. Bridging a gap in the current literature, the text focuses on the fine behavior of the Kobayashi metric of complex manifolds and its relationships to dynamical systems, hyperbolicity in the sense of Gromov and operator theory, all very active areas of research. The modern points of view expressed in these notes, collected here for the first time, will be of interest to academics working in the fields of several complex variables and metric geometry. The different topics are treated coherently and include expository presentations of the relevant tools, techniques and objects, which will be particularly useful for graduate and PhD students specializing in the area.
Complex dynamical invariants for two-dimensional complex potentials
Indian Academy of Sciences (India)
Abstract. Complex dynamical invariants are searched out for two-dimensional complex poten- tials using rationalization method within the framework of an extended complex phase space characterized by x = x1 + ip3, y = x2 + ip4, px = p1 + ix3, py = p2 + ix4. It is found that the cubic oscillator and shifted harmonic oscillator ...
Directory of Open Access Journals (Sweden)
Shunyi Li
2013-01-01
Full Text Available A predator-prey system with generalized group defense and impulsive control strategy is investigated. By using Floquet theorem and small amplitude perturbation skills, a local asymptotically stable prey-eradication periodic solution is obtained when the impulsive period is less than some critical value. Otherwise, the system is permanent if the impulsive period is larger than the critical value. By using bifurcation theory, we show the existence and stability of positive periodic solution when the pest eradication lost its stability. Numerical examples show that the system considered has more complicated dynamics, including (1 high-order quasiperiodic and periodic oscillation, (2 period-doubling and halving bifurcation, (3 nonunique dynamics (meaning that several attractors coexist, and (4 chaos and attractor crisis. Further, the importance of the impulsive period, the released amount of mature predators and the degree of group defense effect are discussed. Finally, the biological implications of the results and the impulsive control strategy are discussed.
Random complex dynamics and devil's coliseums
Sumi, Hiroki
2015-04-01
We investigate the random dynamics of polynomial maps on the Riemann sphere \\hat{\\Bbb{C}} and the dynamics of semigroups of polynomial maps on \\hat{\\Bbb{C}} . In particular, the dynamics of a semigroup G of polynomials whose planar postcritical set is bounded and the associated random dynamics are studied. In general, the Julia set of such a G may be disconnected. We show that if G is such a semigroup, then regarding the associated random dynamics, the chaos of the averaged system disappears in the C0 sense, and the function T∞ of probability of tending to ∞ \\in \\hat{\\Bbb{C}} is Hölder continuous on \\hat{\\Bbb{C}} and varies only on the Julia set of G. Moreover, the function T∞ has a kind of monotonicity. It turns out that T∞ is a complex analogue of the devil's staircase, and we call T∞ a ‘devil’s coliseum'. We investigate the details of T∞ when G is generated by two polynomials. In this case, T∞ varies precisely on the Julia set of G, which is a thin fractal set. Moreover, under this condition, we investigate the pointwise Hölder exponents of T∞.
Complex logistics audit system
Directory of Open Access Journals (Sweden)
Zuzana Marková
2010-02-01
Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.
International Nuclear Information System (INIS)
Andersen, V.; Andersen, H.B.; Axel, E.; Petersen, T.
1990-01-01
A short introduction will be given to the European (ESPRIT II) project, ''IT Support for Emergency Management - ISEM''. The project is aimed at the development of an integrated information system capable of supporting the complex, dynamic, distributed decision making in the management of emergencies. The basic models developed to describe and construct emergency management organisations and their preparedness have been illustrated, and it has been stated that similarities may be found even in emergency situations that originally are of quite different nature. (author)
Team dynamics in complex projects
Oeij, P.; Vroome, E.E.M. de; Dhondt, S.; Gaspersz, J.B.R.
2012-01-01
Complexity of projects is hotly debated and a factor which affects innovativeness of team performance. Much attention in the past is paid to technical complexity and many issues are related to natural and physical sciences. A growing awareness of the importance of socioorganisational issues is
Encyclopedia of Complexity and Systems Science
Meyers, Robert A
2009-01-01
Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...
Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics
Chen, Yu-Zhong; Lai, Ying-Cheng
2018-03-01
Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.
A weed-crop complex in sorghum: The dynamics of genetic diversity in a traditional farming system.
Barnaud, Adeline; Deu, Monique; Garine, Eric; Chantereau, Jacques; Bolteu, Justin; Koïda, Esaei Ouin; McKey, Doyle; Joly, Hélène I
2009-10-01
Despite the major ecological and economic impacts of gene flow between domesticated plants and their wild relatives, many aspects of the process, particularly the relative roles of natural and human selection in facilitating or constraining gene flow, are still poorly understood. We developed a multidisciplinary approach, involving both biologists and social scientists, to investigate the dynamics of genetic diversity of a sorghum weed-crop complex in a village of Duupa farmers in northern Cameroon. Farmers distinguish a gradient from weedy morphotypes (naa baa see, haariya, and genkiya) to domesticated morphotypes; haariya and genkiya have intermediate morphological traits. We investigated the pattern of diversity in this complex using both morphological and genetic data. Our biological results are interpreted in the light of data on farmers' taxonomy and practices such as spatial pattern of planting and plant selection. Both morphological and genetic data are congruent with farmers' taxonomy and confirm the introgressed status of intermediate weedy morphotypes. Farmers actively select against weedy morphotypes, but several practices unconsciously favor gene flow. Furthermore, haariya and genkiya may facilitate introgression between naa baa see and domesticated morphotypes by virtue of their intermediate flowering period and their mode of management by farmers.
International Nuclear Information System (INIS)
Liu Xianning; Chen Lansun
2003-01-01
This paper develops the Holling type II Lotka-Volterra predator-prey system, which may inherently oscillate, by introducing periodic constant impulsive immigration of predator. Condition for the system to be extinct is given and permanence condition is established via the method of comparison involving multiple Liapunov functions. Further influences of the impulsive perturbations on the inherent oscillation are studied numerically, which shows that with the increasing of the amount of the immigration, the system experiences process of quasi-periodic oscillating→cycles→periodic doubling cascade→chaos→periodic halfing cascade→cycles, which is characterized by (1) quasi-periodic oscillating, (2) period doubling, (3) period halfing, (4) non-unique dynamics, meaning that several attractors coexist
Emergence in Dynamical Systems
Directory of Open Access Journals (Sweden)
John Collier
2013-12-01
Full Text Available Emergence is a term used in many contexts in current science; it has become fashionable. It has a traditional usage in philosophy that started in 1875 and was expanded by J. S. Mill (earlier, under a different term and C. D. Broad. It is this form of emergence that I am concerned with here. I distinguish it from uses like ‘computational emergence,’ which can be reduced to combinations of program steps, or its application to merely surprising new features that appear in complex combinations of parts. I will be concerned specifically with ontological emergence that has the logical properties required by Mill and Broad (though there might be some quibbling about the details of their views. I restrict myself to dynamical systems that are embodied in processes. Everything that we can interact with through sensation or action is either dynamical or can be understood in dynamical terms, so this covers all comprehensible forms of emergence in the strong (nonreducible sense I use. I will give general dynamical conditions that underlie the logical conditions traditionally assigned to emergence in nature.The advantage of this is that, though we cannot test logical conditions directly, we can test dynamical conditions. This gives us an empirical and realistic form of emergence, contrary those who say it is a matter of perspective.
Exponential rise of dynamical complexity in quantum computing through projections.
Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya
2014-10-10
The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.
Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo
2001-01-01
The world of artificial systems is reaching complexity levels that es cape human understanding. Surface traffic, electricity distribution, air planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...
Dynamic complexity: plant receptor complexes at the plasma membrane.
Burkart, Rebecca C; Stahl, Yvonne
2017-12-01
Plant receptor complexes at the cell surface perceive many different external and internal signalling molecules and relay these signals into the cell to regulate development, growth and immunity. Recent progress in the analyses of receptor complexes using different live cell imaging approaches have shown that receptor complex formation and composition are dynamic and take place at specific microdomains at the plasma membrane. In this review we focus on three prominent examples of Arabidopsis thaliana receptor complexes and how their dynamic spatio-temporal distribution at the PM has been studied recently. We will elaborate on the newly emerging concept of plasma membrane microdomains as potential hubs for specific receptor complex assembly and signalling outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.
Transition Manifolds of Complex Metastable Systems
Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof
2018-04-01
We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.
Traffic Dynamics on Complex Networks: A Survey
Directory of Open Access Journals (Sweden)
Shengyong Chen
2012-01-01
Full Text Available Traffic dynamics on complex networks are intriguing in recent years due to their practical implications in real communication networks. In this survey, we give a brief review of studies on traffic routing dynamics on complex networks. Strategies for improving transport efficiency, including designing efficient routing strategies and making appropriate adjustments to the underlying network structure, are introduced in this survey. Finally, a few open problems are discussed in this survey.
Pinning Synchronization of Switched Complex Dynamical Networks
Directory of Open Access Journals (Sweden)
Liming Du
2015-01-01
Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.
The heterogeneous dynamics of economic complexity.
Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano
2015-01-01
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch--Economic Complexity--have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method--the selective predictability scheme--in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries.
Complex dynamic in ecological time series
Peter Turchin; Andrew D. Taylor
1992-01-01
Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...
Dynamical complexity changes during two forms of meditation
Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng
2011-06-01
Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.
Chaotic, fractional, and complex dynamics new insights and perspectives
Macau, Elbert; Sanjuan, Miguel
2018-01-01
The book presents nonlinear, chaotic and fractional dynamics, complex systems and networks, together with cutting-edge research on related topics. The fifteen chapters – written by leading scientists working in the areas of nonlinear, chaotic and fractional dynamics, as well as complex systems and networks – offer an extensive overview of cutting-edge research on a range of topics, including fundamental and applied research. These include but are not limited to aspects of synchronization in complex dynamical systems, universality features in systems with specific fractional dynamics, and chaotic scattering. As such, the book provides an excellent and timely snapshot of the current state of research, blending the insights and experiences of many prominent researchers.
Dynamics in electron transfer protein complexes
Bashir, Qamar
2010-01-01
Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize the ensemble of encounter orientations in the short-lived electron transfer complex of yeast Cc and CcP. The complete conformational space sampled by the protein molecules during the dynamic part of ...
Discontinuity and complexity in nonlinear physical systems
Baleanu, Dumitru; Luo, Albert
2014-01-01
This unique book explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian systems, important to understand the resonance interactions in nonlinear dynamical systems, such as Tsunami waves and wildfire propagations; as well as Lev flights in chaotic trajectories, dynamical system synchronization and DNA information complexity analysis. Part III examines chaos and periodic motions in discontinuous dynamical systems, extensively present in a range of systems, including piecewise linear systems, vibro-impact systems and drilling systems in engineering. And in Part IV, engineering and financial nonlinearity are discussed. The mechanism of shock wave with saddle-node bifurcation and rotating disk stability will be presented, and the financial nonlinear models will be discussed....
Constraint elimination in dynamical systems
Singh, R. P.; Likins, P. W.
1989-01-01
Large space structures (LSSs) and other dynamical systems of current interest are often extremely complex assemblies of rigid and flexible bodies subjected to kinematical constraints. A formulation is presented for the governing equations of constrained multibody systems via the application of singular value decomposition (SVD). The resulting equations of motion are shown to be of minimum dimension.
Competitive Dynamics on Complex Networks
Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan
2014-07-01
We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.
Energy Technology Data Exchange (ETDEWEB)
Sibener, Steven J. [Univ. of Chicago, IL (United States). James Franck Inst. and Dept. of Chemistry
2014-03-11
This research program explored the efficacy of using molecular-level manipulation, imaging and scanning tunneling spectroscopy in conjunction with supersonic molecular beam gas-surface scattering to significantly enhance our understanding of chemical processes occurring on well-characterized interfaces. One program focus was on the spatially-resolved emergent behavior of complex reaction systems as a function of the local geometry and density of adsorbate-substrate systems under reaction conditions. Another focus was on elucidating the emergent electronic and related reactivity characteristics of intentionally constructed single and multicomponent atom- and nanoparticle-based materials. We also examined emergent chirality and self-organization in adsorbed molecular systems where collective interactions between adsorbates and the supporting interface lead to spatial symmetry breaking. In many of these studies we combined the advantages of scanning tunneling (STM) and atomic force (AFM) imaging, scanning tunneling local electronic spectroscopy (STS), and reactive supersonic molecular beams to elucidate precise details of interfacial reactivity that had not been observed by more traditional surface science methods. Using these methods, it was possible to examine, for example, the differential reactivity of molecules adsorbed at different bonding sites in conjunction with how reactivity is modified by the local configuration of nearby adsorbates. At the core of this effort was the goal of significantly extending our understanding of interfacial atomic-scale interactions to create, with intent, molecular assemblies and materials with advanced chemical and physical properties. This ambitious program addressed several key topics in DOE Grand Challenge Science, including emergent chemical and physical properties in condensed phase systems, novel uses of chemical imaging, and the development of advanced reactivity concepts in combustion and catalysis including carbon
Complex Dynamics in Nonequilibrium Economics and Chemistry
Wen, Kehong
Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator
Spreading dynamics in complex networks
Pei, Sen; Makse, Hernán A.
2013-12-01
Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality.
Spreading dynamics in complex networks
International Nuclear Information System (INIS)
Pei, Sen; Makse, Hernán A
2013-01-01
Searching for influential spreaders in complex networks is an issue of great significance for applications across various domains, ranging from epidemic control, innovation diffusion, viral marketing, and social movement to idea propagation. In this paper, we first display some of the most important theoretical models that describe spreading processes, and then discuss the problem of locating both the individual and multiple influential spreaders respectively. Recent approaches in these two topics are presented. For the identification of privileged single spreaders, we summarize several widely used centralities, such as degree, betweenness centrality, PageRank, k-shell, etc. We investigate the empirical diffusion data in a large scale online social community—LiveJournal. With this extensive dataset, we find that various measures can convey very distinct information of nodes. Of all the users in the LiveJournal social network, only a small fraction of them are involved in spreading. For the spreading processes in LiveJournal, while degree can locate nodes participating in information diffusion with higher probability, k-shell is more effective in finding nodes with a large influence. Our results should provide useful information for designing efficient spreading strategies in reality. (paper)
Pilyugin, Sergei Yu
2012-01-01
Dynamical systems are abundant in theoretical physics and engineering. Their understanding, with sufficient mathematical rigor, is vital to solving many problems. This work conveys the modern theory of dynamical systems in a didactically developed fashion.In addition to topological dynamics, structural stability and chaotic dynamics, also generic properties and pseudotrajectories are covered, as well as nonlinearity. The author is an experienced book writer and his work is based on years of teaching.
Complex adaptive systems ecology
DEFF Research Database (Denmark)
Sommerlund, Julie
2003-01-01
In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...
Lattice dynamics and molecular dynamics simulation of complex materials
International Nuclear Information System (INIS)
Chaplot, S.L.
1997-01-01
In this article we briefly review the lattice dynamics and molecular dynamics simulation techniques, as used for complex ionic and molecular solids, and demonstrate a number of applications through examples of our work. These computational studies, along with experiments, have provided microscopic insight into the structure and dynamics, phase transitions and thermodynamical properties of a variety of materials including fullerene, high temperature superconducting oxides and geological minerals as a function of pressure and temperature. The computational techniques also allow the study of the structures and dynamics associated with disorder, defects, surfaces, interfaces etc. (author)
Gils, S; Hoveijn, I; Takens, F; Nonlinear Dynamical Systems and Chaos
1996-01-01
Symmetries in dynamical systems, "KAM theory and other perturbation theories", "Infinite dimensional systems", "Time series analysis" and "Numerical continuation and bifurcation analysis" were the main topics of the December 1995 Dynamical Systems Conference held in Groningen in honour of Johann Bernoulli. They now form the core of this work which seeks to present the state of the art in various branches of the theory of dynamical systems. A number of articles have a survey character whereas others deal with recent results in current research. It contains interesting material for all members of the dynamical systems community, ranging from geometric and analytic aspects from a mathematical point of view to applications in various sciences.
Skjeltorp, Arne T
2006-01-01
The book reviews the synergism between various fields of research that are confronted with networks, such as genetic and metabolic networks, social networks, the Internet and ecological systems. In many cases, the interacting networks manifest so-called emergent properties that are not possessed by any of the individual components. This means that the detailed knowledge of the components is insufficient to describe the whole system. Recent work has indicated that networks in nature have so-called scale-free characteristics, and the associated dynamic network modelling shows unexpected results such as an amazing robustness against accidental failures. Modelling the signal transduction networks in bioprocesses as in living cells is a challenging interdisciplinary research area. It is now realized that the many features of molecular interaction networks within a cell are shared to a large degree by the other complex systems mentioned above, such as the Internet, computer chips and society. Thus knowledge gained ...
Directory of Open Access Journals (Sweden)
Gloria Nogueiras
2017-05-01
Full Text Available This study adopts a dynamic systems approach to investigate how individuals successfully manage contextual complexity. To that end, we tracked individuals' emotional trajectories during a challenging training course, seeking qualitative changes–turning points—and we tested their relationship with the perceived complexity of the training. The research context was a 5-day higher education course based on process-oriented experiential learning, and the sample consisted of 17 students. The students used a five-point Likert scale to rate the intensity of 16 emotions and the complexity of the training on 8 measurement points. Monte Carlo permutation tests enabled to identify 30 turning points in the 272 emotional trajectories analyzed (17 students * 16 emotions each. 83% of the turning points indicated a change of pattern in the emotional trajectories that consisted of: (a increasingly intense positive emotions or (b decreasingly intense negative emotions. These turning points also coincided with particularly complex periods in the training as perceived by the participants (p = 0.003, and p = 0.001 respectively. The relationship between positively-trended turning points in the students' emotional trajectories and the complexity of the training may be interpreted as evidence of a successful management of the cognitive conflict arising from the clash between the students' prior ways of meaning-making and the challenging demands of the training. One of the strengths of this study is that it provides a relatively simple procedure for identifying turning points in developmental trajectories, which can be applied to various longitudinal experiences that are very common in educational and developmental contexts. Additionally, the findings contribute to sustaining that the assumption that complex contextual demands lead unfailingly to individuals' learning is incomplete. Instead, it is how individuals manage complexity which may or may not lead to
Directory of Open Access Journals (Sweden)
Huayong Zhang
2018-01-01
Full Text Available We present in this paper an investigation on a discrete predator-prey system with Crowley-Martin type functional response to know its complex dynamics on the routes to chaos which are induced by bifurcations. Via application of the center manifold theorem and bifurcation theorems, occurrence conditions for flip bifurcation and Neimark-Sacker bifurcation are determined, respectively. Numerical simulations are performed, on the one hand, verifying the theoretical results and, on the other hand, revealing new interesting dynamical behaviors of the discrete predator-prey system, including period-doubling cascades, period-2, period-3, period-4, period-5, period-6, period-7, period-8, period-9, period-11, period-13, period-15, period-16, period-20, period-22, period-24, period-30, and period-34 orbits, invariant cycles, chaotic attractors, sub-flip bifurcation, sub-(inverse Neimark-Sacker bifurcation, chaotic interior crisis, chaotic band, sudden disappearance of chaotic dynamics and abrupt emergence of chaos, and intermittent periodic behaviors. Moreover, three-dimensional bifurcation diagrams are utilized to study the transition between flip bifurcation and Neimark-Sacker bifurcation, and a critical case between the two bifurcations is found. This critical bifurcation case is a combination of flip bifurcation and Neimark-Sacker bifurcation, showing the nonlinear characteristics of both bifurcations.
Synchronization coupled systems to complex networks
Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas
2018-01-01
A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...
Workshop on Nonlinear Phenomena in Complex Systems
1989-01-01
This book contains a thorough treatment of neural networks, cellular-automata and synergetics, in an attempt to provide three different approaches to nonlinear phenomena in complex systems. These topics are of major interest to physicists active in the fields of statistical mechanics and dynamical systems. They have been developed with a high degree of sophistication and include the refinements necessary to work with the complexity of real systems as well as the more recent research developments in these areas.
Transparency in complex dynamic food supply chains
Trienekens, J.H.; Wognum, P.M.; Beulens, A.J.M.; Vorst, van der J.G.A.J.
2012-01-01
Food supply chains are increasingly complex and dynamic due to (i) increasing product proliferation to serve ever diversifying and globalising markets as a form of mass customisation with resulting global flows of raw materials, ingredients and products, and (ii) the need to satisfy changing and
Alexandridis, Konstantinos T.
This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land
Complex motions and chaos in nonlinear systems
Machado, José; Zhang, Jiazhong
2016-01-01
This book brings together 10 chapters on a new stream of research examining complex phenomena in nonlinear systems—including engineering, physics, and social science. Complex Motions and Chaos in Nonlinear Systems provides readers a particular vantage of the nature and nonlinear phenomena in nonlinear dynamics that can develop the corresponding mathematical theory and apply nonlinear design to practical engineering as well as the study of other complex phenomena including those investigated within social science.
Dynamic Systems and Control Engineering
International Nuclear Information System (INIS)
Kim, Jong Seok
1994-02-01
This book deals with introduction of dynamic system and control engineering, frequency domain modeling of dynamic system, temporal modeling of dynamic system, typical dynamic system and automatic control device, performance and stability of control system, root locus analysis, analysis of frequency domain dynamic system, design of frequency domain dynamic system, design and analysis of space, space of control system and digital control system such as control system design of direct digital and digitalization of consecutive control system.
Dynamic Systems and Control Engineering
Energy Technology Data Exchange (ETDEWEB)
Kim, Jong Seok
1994-02-15
This book deals with introduction of dynamic system and control engineering, frequency domain modeling of dynamic system, temporal modeling of dynamic system, typical dynamic system and automatic control device, performance and stability of control system, root locus analysis, analysis of frequency domain dynamic system, design of frequency domain dynamic system, design and analysis of space, space of control system and digital control system such as control system design of direct digital and digitalization of consecutive control system.
Atomic switch networks as complex adaptive systems
Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.
2018-03-01
Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.
Hamiltonian dynamics for complex food webs
Kozlov, Vladimir; Vakulenko, Sergey; Wennergren, Uno
2016-03-01
We investigate stability and dynamics of large ecological networks by introducing classical methods of dynamical system theory from physics, including Hamiltonian and averaging methods. Our analysis exploits the topological structure of the network, namely the existence of strongly connected nodes (hubs) in the networks. We reveal new relations between topology, interaction structure, and network dynamics. We describe mechanisms of catastrophic phenomena leading to sharp changes of dynamics and hence completely altering the ecosystem. We also show how these phenomena depend on the structure of interaction between species. We can conclude that a Hamiltonian structure of biological interactions leads to stability and large biodiversity.
From System Complexity to Emergent Properties
Aziz-Alaoui, M. A
2009-01-01
Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.
Stability of dynamical systems
Liao, Xiaoxin; Yu, P 0
2007-01-01
The main purpose of developing stability theory is to examine dynamic responses of a system to disturbances as the time approaches infinity. It has been and still is the object of intense investigations due to its intrinsic interest and its relevance to all practical systems in engineering, finance, natural science and social science. This monograph provides some state-of-the-art expositions of major advances in fundamental stability theories and methods for dynamic systems of ODE and DDE types and in limit cycle, normal form and Hopf bifurcation control of nonlinear dynamic systems.ʺ Presents
The Complex Dynamics of Sponsored Search Markets
Robu, Valentin; La Poutré, Han; Bohte, Sander
This paper provides a comprehensive study of the structure and dynamics of online advertising markets, mostly based on techniques from the emergent discipline of complex systems analysis. First, we look at how the display rank of a URL link influences its click frequency, for both sponsored search and organic search. Second, we study the market structure that emerges from these queries, especially the market share distribution of different advertisers. We show that the sponsored search market is highly concentrated, with less than 5% of all advertisers receiving over 2/3 of the clicks in the market. Furthermore, we show that both the number of ad impressions and the number of clicks follow power law distributions of approximately the same coefficient. However, we find this result does not hold when studying the same distribution of clicks per rank position, which shows considerable variance, most likely due to the way advertisers divide their budget on different keywords. Finally, we turn our attention to how such sponsored search data could be used to provide decision support tools for bidding for combinations of keywords. We provide a method to visualize keywords of interest in graphical form, as well as a method to partition these graphs to obtain desirable subsets of search terms.
The sleeping brain as a complex system.
Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas
2011-10-13
'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.
Oluoch, K.; Marwan, N.; Trauth, M.; Loew, A.; Kurths, J.
2012-04-01
The African continent lie almost entirely within the tropics and as such its (tropical) climate systems are predominantly governed by the heterogeneous, spatial and temporal variability of the Hadley and Walker circulations. The variabilities in these meridional and zonal circulations lead to intensification or suppression of the intensities, durations and frequencies of the Inter-tropical Convergence Zone (ICTZ) migration, trade winds and subtropical high-pressure regions and the continental monsoons. The above features play a central role in determining the African rainfall spatial and temporal variability patterns. The current understanding of these climate features and their influence on the rainfall patterns is not sufficiently understood. Like many real-world systems, atmospheric-oceanic processes exhibit non-linear properties that can be better explored using non-linear (NL) methods of time-series analysis. Over the recent years, the complex network approach has evolved as a powerful new player in understanding spatio-temporal dynamics and evolution of complex systems. Together with NL techniques, it is continuing to find new applications in many areas of science and technology including climate research. We would like to use these two powerful methods to understand the spatial structure and dynamics of African rainfall anomaly patterns and extremes. The method of event synchronization (ES) developed by Quiroga et al., 2002 and first applied to climate networks by Malik et al., 2011 looks at correlations with a dynamic time lag and as such, it is a more intuitive way to correlate a complex and heterogeneous system like climate networks than a fixed time delay most commonly used. On the other hand, the short comings of ES is its lack of vigorous test statistics for the significance level of the correlations, and the fact that only the events' time indices are synchronized while all information about how the relative intensities propagate within network
International Nuclear Information System (INIS)
Posch, H.A.; Narnhofer, H.; Thirring, W.
1990-01-01
We study the dynamics of classical particles interacting with attractive Gaussian potentials. This system is thermodynamically not stable and exhibits negative specific heat. The results of the computer simulation of the dynamics are discussed in comparison with various theories. In particular, we find that the condensed phase is a stationary solution of the Vlasov equation, but the Vlasov dynamics cannot describe the collapse. 14 refs., 1 tab., 11 figs. (Authors)
Ligterink, N.E.
2007-01-01
Functional system dynamics is the analysis, modelling, and simulation of continuous systems usually described by partial differential equations. From the infinite degrees of freedom of such systems only a finite number of relevant variables have to be chosen for a practical model description. The proper input and output of the system are an important part of the relevant variables.
Shadowing in dynamical systems
Pilyugin, Sergei Yu
1999-01-01
This book is an introduction to the theory of shadowing of approximate trajectories in dynamical systems by exact ones. This is the first book completely devoted to the theory of shadowing. It shows the importance of shadowing theory for both the qualitative theory of dynamical systems and the theory of numerical methods. Shadowing Methods allow us to estimate differences between exact and approximate solutions on infinite time intervals and to understand the influence of error terms. The book is intended for specialists in dynamical systems, for researchers and graduate students in the theory of numerical methods.
Complex and unexpected dynamics in simple genetic regulatory networks
Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey
2014-03-01
One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.
Nonlinear dynamics, chaos and complex cardiac arrhythmias
Glass, L.; Courtemanche, M.; Shrier, A.; Goldberger, A. L.
1987-01-01
Periodic stimulation of a nonlinear cardiac oscillator in vitro gives rise to complex dynamics that is well described by one-dimensional finite difference equations. As stimulation parameters are varied, a large number of different phase-locked and chaotic rhythms is observed. Similar rhythms can be observed in the intact human heart when there is interaction between two pacemaker sites. Simplified models are analyzed, which show some correspondence to clinical observations.
Early days in complex dynamics a history of complex dynamics in one variable during 1906-1942
Alexander, Daniel S; Rosa, Alessandro
2011-01-01
The theory of complex dynamics, whose roots lie in 19th-century studies of the iteration of complex function conducted by Kœnigs, Schröder, and others, flourished remarkably during the first half of the 20th century, when many of the central ideas and techniques of the subject developed. This book by Alexander, Iavernaro, and Rosa paints a robust picture of the field of complex dynamics between 1906 and 1942 through detailed discussions of the work of Fatou, Julia, Siegel, and several others. A recurrent theme of the authors' treatment is the center problem in complex dynamics. They present its complete history during this period and, in so doing, bring out analogies between complex dynamics and the study of differential equations, in particular, the problem of stability in Hamiltonian systems. Among these analogies are the use of iteration and problems involving small divisors which the authors examine in the work of Poincaré and others, linking them to complex dynamics, principally via the work of Samuel...
Narotam, Pradeep K; Morrison, John F; Schmidt, Michael D; Nathoo, Narendra
2014-04-01
Predictive modeling of emergent behavior, inherent to complex physiological systems, requires the analysis of large complex clinical data streams currently being generated in the intensive care unit. Brain tissue oxygen protocols have yielded outcome benefits in traumatic brain injury (TBI), but the critical physiological thresholds for low brain oxygen have not been established for a dynamical patho-physiological system. High frequency, multi-modal clinical data sets from 29 patients with severe TBI who underwent multi-modality neuro-clinical care monitoring and treatment with a brain oxygen protocol were analyzed. The inter-relationship between acute physiological parameters was determined using symbolic regression (SR) as the computational framework. The mean patient age was 44.4±15 with a mean admission GCS of 6.6±3.9. Sixty-three percent sustained motor vehicle accidents and the most common pathology was intra-cerebral hemorrhage (50%). Hospital discharge mortality was 21%, poor outcome occurred in 24% of patients, and good outcome occurred in 56% of patients. Criticality for low brain oxygen was intracranial pressure (ICP) ≥22.8 mm Hg, for mortality at ICP≥37.1 mm Hg. The upper therapeutic threshold for cerebral perfusion pressure (CPP) was 75 mm Hg. Eubaric hyperoxia significantly impacted partial pressure of oxygen in brain tissue (PbtO2) at all ICP levels. Optimal brain temperature (Tbr) was 34-35°C, with an adverse effect when Tbr≥38°C. Survivors clustered at [Formula: see text] Hg vs. non-survivors [Formula: see text] 18 mm Hg. There were two mortality clusters for ICP: High ICP/low PbtO2 and low ICP/low PbtO2. Survivors maintained PbtO2 at all ranges of mean arterial pressure in contrast to non-survivors. The final SR equation for cerebral oxygenation is: [Formula: see text]. The SR-model of acute TBI advances new physiological thresholds or boundary conditions for acute TBI management: PbtO2≥25 mmHg; ICP≤22 mmHg; CPP≈60-75
Complex dynamics in double-diffusive convection
Energy Technology Data Exchange (ETDEWEB)
Meca, Esteban; Ramirez-Piscina, Laureano [Universitat Politecnica de Catalunya, Departament de Fisica Aplicada, Barcelona (Spain); Mercader, Isabel; Batiste, Oriol [Universitat Politecnica de Catalunya, Departament de Fisica Aplicada, Barcelona (Spain)
2004-11-01
The dynamics of a small Prandtl number binary mixture in a laterally heated cavity is studied numerically. By combining temporal integration, steady state solving and linear stability analysis of the full PDE equations, we have been able to locate and characterize a codimension-three degenerate Takens-Bogdanov point whose unfolding describes the dynamics of the system for a certain range of Rayleigh numbers and separation ratios near S=-1. (orig.)
Invitation to dynamical systems
Scheinerman, Edward R
2012-01-01
This text is designed for those who wish to study mathematics beyond linear algebra but are unready for abstract material. Rather than a theorem-proof-corollary exposition, it stresses geometry, intuition, and dynamical systems. 1996 edition.
An Axiomatic Representation of System Dynamics
Baianu, I
2004-01-01
An axiomatic representation of system dynamics is introduced in terms of categories, functors, organismal supercategories, limits and colimits of diagrams. Specific examples are considered in Complex Systems Biology, such as ribosome biogenesis and Hormonal Control in human subjects. "Fuzzy" Relational Structures are also proposed for flexible representations of biological system dynamics and organization.
Fourth International Conference on Complex Systems
Minai, Ali A; Unifying Themes in Complex Systems IV
2008-01-01
In June of 2002, over 500 professors, students and researchers met in Boston, Massachusetts for the Fourth International Conference on Complex Systems. The attendees represented a remarkably diverse collection of fields: biology, ecology, physics, engineering, computer science, economics, psychology and sociology, The goal of the conference was to encourage cross-fertilization between the many disciplines represented and to deepen understanding of the properties common to all complex systems. This volume contains 43 papers selected from the more than 200 presented at the conference. Topics include: cellular automata, neurology, evolution, computer science, network dynamics, and urban planning. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex sys...
The dynamic complexity of a three species food chain model
International Nuclear Information System (INIS)
Lv Songjuan; Zhao Min
2008-01-01
In this paper, a three-species food chain model is analytically investigated on theories of ecology and using numerical simulation. Bifurcation diagrams are obtained for biologically feasible parameters. The results show that the system exhibits rich complexity features such as stable, periodic and chaotic dynamics
Sixth International Conference on Complex Systems
Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems
2008-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.
Ligterink, N.E.
2007-01-01
Functional system dynamics is the analysis, modelling, and simulation of continuous systems usually described by partial differential equations. From the infinite degrees of freedom of such systems only a finite number of relevant variables have to be chosen for a practical model description. The
Complex economic dynamics: Chaotic saddle, crisis and intermittency
International Nuclear Information System (INIS)
Chian, Abraham C.-L.; Rempel, Erico L.; Rogers, Colin
2006-01-01
Complex economic dynamics is studied by a forced oscillator model of business cycles. The technique of numerical modeling is applied to characterize the fundamental properties of complex economic systems which exhibit multiscale and multistability behaviors, as well as coexistence of order and chaos. In particular, we focus on the dynamics and structure of unstable periodic orbits and chaotic saddles within a periodic window of the bifurcation diagram, at the onset of a saddle-node bifurcation and of an attractor merging crisis, and in the chaotic regions associated with type-I intermittency and crisis-induced intermittency, in non-linear economic cycles. Inside a periodic window, chaotic saddles are responsible for the transient motion preceding convergence to a periodic or a chaotic attractor. The links between chaotic saddles, crisis and intermittency in complex economic dynamics are discussed. We show that a chaotic attractor is composed of chaotic saddles and unstable periodic orbits located in the gap regions of chaotic saddles. Non-linear modeling of economic chaotic saddle, crisis and intermittency can improve our understanding of the dynamics of financial intermittency observed in stock market and foreign exchange market. Characterization of the complex dynamics of economic systems is a powerful tool for pattern recognition and forecasting of business and financial cycles, as well as for optimization of management strategy and decision technology
Directory of Open Access Journals (Sweden)
Camilo Henrique da Silva Lima
2015-10-01
Full Text Available Molecular dynamics (MD simulations of 12 aqueous systems of the NADH-dependent enoyl-ACP reductase from Mycobacterium tuberculosis (InhA were carried out for up to 20–40 ns using the GROMACS 4.5 package. Simulations of the holoenzyme, holoenzyme-substrate, and 10 holoenzyme-inhibitor complexes were conducted in order to gain more insight about the secondary structure motifs of the InhA substrate-binding pocket. We monitored the lifetime of the main intermolecular interactions: hydrogen bonds and hydrophobic contacts. Our MD simulations demonstrate the importance of evaluating the conformational changes that occur close to the active site of the enzyme-cofactor complex before and after binding of the ligand and the influence of the water molecules. Moreover, the protein-inhibitor total steric (ELJ and electrostatic (EC interaction energies, related to Gly96 and Tyr158, are able to explain 80% of the biological response variance according to the best linear equation, pKi = 7.772 − 0.1885 × Gly96 + 0.0517 × Tyr158 (R2 = 0.80; n = 10, where interactions with Gly96, mainly electrostatic, increase the biological response, while those with Tyr158 decrease. These results will help to understand the structure-activity relationships and to design new and more potent anti-TB drugs.
International Nuclear Information System (INIS)
Sumner, H.M.
1969-03-01
The KDF9/EGDON program ZIP MK 2 is the third of a series of programs for off-line digital computer analysis of dynamic systems: it has been designed specifically to cater for the needs of the design or control engineer in having an input scheme which is minimally computer-oriented. It uses numerical algorithms which are as near fool-proof as the author could discover or devise, and has comprehensive diagnostic sections to help the user in the event of faulty data or machine execution. ZIP MK 2 accepts mathematical models comprising first order linear differential and linear algebraic equations, and from these computes and factorises the transfer functions between specified pairs of output and input variables; if desired, the frequency response may be computed from the computed transfer function. The model input scheme is fully compatible with the frequency response programs FRP MK 1 and MK 2, except that, for ZIP MK 2, transport, or time-delays must be converted by the user to Pade or Bode approximations prior to input. ZIP provides the pole-zero plot, (or complex plane analysis), while FRP provides the frequency response and FIFI the time domain analyses. The pole-zero method of analysis has been little used in the past for complex models, especially where transport delays occur, and one of its primary purposes is as a research tool to investigate the usefulness of this method, for process plant, whether nuclear, chemical or other continuous processes. (author)
Investigating dynamical complexity in the magnetosphere using various entropy measures
Balasis, Georgios; Daglis, Ioannis A.; Papadimitriou, Constantinos; Kalimeri, Maria; Anastasiadis, Anastasios; Eftaxias, Konstantinos
2009-09-01
The complex system of the Earth's magnetosphere corresponds to an open spatially extended nonequilibrium (input-output) dynamical system. The nonextensive Tsallis entropy has been recently introduced as an appropriate information measure to investigate dynamical complexity in the magnetosphere. The method has been employed for analyzing Dst time series and gave promising results, detecting the complexity dissimilarity among different physiological and pathological magnetospheric states (i.e., prestorm activity and intense magnetic storms, respectively). This paper explores the applicability and effectiveness of a variety of computable entropy measures (e.g., block entropy, Kolmogorov entropy, T complexity, and approximate entropy) to the investigation of dynamical complexity in the magnetosphere. We show that as the magnetic storm approaches there is clear evidence of significant lower complexity in the magnetosphere. The observed higher degree of organization of the system agrees with that inferred previously, from an independent linear fractal spectral analysis based on wavelet transforms. This convergence between nonlinear and linear analyses provides a more reliable detection of the transition from the quiet time to the storm time magnetosphere, thus showing evidence that the occurrence of an intense magnetic storm is imminent. More precisely, we claim that our results suggest an important principle: significant complexity decrease and accession of persistency in Dst time series can be confirmed as the magnetic storm approaches, which can be used as diagnostic tools for the magnetospheric injury (global instability). Overall, approximate entropy and Tsallis entropy yield superior results for detecting dynamical complexity changes in the magnetosphere in comparison to the other entropy measures presented herein. Ultimately, the analysis tools developed in the course of this study for the treatment of Dst index can provide convenience for space weather
Exponential Synchronization of Uncertain Complex Dynamical Networks with Delay Coupling
International Nuclear Information System (INIS)
Wang Lifu; Kong Zhi; Jing Yuanwei
2010-01-01
This paper studies the global exponential synchronization of uncertain complex delayed dynamical networks. The network model considered is general dynamical delay networks with unknown network structure and unknown coupling functions but bounded. Novel delay-dependent linear controllers are designed via the Lyapunov stability theory. Especially, it is shown that the controlled networks are globally exponentially synchronized with a given convergence rate. An example of typical dynamical network of this class, having the Lorenz system at each node, has been used to demonstrate and verify the novel design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches. (general)
Adaptive, dynamic, and resilient systems
Suri, Niranjan
2015-01-01
As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r
Complex phase dynamics in coupled bursters
DEFF Research Database (Denmark)
Postnov, D E; Sosnovtseva, Olga; Malova, S Y
2003-01-01
The phenomenon of phase multistability in the synchronization of two coupled oscillatory systems typically arises when the systems individually display complex wave forms associated, for instance, with the presence of subharmonic components. Alternatively, phase multistability can be caused...... the number of spikes per train and the proximity of a neighboring equilibrium point can influence the formation of coexisting regimes....
Energy Technology Data Exchange (ETDEWEB)
Burgwinkel, Paul; Vreydal, Daniel; Eltaliawi, Gamil; Vijayakumar, Nandhakumar [RWTH Aachen (DE). Inst. fuer Maschinentechnik der Rohstoffindustrie (IMR)
2010-09-15
For the first time the Co-simulation method was successfully used for full representation of a large belt conveyor for an open cast mine in a simulation model at the Institute for Mechanical Engineering in the Raw Materials Industry at Rhineland-Westphalia Technological University in Aachen. The aim of this project was the development of an electro-mechanical simulation model, which represents all components of a large belt conveyor from the drive motor to the conveyor belt in one simulation model and thus makes the interactions between the individual assemblies verifiable by calculations. With the aid of the developed model it was possible to determine critical operating speeds of the represented large belt conveyor and derive suitable measures to combat undesirable resonance states in the drive assembly. Furthermore it was possible to clarify the advantage of the full numerical representation of an electromechanical drive system. (orig.)
Imaging complex nutrient dynamics in mycelial networks.
Fricker, M D; Lee, J A; Bebber, D P; Tlalka, M; Hynes, J; Darrah, P R; Watkinson, S C; Boddy, L
2008-08-01
Transport networks are vital components of multi-cellular organisms, distributing nutrients and removing waste products. Animal cardiovascular and respiratory systems, and plant vasculature, are branching trees whose architecture is thought to determine universal scaling laws in these organisms. In contrast, the transport systems of many multi-cellular fungi do not fit into this conceptual framework, as they have evolved to explore a patchy environment in search of new resources, rather than ramify through a three-dimensional organism. These fungi grow as a foraging mycelium, formed by the branching and fusion of threadlike hyphae, that gives rise to a complex network. To function efficiently, the mycelial network must both transport nutrients between spatially separated source and sink regions and also maintain its integrity in the face of continuous attack by mycophagous insects or random damage. Here we review the development of novel imaging approaches and software tools that we have used to characterise nutrient transport and network formation in foraging mycelia over a range of spatial scales. On a millimetre scale, we have used a combination of time-lapse confocal imaging and fluorescence recovery after photobleaching to quantify the rate of diffusive transport through the unique vacuole system in individual hyphae. These data then form the basis of a simulation model to predict the impact of such diffusion-based movement on a scale of several millimetres. On a centimetre scale, we have used novel photon-counting scintillation imaging techniques to visualize radiolabel movement in small microcosms. This approach has revealed novel N-transport phenomena, including rapid, preferential N-resource allocation to C-rich sinks, induction of simultaneous bi-directional transport, abrupt switching between different pre-existing transport routes, and a strong pulsatile component to transport in some species. Analysis of the pulsatile transport component using Fourier
Searching for Appropriate Ways to Face the Challenges of Complexity and Dynamics
Sommerfeld, Peter; Hollenstein, Lea
2017-01-01
People, as bio-psychological systems, are just as dynamic and complex as the social systems that they create. Social work intervenes in the interplay of these two complex, dynamic systems. How can we capture these complexities and dynamics in social work research and practice? The paper introduces the theoretical grounds on which a mixed-methods design has been developed combining a longitudinal quantitative method called Real Time Monitoring that produces dense time series data with qualitat...
Complex networks under dynamic repair model
Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao
2018-01-01
Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.
Structure and dynamics of weakly bound complexes
International Nuclear Information System (INIS)
Skouteris, D.
1998-01-01
The present thesis deals with the spectroscopic and theoretical investigation of weakly bound complexes involving a methane molecule. Studies of these Van der Waals complexes can give valuable information on the relevant intermolecular dynamics and promote the understanding of the interactions between molecules (which can ultimately lead to chemical reactions). Especially interesting are complexes involving molecules of high symmetry (e.g. tetrahedral, such as methane) because of the unusual effects arising from it (selection rules, nuclear Spin statistical weights etc.). The infrared spectrum of the Van der Waals complex between a CH 4 and a N 2 O molecule has been recorded and most of it has been assigned in the region of the N - O stretch (approximately 2225.0 cm -1 ). Despite the fact that this is really a weakly bound complex, it is nevertheless rigid enough so that the standard model for asymmetric top spectra can be applied to it with the usual quantum numbers. From the value of the inertial defect, it turns out that the methane unit is locked in a rigid configuration within the complex rather than freely rotating. The intermolecular distance as well as the tilting angle of the N 2 O linear unit are determined from the rotational constants. The complex itself turns out to have a T - shaped configuration. The infrared spectrum of the Ar - CH 4 complex at the ν 4 (bending) band of methane is also assigned. This is different from the previous one in that the methane unit rotates almost freely Within the complex. As a result, the quantum numbers used to classify rovibrational energy levels include these of the free unit. The concept of 'overall symmetry' is made use of to rationalise selection rules in various sub-bands of the spectrum. Moreover, new terms in the potential anisotropy Hamiltonian are calculated through the use of the overall symmetry concept. These are termed 'mixed anisotropy' terms since they involve both rotational and vibrational degrees of
From Hamiltonian chaos to complex systems a nonlinear physics approach
Leonetti, Marc
2013-01-01
From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach collects contributions on recent developments in non-linear dynamics and statistical physics with an emphasis on complex systems. This book provides a wide range of state-of-the-art research in these fields. The unifying aspect of this book is a demonstration of how similar tools coming from dynamical systems, nonlinear physics, and statistical dynamics can lead to a large panorama of research in various fields of physics and beyond, most notably with the perspective of application in complex systems. This book also: Illustrates the broad research influence of tools coming from dynamical systems, nonlinear physics, and statistical dynamics Adopts a pedagogic approach to facilitate understanding by non-specialists and students Presents applications in complex systems Includes 150 illustrations From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach is an ideal book for graduate students and researchers working in applied...
Lyapunov exponents a tool to explore complex dynamics
Pikovsky, Arkady
2016-01-01
Lyapunov exponents lie at the heart of chaos theory, and are widely used in studies of complex dynamics. Utilising a pragmatic, physical approach, this self-contained book provides a comprehensive description of the concept. Beginning with the basic properties and numerical methods, it then guides readers through to the most recent advances in applications to complex systems. Practical algorithms are thoroughly reviewed and their performance is discussed, while a broad set of examples illustrate the wide range of potential applications. The description of various numerical and analytical techniques for the computation of Lyapunov exponents offers an extensive array of tools for the characterization of phenomena such as synchronization, weak and global chaos in low and high-dimensional set-ups, and localization. This text equips readers with all the investigative expertise needed to fully explore the dynamical properties of complex systems, making it ideal for both graduate students and experienced researchers...
Markovian dynamics on complex reaction networks
Energy Technology Data Exchange (ETDEWEB)
Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu
2013-08-10
Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.
Markovian dynamics on complex reaction networks
International Nuclear Information System (INIS)
Goutsias, J.; Jenkinson, G.
2013-01-01
Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples
Dynamics of Information Systems
Hirsch, Michael J; Murphey, Robert
2010-01-01
Our understanding of information and information dynamics has outgrown classical information theory. This book presents the research explaining the importance of information in the evolution of a distributed or networked system. It presents techniques for measuring the value or significance of information within the context of a system
Coupled disease-behavior dynamics on complex networks: A review
Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.
2015-12-01
It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.
Evolutionary dynamics of complex communications networks
Karyotis, Vasileios; Papavassiliou, Symeon
2013-01-01
Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks. Addressing the emerging aspects of modern network analysis and design, Evolutionary Dynamics of Complex Communications Networks introduces and develops a top-bottom approach where elements of the higher layer can be exploited in modifying the lowest physical topology-closing the network design loop in an evolutionary fashion similar to
System dynamics modelling of situation awareness
CSIR Research Space (South Africa)
Oosthuizen, R
2015-11-01
Full Text Available . The feedback loops and delays in the Command and Control system also contribute to the complex dynamic behavior. This paper will build on existing situation awareness models to develop a System Dynamics model to support a qualitative investigation through...
International Nuclear Information System (INIS)
Cugliandolo, Leticia F.
2003-09-01
These lecture notes can be read in two ways. The first two Sections contain a review of the phenomenology of several physical systems with slow nonequilibrium dynamics. In the Conclusions we summarize the scenario for this temporal evolution derived from the solution to some solvable models (p spin and the like) that are intimately connected to the mode coupling approach (and similar ones) to super-cooled liquids. At the end we list a number of open problems of great relevance in this context. These Sections can be read independently of the body of the paper where we present some of the basic analytic techniques used to study the out of equilibrium dynamics of classical and quantum models with and without disorder. We start the technical part by briefly discussing the role played by the environment and by introducing and comparing its representation in the equilibrium and dynamic treatment of classical and quantum systems. We next explain the role played by explicit quenched disorder in both approaches. Later on we focus on analytical techniques; we expand on the dynamic functional methods, and the diagrammatic expansions and resummations used to derive macroscopic equations from the microscopic dynamics. We show why the macroscopic dynamic equations for disordered models and those resulting from self-consistent approximations to non-disordered ones coincide. We review some generic properties of dynamic systems evolving out of equilibrium like the modifications of the fluctuation-dissipation theorem, generic scaling forms of the correlation functions, etc. Finally we solve a family of mean-field models. The connection between the dynamic treatment and the analysis of the free-energy landscape of these models is also presented. We use pedagogical examples all along these lectures to illustrate the properties and results. (author)
Butschli Dynamic Droplet System
DEFF Research Database (Denmark)
Armstrong, R.; Hanczyc, M.
2013-01-01
Dynamical oil-water systems such as droplets display lifelike properties and may lend themselves to chemical programming to perform useful work, specifically with respect to the built environment. We present Butschli water-in-oil droplets as a model for further investigation into the development...... reconstructed the Butschli system and observed its life span under a light microscope, observing chemical patterns and droplet behaviors in nearly three hundred replicate experiments. Self-organizing patterns were observed, and during this dynamic, embodied phase the droplets provided a means of introducing...... temporal and spatial order in the system with the potential for chemical programmability. The authors propose that the discrete formation of dynamic droplets, characterized by their lifelike behavior patterns, during a variable window of time (from 30 s to 30 min after the addition of alkaline water...
Automatic Emergence Detection in Complex Systems
Directory of Open Access Journals (Sweden)
Eugene Santos
2017-01-01
Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.
Measuring Complexity of SAP Systems
Directory of Open Access Journals (Sweden)
Ilja Holub
2016-10-01
Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.
Mathematical Models to Determine Stable Behavior of Complex Systems
Sumin, V. I.; Dushkin, A. V.; Smolentseva, T. E.
2018-05-01
The paper analyzes a possibility to predict functioning of a complex dynamic system with a significant amount of circulating information and a large number of random factors impacting its functioning. Functioning of the complex dynamic system is described as a chaotic state, self-organized criticality and bifurcation. This problem may be resolved by modeling such systems as dynamic ones, without applying stochastic models and taking into account strange attractors.
Nonautonomous dynamical systems
Kloeden, Peter E
2011-01-01
The theory of nonautonomous dynamical systems in both of its formulations as processes and skew product flows is developed systematically in this book. The focus is on dissipative systems and nonautonomous attractors, in particular the recently introduced concept of pullback attractors. Linearization theory, invariant manifolds, Lyapunov functions, Morse decompositions and bifurcations for nonautonomous systems and set-valued generalizations are also considered as well as applications to numerical approximations, switching systems and synchronization. Parallels with corresponding theories of control and random dynamical systems are briefly sketched. With its clear and systematic exposition, many examples and exercises, as well as its interesting applications, this book can serve as a text at the beginning graduate level. It is also useful for those who wish to begin their own independent research in this rapidly developing area.
Spreading dynamics on complex networks: a general stochastic approach.
Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J
2014-12-01
Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.
Vibrations and stability of complex beam systems
Stojanović, Vladimir
2015-01-01
This book reports on solved problems concerning vibrations and stability of complex beam systems. The complexity of a system is considered from two points of view: the complexity originating from the nature of the structure, in the case of two or more elastically connected beams; and the complexity derived from the dynamic behavior of the system, in the case of a damaged single beam, resulting from the harm done to its simple structure. Furthermore, the book describes the analytical derivation of equations of two or more elastically connected beams, using four different theories (Euler, Rayleigh, Timoshenko and Reddy-Bickford). It also reports on a new, improved p-version of the finite element method for geometrically nonlinear vibrations. The new method provides more accurate approximations of solutions, while also allowing us to analyze geometrically nonlinear vibrations. The book describes the appearance of longitudinal vibrations of damaged clamped-clamped beams as a result of discontinuity (damage). It...
Collectives and the design of complex systems
Wolpert, David
2004-01-01
Increasingly powerful computers are making possible distributed systems comprised of many adaptive and self-motivated computational agents. Such systems, when distinguished by system-level performance criteria, are known as "collectives." Collectives and the Design of Complex Systems lays the foundation for a science of collectives and describes how to design them for optimal performance. An introductory survey chapter is followed by descriptions of information-processing problems that can only be solved by the joint actions of large communities of computers, each running its own complex, decentralized machine-learning algorithm. Subsequent chapters analyze the dynamics and structures of collectives, as well as address economic, model-free, and control-theory approaches to designing complex systems. The work assumes a modest understanding of basic statistics and calculus. Topics and Features: Introduces the burgeoning science of collectives and its practical applications in a single useful volume Combines ap...
System dynamics with interaction discontinuity
Luo, Albert C J
2015-01-01
This book describes system dynamics with discontinuity caused by system interactions and presents the theory of flow singularity and switchability at the boundary in discontinuous dynamical systems. Based on such a theory, the authors address dynamics and motion mechanism of engineering discontinuous systems due to interaction. Stability and bifurcations of fixed points in nonlinear discrete dynamical systems are presented, and mapping dynamics are developed for analytical predictions of periodic motions in engineering discontinuous dynamical systems. Ultimately, the book provides an alternative way to discuss the periodic and chaotic behaviors in discontinuous dynamical systems.
Entropy for the Complexity of Physiological Signal Dynamics.
Zhang, Xiaohua Douglas
2017-01-01
Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.
European Conference on Complex Systems
Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela
2016-01-01
This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.
Dynamics of Variable Mass Systems
Eke, Fidelis O.
1998-01-01
This report presents the results of an investigation of the effects of mass loss on the attitude behavior of spinning bodies in flight. The principal goal is to determine whether there are circumstances under which the motion of variable mass systems can become unstable in the sense that their transverse angular velocities become unbounded. Obviously, results from a study of this kind would find immediate application in the aerospace field. The first part of this study features a complete and mathematically rigorous derivation of a set of equations that govern both the translational and rotational motions of general variable mass systems. The remainder of the study is then devoted to the application of the equations obtained to a systematic investigation of the effect of various mass loss scenarios on the dynamics of increasingly complex models of variable mass systems. It is found that mass loss can have a major impact on the dynamics of mechanical systems, including a possible change in the systems stability picture. Factors such as nozzle geometry, combustion chamber geometry, propellant's initial shape, size and relative mass, and propellant location can all have important influences on the system's dynamic behavior. The relative importance of these parameters on-system motion are quantified in a way that is useful for design purposes.
Thinking in complexity the complex dynamics of matter, mind, and mankind
Mainzer, Klaus
1994-01-01
The theory of nonlinear complex systems has become a successful and widely used problem-solving approach in the natural sciences - from laser physics, quantum chaos and meteorology to molecular modeling in chemistry and computer simulations of cell growth in biology In recent times it has been recognized that many of the social, ecological and political problems of mankind are also of a global, complex and nonlinear nature And one of the most exciting topics of present scientific and public interest is the idea that even the human mind is governed largely by the nonlinear dynamics of complex systems In this wide-ranging but concise treatment Prof Mainzer discusses, in nontechnical language, the common framework behind these endeavours Special emphasis is given to the evolution of new structures in natural and cultural systems and it is seen clearly how the new integrative approach of complexity theory can give new insights that were not available using traditional reductionistic methods
Complex Dynamic Development of Poliovirus Membranous Replication Complexes
Nair, Vinod; Hansen, Bryan T.; Hoyt, Forrest H.; Fischer, Elizabeth R.; Ehrenfeld, Ellie
2012-01-01
Replication of all positive-strand RNA viruses is intimately associated with membranes. Here we utilize electron tomography and other methods to investigate the remodeling of membranes in poliovirus-infected cells. We found that the viral replication structures previously described as “vesicles” are in fact convoluted, branching chambers with complex and dynamic morphology. They are likely to originate from cis-Golgi membranes and are represented during the early stages of infection by single-walled connecting and branching tubular compartments. These early viral organelles gradually transform into double-membrane structures by extension of membranous walls and/or collapsing of the luminal cavity of the single-membrane structures. As the double-membrane regions develop, they enclose cytoplasmic material. At this stage, a continuous membranous structure may have double- and single-walled membrane morphology at adjacent cross-sections. In the late stages of the replication cycle, the structures are represented mostly by double-membrane vesicles. Viral replication proteins, double-stranded RNA species, and actively replicating RNA are associated with both double- and single-membrane structures. However, the exponential phase of viral RNA synthesis occurs when single-membrane formations are predominant in the cell. It has been shown previously that replication complexes of some other positive-strand RNA viruses form on membrane invaginations, which result from negative membrane curvature. Our data show that the remodeling of cellular membranes in poliovirus-infected cells produces structures with positive curvature of membranes. Thus, it is likely that there is a fundamental divergence in the requirements for the supporting cellular membrane-shaping machinery among different groups of positive-strand RNA viruses. PMID:22072780
Polyacrylic acids–bovine serum albumin complexation: Structure and dynamics
International Nuclear Information System (INIS)
Othman, Mohamed; Aschi, Adel; Gharbi, Abdelhafidh
2016-01-01
The study of the mixture of BSA with polyacrylic acids at different masses versus pH allowed highlighting the existence of two regimes of weak and strong complexation. These complexes were studied in diluted regime concentration, by turbidimetry, dynamic light scattering (DLS), zeta-potential measurements and nuclear magnetic resonance (NMR). We have followed the pH effect on the structure and properties of the complex. This allowed refining the interpretation of the phase diagram and understanding the observed phenomena. The NMR measurements allowed probing the dynamics of the constituents versus the pH. The computational method was used to precisely determine the electrostatic potential of BSA and how the polyelectrolyte binds to it at different pH. - Highlights: • Influence of physico-chemical parameters on the electrostatic interactions in the complex system (polyelectrolyte/protein). • Stabilization and encapsulation of biological macromolecules solution by mean of polyelectrolyte. • Properties and structure of mixture obtained by screening the charges of globular protein and at different masses of polyacrylic acids. • Dynamic of the constituents formed by complexes particles. • Evaluation of the electrostatic properties of bovine serum albumin versus pH through solution of the Poisson-Boltzmann equation.
Chaotic systems are dynamically random
International Nuclear Information System (INIS)
Svozil, K.
1988-01-01
The idea is put forward that the significant route to chaos is driven by recursive iterations of suitable evolution functions. The corresponding formal notion of randomness is not based on dynamic complexity rather than on static complexity. 24 refs. (Author)
Anomaly Detection for Complex Systems
National Aeronautics and Space Administration — In performance maintenance in large, complex systems, sensor information from sub-components tends to be readily available, and can be used to make predictions about...
Decentralized control of complex systems
Siljak, Dragoslav D
2011-01-01
Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t
Complexity and network dynamics in physiological adaptation: An integrated view
Baffy, Gyorgy; Loscalzo, Joseph
2014-01-01
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of t...
The Heterogeneous Dynamics of Economic Complexity
Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano
2015-01-01
What will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries. PMID:25671312
What are System Dynamics Insights?
Stave, K.; Zimmermann, N. S.; Kim, H.
2016-01-01
This paper explores the concept of system dynamics insights. In our field, the term “insight” is generally understood to mean dynamic insight, that is, a deep understanding about the relationship between structure and behavior. We argue this is only one aspect of the range of insights possible from system dynamics activities, and describe a broader range of potential system dynamics insights. We also propose an initial framework for discussion that relates different types of system dynamics a...
Dynamics of immune system vulnerabilities
Stromberg, Sean P.
The adaptive immune system can be viewed as a complex system, which adapts, over time, to reflect the history of infections experienced by the organism. Understanding its operation requires viewing it in terms of tradeoffs under constraints and evolutionary history. It typically displays "robust, yet fragile" behavior, meaning common tasks are robust to small changes but novel threats or changes in environment can have dire consequences. In this dissertation we use mechanistic models to study several biological processes: the immune response, the homeostasis of cells in the lymphatic system, and the process that normally prevents autoreactive cells from entering the lymphatic system. Using these models we then study the effects of these processes interacting. We show that the mechanisms that regulate the numbers of cells in the immune system, in conjunction with the immune response, can act to suppress autoreactive cells from proliferating, thus showing quantitatively how pathogenic infections can suppress autoimmune disease. We also show that over long periods of time this same effect can thin the repertoire of cells that defend against novel threats, leading to an age correlated vulnerability. This vulnerability is shown to be a consequence of system dynamics, not due to degradation of immune system components with age. Finally, modeling a specific tolerance mechanism that normally prevents autoimmune disease, in conjunction with models of the immune response and homeostasis we look at the consequences of the immune system mistakenly incorporating pathogenic molecules into its tolerizing mechanisms. The signature of this dynamic matches closely that of the dengue virus system.
Recovery time after localized perturbations in complex dynamical networks
Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.
2017-10-01
Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed
Recovery time after localized perturbations in complex dynamical networks
International Nuclear Information System (INIS)
Mitra, Chiranjit; Kittel, Tim; Kurths, Jürgen; Donner, Reik V; Choudhary, Anshul
2017-01-01
Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed
Topics in Complexity: Dynamical Patterns in the Cyberworld
Qi, Hong
Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.
Chaperone-client complexes: A dynamic liaison
Hiller, Sebastian; Burmann, Björn M.
2018-04-01
Living cells contain molecular chaperones that are organized in intricate networks to surveil protein homeostasis by avoiding polypeptide misfolding, aggregation, and the generation of toxic species. In addition, cellular chaperones also fulfill a multitude of alternative functionalities: transport of clients towards a target location, help them fold, unfold misfolded species, resolve aggregates, or deliver clients towards proteolysis machineries. Until recently, the only available source of atomic resolution information for virtually all chaperones were crystal structures of their client-free, apo-forms. These structures were unable to explain details of the functional mechanisms underlying chaperone-client interactions. The difficulties to crystallize chaperones in complexes with clients arise from their highly dynamic nature, making solution NMR spectroscopy the method of choice for their study. With the advent of advanced solution NMR techniques, in the past few years a substantial number of structural and functional studies on chaperone-client complexes have been resolved, allowing unique insight into the chaperone-client interaction. This review summarizes the recent insights provided by advanced high-resolution NMR-spectroscopy to understand chaperone-client interaction mechanisms at the atomic scale.
Anti-synchronization between different chaotic complex systems
International Nuclear Information System (INIS)
Liu Ping; Liu Shutang
2011-01-01
Many studies on the anti-synchronization of nonlinear real dynamic systems have been carried out, whereas the anti-synchronization of chaotic complex systems has not been studied extensively. In this work, the anti-synchronization between a new chaotic complex system and a complex Lorenz system and that between a new chaotic complex system and a complex Lue system were separately investigated by active control and nonlinear control methods, and explicit expressions were derived for the controllers that are used to achieve the anti-synchronization of chaotic complex systems. These expressions were tested numerically and excellent agreement was found. Concerning the new chaotic complex system, we discuss its dynamical properties including dissipation, chaotic behavior, fixed points, and their stability and invariance.
1989 lectures in complex systems
International Nuclear Information System (INIS)
Jen, E.
1990-01-01
This report contains papers on the following topics: Lectures on a Theory of Computation and Complexity over the Reals; Algorithmic Information Content, Church-Turing Thesis, Physical Entroph, and Maxwell's Demon; Physical Measures of Complexity; An Introduction to Chaos and Prediction; Hamiltonian Chaos in Nonlinear Polarized Optical Beam; Chemical Oscillators and Nonlinear Chemical Dynamics; Isotropic Navier-Stokes Turbulence. I. Qualitative Features and Basic Equations; Isotropic Navier-Stokes Turbulence. II. Statistical Approximation Methods; Lattice Gases; Data-Parallel Computation and the Connection Machine; Preimages and Forecasting for Cellular Automata; Lattice-Gas Models for Multiphase Flows and Magnetohydrodynamics; Probabilistic Cellular Automata: Some Statistical Mechanical Considerations; Complexity Due to Disorder and Frustration; Self-Organization by Simulated Evolution; Theoretical Immunology; Morphogenesis by Cell Intercalation; and Theoretical Physics Meets Experimental Neurobiology
Interactive Dynamic-System Simulation
Korn, Granino A
2010-01-01
Showing you how to use personal computers for modeling and simulation, Interactive Dynamic-System Simulation, Second Edition provides a practical tutorial on interactive dynamic-system modeling and simulation. It discusses how to effectively simulate dynamical systems, such as aerospace vehicles, power plants, chemical processes, control systems, and physiological systems. Written by a pioneer in simulation, the book introduces dynamic-system models and explains how software for solving differential equations works. After demonstrating real simulation programs with simple examples, the author
Dynamic coherence in excitonic molecular complexes under various excitation conditions
Energy Technology Data Exchange (ETDEWEB)
Chenu, Aurélia; Malý, Pavel; Mančal, Tomáš, E-mail: mancal@karlov.mff.cuni.cz
2014-08-17
Highlights: • Dynamic coherence does not improve energy transfer efficiency in natural conditions. • Photo-induced quantum jumps are discussed in classical context. • Natural time scale of a light excitation event is identified. • Coherence in FMO complex averages out under excitation by neighboring antenna. • This result is valid even in absence of dissipation. - Abstract: We investigate the relevance of dynamic quantum coherence in the energy transfer efficiency of molecular aggregates. We derive the time evolution of the density matrix for an open quantum system excited by light or by a neighboring antenna. Unlike in the classical case, the quantum description does not allow for a formal decomposition of the dynamics into sudden jumps in an observable quantity – an expectation value. Rather, there is a natural finite time-scale associated with the excitation process. We propose a simple experiment to test the influence of this time scale on the yield of photosynthesis. We demonstrate, using typical parameters of the Fenna–Matthews–Olson (FMO) complex and a typical energy transfer rate from the chlorosome baseplate, that dynamic coherences are averaged out in the complex even when the FMO model is completely free of all dissipation and dephasing.
Complexity and network dynamics in physiological adaptation: an integrated view.
Baffy, György; Loscalzo, Joseph
2014-05-28
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.
Wisdom, Jack
2002-01-01
In these 18 years, the research has touched every major dynamical problem in the solar system, including: the effect of chaotic zones on the distribution of asteroids, the delivery of meteorites along chaotic pathways, the chaotic motion of Pluto, the chaotic motion of the outer planets and that of the whole solar system, the delivery of short period comets from the Kuiper belt, the tidal evolution of the Uranian arid Galilean satellites, the chaotic tumbling of Hyperion and other irregular satellites, the large chaotic variations of the obliquity of Mars, the evolution of the Earth-Moon system, and the resonant core- mantle dynamics of Earth and Venus. It has introduced new analytical and numerical tools that are in widespread use. Today, nearly every long-term integration of our solar system, its subsystems, and other solar systems uses algorithms that was invented. This research has all been primarily Supported by this sequence of PGG NASA grants. During this period published major investigations of tidal evolution of the Earth-Moon system and of the passage of the Earth and Venus through non-linear core-mantle resonances were completed. It has published a major innovation in symplectic algorithms: the symplectic corrector. A paper was completed on non-perturbative hydrostatic equilibrium.
A paradox for traffic dynamics in complex networks with ATIS
International Nuclear Information System (INIS)
Zheng Jianfeng; Gao Ziyou
2008-01-01
In this work, we study the statistical properties of traffic (e.g., vehicles) dynamics in complex networks, by introducing advanced transportation information systems (ATIS). The ATIS can provide the information of traffic flow pattern throughout the network and have an obvious effect on path routing strategy for such vehicles equipped with ATIS. The ATIS can be described by the understanding of link cost functions. Different indices such as efficiency and system total cost are discussed in depth. It is found that, for random networks (scale-free networks), the efficiency is effectively improved (decreased) if ATIS is properly equipped; however the system total cost is largely increased (decreased). It indicates that there exists a paradox between the efficiency and system total cost in complex networks. Furthermore, we report the simulation results by considering different kinds of link cost functions, and the paradox is recovered. Finally, we extend our traffic model, and also find the existence of the paradox
Language Networks as Complex Systems
Lee, Max Kueiming; Ou, Sheue-Jen
2008-01-01
Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…
FRAM Modelling Complex Socio-technical Systems
Hollnagel, Erik
2012-01-01
There has not yet been a comprehensive method that goes behind 'human error' and beyond the failure concept, and various complicated accidents have accentuated the need for it. The Functional Resonance Analysis Method (FRAM) fulfils that need. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, and understand both why things sometimes go wrong but also why they normally succeed.
What Is a Complex Innovation System?
Katz, J. Sylvan
2016-01-01
Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too. PMID:27258040
What Is a Complex Innovation System?
Directory of Open Access Journals (Sweden)
J Sylvan Katz
Full Text Available Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.
Practical synchronization on complex dynamical networks via optimal pinning control
Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu
2015-07-01
We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.
Hidden attractors in dynamical systems
Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh
2016-06-01
Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.
Unified Computational Intelligence for Complex Systems
Seiffertt, John
2010-01-01
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e
Kularathna, M.D.U.P.
1992-01-01
The technique of Stochastic Dynamic Programming (SDP) is ideally suited for operation policy analyses of water resources systems. However SDP has a major drawback which is appropriately termed as its "curse of dimensionality".
Aggregation/Disaggregation techniques based on SDP and
Metric for Calculation of System Complexity based on its Connections
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João Ricardo Braga de Paiva
2017-02-01
Full Text Available This paper proposes a methodology based on system connections to calculate its complexity. Two study cases are proposed: the dining Chinese philosophers’ problem and the distribution center. Both studies are modeled using the theory of Discrete Event Systems and simulations in different contexts were performed in order to measure their complexities. The obtained results present i the static complexity as a limiting factor for the dynamic complexity, ii the lowest cost in terms of complexity for each unit of measure of the system performance and iii the output sensitivity to the input parameters. The associated complexity and performance measures aggregate knowledge about the system.
Quantum transport in complex system
International Nuclear Information System (INIS)
Kusnezov, D.; Bulgac, A.; DoDang, G.
1998-01-01
We derive the influence function and the effective dynamics of a quantum systems coupled to a chaotic environment, using very general parametric and banded random matrices to describe the quantum properties of a chaotic bath. We find that only in certain limits the thermalization can result from the environment. We study the general transport problems including escape, fusion and tunneling (fission). (author)
Dependability problems of complex information systems
Zamojski, Wojciech
2014-01-01
This monograph presents original research results on selected problems of dependability in contemporary Complex Information Systems (CIS). The ten chapters are concentrated around the following three aspects: methods for modelling of the system and its components, tasks ? or in more generic and more adequate interpretation, functionalities ? accomplished by the system and conditions for their correct realization in the dynamic operational environment. While the main focus is on theoretical advances and roadmaps for implementations of new technologies, a?much needed forum for sharing of the bes
Integration of the immune system: a complex adaptive supersystem
Crisman, Mark V.
2001-10-01
Immunity to pathogenic organisms is a complex process involving interacting factors within the immune system including circulating cells, tissues and soluble chemical mediators. Both the efficiency and adaptive responses of the immune system in a dynamic, often hostile, environment are essential for maintaining our health and homeostasis. This paper will present a brief review of one of nature's most elegant, complex adaptive systems.
On Rank Driven Dynamical Systems
Veerman, J. J. P.; Prieto, F. J.
2014-08-01
We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.
Interval stability for complex systems
Klinshov, Vladimir V.; Kirillov, Sergey; Kurths, Jürgen; Nekorkin, Vladimir I.
2018-04-01
Stability of dynamical systems against strong perturbations is an important problem of nonlinear dynamics relevant to many applications in various areas. Here, we develop a novel concept of interval stability, referring to the behavior of the perturbed system during a finite time interval. Based on this concept, we suggest new measures of stability, namely interval basin stability (IBS) and interval stability threshold (IST). IBS characterizes the likelihood that the perturbed system returns to the stable regime (attractor) in a given time. IST provides the minimal magnitude of the perturbation capable to disrupt the stable regime for a given interval of time. The suggested measures provide important information about the system susceptibility to external perturbations which may be useful for practical applications. Moreover, from a theoretical viewpoint the interval stability measures are shown to bridge the gap between linear and asymptotic stability. We also suggest numerical algorithms for quantification of the interval stability characteristics and demonstrate their potential for several dynamical systems of various nature, such as power grids and neural networks.
Storey, Brian; Butler, Joy
2013-01-01
Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking"…
Dynamic Systems Modeling in Educational System Design & Policy
Groff, Jennifer Sterling
2013-01-01
Over the last several hundred years, local and national educational systems have evolved from relatively simple systems to incredibly complex, interdependent, policy-laden structures, to which many question their value, effectiveness, and direction they are headed. System Dynamics is a field of analysis used to guide policy and system design in…
Dynamical versus diffraction spectrum for structures with finite local complexity
Baake, Michael; Lenz, Daniel; van Enter, Aernout
2015-01-01
It is well known that the dynamical spectrum of an ergodic measure dynamical system is related to the diffraction measure of a typical element of the system. This situation includes ergodic subshifts from symbolic dynamics as well as ergodic Delone dynamical systems, both via suitable embeddings.
Controller Design of Complex System Based on Nonlinear Strength
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Rongjun Mu
2015-01-01
Full Text Available This paper presents a new idea of controller design for complex systems. The nonlinearity index method was first developed for error propagation of nonlinear system. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of the system model. The algorithm of nonlinearity index according to engineering application is first proposed in this paper. Applying this method on nonlinear systems is an effective way to measure the nonlinear strength of dynamics model over the full flight envelope. The nonlinearity indices access the boundary between the strong and the weak nonlinearities of system model. According to the different nonlinear strength of dynamical model, the control system is designed. The simulation time of dynamical complex system is selected by the maximum value of dynamic nonlinearity indices. Take a missile as example; dynamical system and control characteristic of missile are simulated. The simulation results show that the method is correct and appropriate.
Physical approach to complex systems
Kwapień, Jarosław; Drożdż, Stanisław
2012-06-01
Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. As a result, they are flexible and easily adapt to variable external conditions. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence-consolidated also in the present review-that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. Physics methodology proves helpful in addressing many of the related issues. In this review, we advocate some of the computational methods which in our opinion are especially fruitful in extracting information on selected-but at the same time most representative-complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems. The properties we focus on comprise the collective effects and their coexistence with noise, long-range interactions, the interplay between determinism and flexibility in evolution, scale invariance, criticality, multifractality and hierarchical structure. The methods described either originate from “hard” physics-like the random matrix theory-and then were transmitted to other fields of science via the field of complex systems research, or they originated elsewhere but
The dynamical complexity of optically injected semiconductor lasers
International Nuclear Information System (INIS)
Wieczorek, S.; Krauskopf, B.; Simpson, T.B.; Lenstra, D.
2005-01-01
This report presents a modern approach to the theoretical and experimental study of complex nonlinear behavior of a semiconductor laser with optical injection-an example of a widely applied and technologically relevant forced nonlinear oscillator. We show that the careful bifurcation analysis of a rate equation model yields (i) a deeper understanding of already studied physical phenomena, and (ii) the discovery of new dynamical effects, such as multipulse excitability. Different instabilities, cascades of bifurcations, multistability, and sudden chaotic transitions, which are often viewed as independent, are in fact logically connected into a consistent web of bifurcations via special points called organizing centers. This theoretical bifurcation analysis has predictive power, which manifests itself in good agreement with experimental measurements over a wide range of parameters and diversity of dynamics. While it is dealing with the specific system of an optically injected laser, our work constitutes the state-of-the-art in the understanding and modeling of a nonlinear physical system in general
Classroom-oriented research from a complex systems perspective
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Diane Larsen-Freeman
2016-09-01
Full Text Available Bringing a complex systems perspective to bear on classroom-oriented research challenges researchers to think differently, seeing the classroom ecology as one dynamic system nested in a hierarchy of such systems at different levels of scale, all of which are spatially and temporally situated. This article begins with an introduction to complex dynamic systems theory, in which challenges to traditional ways of conducting classroom research are interwoven. It concludes with suggestions for research methods that are more consistent with the theory. Research does not become easier when approached from a complex systems perspective, but it has the virtue of reflecting the way the world works.
Cosmological dynamical systems
Leon, Genly
2011-01-01
In this book are studied, from the perspective of the dynamical systems, several Universe models. In chapter 1 we give a bird's eye view on cosmology and cosmological problems. Chapter 2 is devoted to a brief review on some results and useful tools from the qualitative theory of dynamical systems. They provide the theoretical basis for the qualitative study of concrete cosmological models. Chapters 1 and 2 are a review of well-known results. Chapters 3, 4, 5 and 6 are devoted to our main results. In these chapters are extended and settled in a substantially different, more strict mathematical language, several results obtained by one of us in arXiv:0812.1013 [gr-qc]; arXiv:1009.0689 [gr-qc]; arXiv:0904.1577[gr-qc]; and arXiv:0909.3571 [hep-th]. In chapter 6, we provide a different approach to the subject discussed in astro-ph/0503478. Additionally, we perform a Poincar\\'e compactification process allowing to construct a global phase space containing all the cosmological information in both finite and infinite...
Dynamics of stochastic systems
Klyatskin, Valery I
2005-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...
Complexity in electronic negotiation support systems.
Griessmair, Michele; Strunk, Guido; Vetschera, Rudolf; Koeszegi, Sabine T
2011-10-01
It is generally acknowledged that the medium influences the way we communicate and negotiation research directs considerable attention to the impact of different electronic communication modes on the negotiation process and outcomes. Complexity theories offer models and methods that allow the investigation of how pattern and temporal sequences unfold over time in negotiation interactions. By focusing on the dynamic and interactive quality of negotiations as well as the information, choice, and uncertainty contained in the negotiation process, the complexity perspective addresses several issues of central interest in classical negotiation research. In the present study we compare the complexity of the negotiation communication process among synchronous and asynchronous negotiations (IM vs. e-mail) as well as an electronic negotiation support system including a decision support system (DSS). For this purpose, transcripts of 145 negotiations have been coded and analyzed with the Shannon entropy and the grammar complexity. Our results show that negotiating asynchronically via e-mail as well as including a DSS significantly reduces the complexity of the negotiation process. Furthermore, a reduction of the complexity increases the probability of reaching an agreement.
Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks
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Jose P. Perez
2014-01-01
Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.
Chaos from simple models to complex systems
Cencini, Massimo; Vulpiani, Angelo
2010-01-01
Chaos: from simple models to complex systems aims to guide science and engineering students through chaos and nonlinear dynamics from classical examples to the most recent fields of research. The first part, intended for undergraduate and graduate students, is a gentle and self-contained introduction to the concepts and main tools for the characterization of deterministic chaotic systems, with emphasis to statistical approaches. The second part can be used as a reference by researchers as it focuses on more advanced topics including the characterization of chaos with tools of information theor
Dynamics in electron transfer protein complexes
Bashir, Qamar
2010-01-01
Recent studies have provided experimental evidence for the existence of an encounter complex, a transient intermediate in the formation of protein complexes. We have used paramagnetic relaxation enhancement NMR spectroscopy in combination with Monte Carlo simulations to characterize and visualize
Reaction dynamics in polyatomic molecular systems
Energy Technology Data Exchange (ETDEWEB)
Miller, W.H. [Lawrence Berkeley Laboratory, CA (United States)
1993-12-01
The goal of this program is the development of theoretical methods and models for describing the dynamics of chemical reactions, with specific interest for application to polyatomic molecular systems of special interest and relevance. There is interest in developing the most rigorous possible theoretical approaches and also in more approximate treatments that are more readily applicable to complex systems.
The topology and dynamics of complex networks
Dezso, Zoltan
We start with a brief introduction about the topological properties of real networks. Most real networks are scale-free, being characterized by a power-law degree distribution. The scale-free nature of real networks leads to unexpected properties such as the vanishing epidemic threshold. Traditional methods aiming to reduce the spreading rate of viruses cannot succeed on eradicating the epidemic on a scale-free network. We demonstrate that policies that discriminate between the nodes, curing mostly the highly connected nodes, can restore a finite epidemic threshold and potentially eradicate the virus. We find that the more biased a policy is towards the hubs, the more chance it has to bring the epidemic threshold above the virus' spreading rate. We continue by studying a large Web portal as a model system for a rapidly evolving network. We find that the visitation pattern of a news document decays as a power law, in contrast with the exponential prediction provided by simple models of site visitation. This is rooted in the inhomogeneous nature of the browsing pattern characterizing individual users: the time interval between consecutive visits by the same user to the site follows a power law distribution, in contrast with the exponential expected for Poisson processes. We show that the exponent characterizing the individual user's browsing patterns determines the power-law decay in a document's visitation. Finally, we turn our attention to biological networks and demonstrate quantitatively that protein complexes in the yeast, Saccharomyces cerevisiae, are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or non-essential) and share identical functional classification and cellular localization. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.
Complex network synchronization of chaotic systems with delay coupling
International Nuclear Information System (INIS)
Theesar, S. Jeeva Sathya; Ratnavelu, K.
2014-01-01
The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology
The nonlinear dynamics of a coupled fission system
International Nuclear Information System (INIS)
Bilanovic, Z.; Harms, A.A.
1993-01-01
The dynamic properties of a nonlinear and in situ vibrationally perturbed nuclear-to-thermal coupled neutron multiplying medium are examined. Some unique self-organizational temporal patterns appear in such fission systems and suggest a complex underlying dynamic. (Author)
Complex Dynamics of an Adnascent-Type Game Model
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Baogui Xin
2008-01-01
Full Text Available The paper presents a nonlinear discrete game model for two oligopolistic firms whose products are adnascent. (In biology, the term adnascent has only one sense, “growing to or on something else,” e.g., “moss is an adnascent plant.” See Webster's Revised Unabridged Dictionary published in 1913 by C. & G. Merriam Co., edited by Noah Porter. The bifurcation of its Nash equilibrium is analyzed with Schwarzian derivative and normal form theory. Its complex dynamics is demonstrated by means of the largest Lyapunov exponents, fractal dimensions, bifurcation diagrams, and phase portraits. At last, bifurcation and chaos anticontrol of this system are studied.
Directory of Open Access Journals (Sweden)
Xinwei Wang
2017-01-01
Full Text Available Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.
Dynamic complexities in a parasitoid-host-parasitoid ecological model
International Nuclear Information System (INIS)
Yu Hengguo; Zhao Min; Lv Songjuan; Zhu Lili
2009-01-01
Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model
Dynamic complexities in a parasitoid-host-parasitoid ecological model
Energy Technology Data Exchange (ETDEWEB)
Yu Hengguo [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China); Zhao Min [School of Life and Environmental Science, Wenzhou University, Wenzhou, Zhejiang 325027 (China)], E-mail: zmcn@tom.com; Lv Songjuan; Zhu Lili [School of Mathematic and Information Science, Wenzhou University, Wenzhou, Zhejiang 325035 (China)
2009-01-15
Chaotic dynamics have been observed in a wide range of population models. In this study, the complex dynamics in a discrete-time ecological model of parasitoid-host-parasitoid are presented. The model shows that the superiority coefficient not only stabilizes the dynamics, but may strongly destabilize them as well. Many forms of complex dynamics were observed, including pitchfork bifurcation with quasi-periodicity, period-doubling cascade, chaotic crisis, chaotic bands with narrow or wide periodic window, intermittent chaos, and supertransient behavior. Furthermore, computation of the largest Lyapunov exponent demonstrated the chaotic dynamic behavior of the model.
Quantum Dynamics in Biological Systems
Shim, Sangwoo
In the first part of this dissertation, recent efforts to understand quantum mechanical effects in biological systems are discussed. Especially, long-lived quantum coherences observed during the electronic energy transfer process in the Fenna-Matthews-Olson complex at physiological condition are studied extensively using theories of open quantum systems. In addition to the usual master equation based approaches, the effect of the protein structure is investigated in atomistic detail through the combined application of quantum chemistry and molecular dynamics simulations. To evaluate the thermalized reduced density matrix, a path-integral Monte Carlo method with a novel importance sampling approach is developed for excitons coupled to an arbitrary phonon bath at a finite temperature. In the second part of the thesis, simulations of molecular systems and applications to vibrational spectra are discussed. First, the quantum dynamics of a molecule is simulated by combining semiclassical initial value representation and density funcitonal theory with analytic derivatives. A computationally-tractable approximation to the sum-of-states formalism of Raman spectra is subsequently discussed.
On some dynamical chameleon systems
Burkin, I. M.; Kuznetsova, O. I.
2018-03-01
It is now well known that dynamical systems can be categorized into systems with self-excited attractors and systems with hidden attractors. A self-excited attractor has a basin of attraction that is associated with an unstable equilibrium, while a hidden attractor has a basin of attraction that does not intersect with small neighborhoods of any equilibrium points. Hidden attractors play the important role in engineering applications because they allow unexpected and potentially disastrous responses to perturbations in a structure like a bridge or an airplane wing. In addition, complex behaviors of chaotic systems have been applied in various areas from image watermarking, audio encryption scheme, asymmetric color pathological image encryption, chaotic masking communication to random number generator. Recently, researchers have discovered the so-called “chameleon systems”. These systems were so named because they demonstrate self-excited or hidden oscillations depending on the value of parameters. The present paper offers a simple algorithm of synthesizing one-parameter chameleon systems. The authors trace the evolution of Lyapunov exponents and the Kaplan-Yorke dimension of such systems which occur when parameters change.
Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application
Li, Xiang
2005-01-01
In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...
Morphodynamics: Ergodic theory of complex systems
International Nuclear Information System (INIS)
Fivaz, R.
1993-01-01
Morphodynamics is a general theory of stationary complex systems, such as living systems, or mental and social systems; it is based on the thermodynamics of physical systems and built on the same lines. By means of the ergodic hypothesis, thermodynamics is known to connect the particle dynamics to the emergence of order parameters in the equations of state. In the same way, morphodynamics connects order parameters to the emergence of higher level variables; through recurrent applications of the ergodic hypothesis, a hierarchy of equations of state is established which describes a series of successive levels of organization. The equations support a cognitivist interpretation that leads to general principles of evolution; the principles determine the spontaneous and irreversible complexification of systems living in their natural environment. 19 refs
Dynamic polarizability of a complex atom in strong laser fields
International Nuclear Information System (INIS)
Rapoport, L.P.; Klinskikh, A.F.; Mordvinov, V.V.
1997-01-01
An asymptotic expansion of the dynamic polarizability of a complex atom in a strong circularly polarized light field is found for the case of high frequencies. The self-consistent approximation of the Hartree-Fock type for the ''atom+field'' system is developed, within the framework of which a numerical calculation of the dynamic polarizability of Ne, Kr, and Ar atoms in a strong radiation field is performed. The strong field effect is shown to manifest itself not only in a change of the energy spectrum and the character of behavior of the wave functions of atomic electrons, but also in a modification of the one-electron self-consistent potential for the atom in the field
Synchronization of complex delayed dynamical networks with nonlinearly coupled nodes
International Nuclear Information System (INIS)
Liu Tao; Zhao Jun; Hill, David J.
2009-01-01
In this paper, we study the global synchronization of nonlinearly coupled complex delayed dynamical networks with both directed and undirected graphs. Via Lyapunov-Krasovskii stability theory and the network topology, we investigate the global synchronization of such networks. Under the assumption that coupling coefficients are known, a family of delay-independent decentralized nonlinear feedback controllers are designed to globally synchronize the networks. When coupling coefficients are unavailable, an adaptive mechanism is introduced to synthesize a family of delay-independent decentralized adaptive controllers which guarantee the global synchronization of the uncertain networks. Two numerical examples of directed and undirected delayed dynamical network are given, respectively, using the Lorenz system as the nodes of the networks, which demonstrate the effectiveness of proposed results.
Relaxation and Diffusion in Complex Systems
Ngai, K L
2011-01-01
Relaxation and Diffusion in Complex Systems comprehensively presents a variety of experimental evidences of universal relaxation and diffusion properties in complex materials and systems. The materials discussed include liquids, glasses, colloids, polymers, rubbers, plastic crystals and aqueous mixtures, as well as carbohydrates, biomolecules, bioprotectants and pharmaceuticals. Due to the abundance of experimental data, emphasis is placed on glass-formers and the glass transition problem, a still unsolved problem in condensed matter physics and chemistry. The evidence for universal properties of relaxation and diffusion dynamics suggests that a fundamental physical law is at work. The origin of the universal properties is traced to the many-body effects of the interaction, rigorous theory of which does not exist at the present time. However, using solutions of simplified models as guides, key quantities have been identified and predictions of the universal properties generated. These predictions from Ngai’...
Synchronization dynamics of two different dynamical systems
International Nuclear Information System (INIS)
Luo, Albert C.J.; Min Fuhong
2011-01-01
Highlights: → Synchronization dynamics of two distinct dynamical systems. → Synchronization, de-synchronization and instantaneous synchronization. → A controlled pendulum synchronizing with the Duffing oscillator. → Synchronization invariant set. → Synchronization parameter map. - Abstract: In this paper, synchronization dynamics of two different dynamical systems is investigated through the theory of discontinuous dynamical systems. The necessary and sufficient conditions for the synchronization, de-synchronization and instantaneous synchronization (penetration or grazing) are presented. Using such a synchronization theory, the synchronization of a controlled pendulum with the Duffing oscillator is systematically discussed as a sampled problem, and the corresponding analytical conditions for the synchronization are presented. The synchronization parameter study is carried out for a better understanding of synchronization characteristics of the controlled pendulum and the Duffing oscillator. Finally, the partial and full synchronizations of the controlled pendulum with periodic and chaotic motions are presented to illustrate the analytical conditions. The synchronization of the Duffing oscillator and pendulum are investigated in order to show the usefulness and efficiency of the methodology in this paper. The synchronization invariant domain is obtained. The technique presented in this paper should have a wide spectrum of applications in engineering. For example, this technique can be applied to the maneuvering target tracking, and the others.
Semiotics of constructed complex systems
Energy Technology Data Exchange (ETDEWEB)
Landauer, C.; Bellman, K.L.
1996-12-31
The scope of this paper is limited to software and other constructed complex systems mediated or integrated by software. Our research program studies foundational issues that we believe will help us develop a theoretically sound approach to constructing complex systems. There have really been only two theoretical approaches that have helped us understand and develop computational systems: mathematics and linguistics. We show how semiotics can also play a role, whether we think of it as part of these other theories or as subsuming one or both of them. We describe our notion of {open_quotes}computational semiotics{close_quotes}, which we define to be the study of computational methods of dealing with symbols, show how such a theory might be formed, and describe what we might get from it in terms of more interesting use of symbols by computing systems. This research was supported in part by the Federal Highway Administration`s Office of Advanced Research and by the Advanced Research Projects Agency`s Software and Intelligent Systems Technology Office.
5th International Conference on Complex Systems
Braha, Dan; Bar-Yam, Yaneer
2011-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.
7th International Conference on Complex Systems
Braha, Dan; Bar-Yam, Yaneer
2012-01-01
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.
Dynamical baryogenesis through complex hybrid inflation
International Nuclear Information System (INIS)
Delepine, D; MartInez, C; Urena-Lopez, L A
2008-01-01
We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U (1) global symmetry associated to the waterfall field charge. We show that the asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry [1
Dynamical baryogenesis through complex hybrid inflation
Energy Technology Data Exchange (ETDEWEB)
Delepine, D; MartInez, C; Urena-Lopez, L A [Instituto de Fisica de la Universidad de Guanajuato, C.P. 37150, Leon, Guanajuato (Mexico)], E-mail: delepine@fisica.ugto.mx, E-mail: crmtz@fisica.ugto.mx, E-mail: lurena@fisica.ugto.mx
2008-06-01
We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U (1) global symmetry associated to the waterfall field charge. We show that the asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry [1].
Charge-Transfer Complexes Studied by Dynamic Force Spectroscopy
Directory of Open Access Journals (Sweden)
Jurriaan Huskens
2013-03-01
Full Text Available In this paper, the strength and kinetics of two charge-transfer complexes, naphthol-methylviologen and pyrene-methylviologen, are studied using dynamic force spectroscopy. The dissociation rates indicate an enhanced stability of the pyrene-methylviologen complex, which agrees with its higher thermodynamic stability compared to naphthol-methylviologen complex.
From globally coupled maps to complex-systems biology
Energy Technology Data Exchange (ETDEWEB)
Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp [Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan)
2015-09-15
Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.
Complex Physical, Biophysical and Econophysical Systems
Dewar, Robert L.; Detering, Frank
1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.
Messina, Joseph Paul
landscape strata and study area locations related to development corridors along transportation networks and expanding urban environments. The presented research combines household survey data with biophysical and geographical data through a spatio-temporal modeling context that links complexity theory and landscape ecology to a GIS and remote sensing analytical framework to increase the understanding of landscape dynamics across time, space, and landscape strata.
Absorption dynamics and delay time in complex potentials
Villavicencio, Jorge; Romo, Roberto; Hernández-Maldonado, Alberto
2018-05-01
The dynamics of absorption is analyzed by using an exactly solvable model that deals with an analytical solution to Schrödinger’s equation for cutoff initial plane waves incident on a complex absorbing potential. A dynamical absorption coefficient which allows us to explore the dynamical loss of particles from the transient to the stationary regime is derived. We find that the absorption process is characterized by the emission of a series of damped periodic pulses in time domain, associated with damped Rabi-type oscillations with a characteristic frequency, ω = (E + ε)/ℏ, where E is the energy of the incident waves and ‑ε is energy of the quasidiscrete state of the system induced by the absorptive part of the Hamiltonian; the width γ of this resonance governs the amplitude of the pulses. The resemblance of the time-dependent absorption coefficient with a real decay process is discussed, in particular the transition from exponential to nonexponential regimes, a well-known feature of quantum decay. We have also analyzed the effect of the absorptive part of the potential on the dynamical delay time, which behaves differently from the one observed in attractive real delta potentials, exhibiting two regimes: time advance and time delay.
Computational models of complex systems
Dabbaghian, Vahid
2014-01-01
Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the reader...
Dynamical Signatures of Living Systems
Zak, M.
1999-01-01
One of the main challenges in modeling living systems is to distinguish a random walk of physical origin (for instance, Brownian motions) from those of biological origin and that will constitute the starting point of the proposed approach. As conjectured, the biological random walk must be nonlinear. Indeed, any stochastic Markov process can be described by linear Fokker-Planck equation (or its discretized version), only that type of process has been observed in the inanimate world. However, all such processes always converge to a stable (ergodic or periodic) state, i.e., to the states of a lower complexity and high entropy. At the same time, the evolution of living systems directed toward a higher level of complexity if complexity is associated with a number of structural variations. The simplest way to mimic such a tendency is to incorporate a nonlinearity into the random walk; then the probability evolution will attain the features of diffusion equation: the formation and dissipation of shock waves initiated by small shallow wave disturbances. As a result, the evolution never "dies:" it produces new different configurations which are accompanied by an increase or decrease of entropy (the decrease takes place during formation of shock waves, the increase-during their dissipation). In other words, the evolution can be directed "against the second law of thermodynamics" by forming patterns outside of equilibrium in the probability space. Due to that, a specie is not locked up in a certain pattern of behavior: it still can perform a variety of motions, and only the statistics of these motions is constrained by this pattern. It should be emphasized that such a "twist" is based upon the concept of reflection, i.e., the existence of the self-image (adopted from psychology). The model consists of a generator of stochastic processes which represents the motor dynamics in the form of nonlinear random walks, and a simulator of the nonlinear version of the diffusion
Chaos for Discrete Dynamical System
Directory of Open Access Journals (Sweden)
Lidong Wang
2013-01-01
Full Text Available We prove that a dynamical system is chaotic in the sense of Martelli and Wiggins, when it is a transitive distributively chaotic in a sequence. Then, we give a sufficient condition for the dynamical system to be chaotic in the strong sense of Li-Yorke. We also prove that a dynamical system is distributively chaotic in a sequence, when it is chaotic in the strong sense of Li-Yorke.
Dynamical Systems for Creative Technology
van Amerongen, J.
2010-01-01
Dynamical Systems for Creative Technology gives a concise description of the physical properties of electrical, mechanical and hydraulic systems. Emphasis is placed on modelling the dynamical properties of these systems. By using a system’s approach it is shown that a limited number of mathematical
Directory of Open Access Journals (Sweden)
Jianhua Xu
2013-01-01
Full Text Available Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD, classical statistics, and geostatistics. The main conclusions are as follows (1 The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2 The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3 The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform.
Narrowing the gap between network models and real complex systems
Viamontes Esquivel, Alcides
2014-01-01
Simple network models that focus only on graph topology or, at best, basic interactions are often insufficient to capture all the aspects of a dynamic complex system. In this thesis, I explore those limitations, and some concrete methods of resolving them. I argue that, in order to succeed at interpreting and influencing complex systems, we need to take into account slightly more complex parts, interactions and information flows in our models.This thesis supports that affirmation with five a...
Dynamical Baryogenesis in Complex Hybrid Inflation
International Nuclear Information System (INIS)
Delepine, David; Martinez, Carlos; Urena-Lopez, L. Arturo
2008-01-01
We propose a hybrid inflation model with a complex waterfall field which contains an interaction term that breaks the U (1) global symmetry associated to the waterfall field charge. We show that the asymmetric evolution of the real and imaginary parts of the complex field during the phase transition at the end of inflation translates into a charge asymmetry. The latter strongly depends on the vev of the waterfall field, which is well constrained by diverse cosmological observations
Complex systems fractionality, time-delay and synchronization
Sun, Jian-Qiao
2012-01-01
"Complex Systems: Fractionality, Time-delay and Synchronization" covers the most recent developments and advances in the theory and application of complex systems in these areas. Each chapter was written by scientists highly active in the field of complex systems. The book discusses a new treatise on fractional dynamics and control, as well as the new methods for differential delay systems and control. Lastly, a theoretical framework for the complexity and synchronization of complex system is presented. The book is intended for researchers in the field of nonlinear dynamics in mathematics, physics and engineering. It can also serve as a reference book for graduate students in physics, applied mathematics and engineering. Dr. Albert C.J. Luo is a Professor at Southern Illinois University Edwardsville, USA. Dr. Jian-Qiao Sun is a Professor at the University of California, Merced, USA.
Modeling Power Systems as Complex Adaptive Systems
Energy Technology Data Exchange (ETDEWEB)
Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.
2004-12-30
Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.
Holism and Emergence: Dynamical Complexity Defeats Laplace's ...
African Journals Online (AJOL)
ideal for scientific theories whose cogency is often not questioned. Laplace's demon is an idealization of mechanistic scientific method. Its principles together imply reducibility, and rule out holism and emergence. I will argue that Laplacean determinism fails even in the realm of planetary dynamics, and that it does not give ...
Stability in dynamical systems I
International Nuclear Information System (INIS)
Courant, E.D.; Ruth, R.D.; Weng, W.T.
1984-08-01
We have reviewed some of the basic techniques which can be used to analyze stability in nonlinear dynamical systems, particularly in circular particle accelerators. We have concentrated on one-dimensional systems in the examples in order to simply illustrate the general techniques. We began with a review of Hamiltonian dynamics and canonical transformations. We then reviewed linear equations with periodic coefficients using the basic techniques from accelerator theory. To handle nonlinear terms we developed a canonical perturbation theory. From this we calculated invariants and the amplitude dependence of the frequency. This led us to resonances. We studied the cubic resonance in detail by using a rotating coordinate system in phase space. We then considered a general isolated nonlinear resonance. In this case we calculated the width of the resonance and estimated the spacing of resonances in order to use the Chirikov criterion to restrict the validity of the analysis. Finally the resonance equation was reduced to the pendulum equation, and we examined the motion on a separatrix. This brought us to the beginnings of stochastic behavior in the neighborhood of the separatrix. It is this complex behavior in the neighborhood of the separatrix which causes the perturbation theory used here to diverge in many cases. In spite of this the methods developed here have been and are used quite successfully to study nonlinear effects in nearly integrable systems. When used with caution and in conjunction with numerical work they give tremendous insight into the nature of the phase space structure and the stability of nonlinear differential equations. 14 references
Dynamical Systems Approaches to Emotional Development
Camras, Linda A.; Witherington, David C.
2005-01-01
Within the last 20 years, transitions in the conceptualization of emotion and its development have given rise to calls for an explanatory framework that captures emotional development in all its organizational complexity and variability. Recent attempts have been made to couch emotional development in terms of a dynamical systems approach through…
Propagating wave correlations in complex systems
International Nuclear Information System (INIS)
Creagh, Stephen C; Gradoni, Gabriele; Hartmann, Timo; Tanner, Gregor
2017-01-01
We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dynamics. By defining appropriate ensemble averages, we show that fluctuations about the mean can be characterised in terms of classical correlations. We give in particular an explicit expression relating fluctuations of diagonal contributions to those of the full wave correlation function. The methods have a wide range of applications both in quantum mechanics and for classical wave problems such as in vibro-acoustics and electromagnetism. We apply the methods here to simple quantum systems, so-called quantum maps, which model the behaviour of generic problems on Poincaré sections. Although low-dimensional, these models exhibit a chaotic classical limit and share common characteristics with wave propagation in complex structures. (paper)
Simulating Complex Systems by Cellular Automata
Kroc, Jiri; Hoekstra, Alfons G
2010-01-01
Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on th...
Energy Technology Data Exchange (ETDEWEB)
Thomas, Javix; Xu, Yunjie, E-mail: yunjie.xu@ualberta.ca [Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 (Canada)
2014-06-21
The hydrogen-bonding topology and tunneling dynamics of the binary adduct, 2,2,2-trifluoroethanol (TFE)⋯water, were investigated using chirped pulse and cavity based Fourier transform microwave spectroscopy with the aid of high level ab initio calculations. Rotational spectra of the most stable binary TFE⋯water conformer and five of its deuterium isotopologues were assigned. A strong preference for the insertion binding topology where water is inserted into the existing intramolecular hydrogen-bonded ring of TFE was observed. Tunneling splittings were detected in all of the measured rotational transitions of TFE⋯water. Based on the relative intensity of the two tunneling components and additional isotopic data, the splitting can be unambiguously attributed to the tunneling motion of the water subunit, i.e., the interchange of the bonded and nonbonded hydrogen atoms of water. The absence of any other splitting in the rotational transitions of all isotopologues observed indicates that the tunneling between g+ and g− TFE is quenched in the TFE⋯H{sub 2}O complex.
Interdisciplinary Symposium on Complex Systems
Zelinka, Ivan; Rössler, Otto
2014-01-01
The book you hold in your hands is the outcome of the "ISCS 2013: Interdisciplinary Symposium on Complex Systems" held at the historical capital of Bohemia as a continuation of our series of symposia in the science of complex systems. Prague, one of the most beautiful European cities, has its own beautiful genius loci. Here, a great number of important discoveries were made and many important scientists spent fruitful and creative years to leave unforgettable traces. The perhaps most significant period was the time of Rudolf II who was a great supporter of the art and the science and attracted a great number of prominent minds to Prague. This trend would continue. Tycho Brahe, Niels Henrik Abel, Johannes Kepler, Bernard Bolzano, August Cauchy Christian Doppler, Ernst Mach, Albert Einstein and many others followed developing fundamental mathematical and physical theories or expanding them. Thus in the beginning of the 17th century, Kepler formulated here the first two of his three laws of planetary motion on ...
Lagardère, Louis; Jolly, Luc-Henri; Lipparini, Filippo; Aviat, Félix; Stamm, Benjamin; Jing, Zhifeng F; Harger, Matthew; Torabifard, Hedieh; Cisneros, G Andrés; Schnieders, Michael J; Gresh, Nohad; Maday, Yvon; Ren, Pengyu Y; Ponder, Jay W; Piquemal, Jean-Philip
2018-01-28
We present Tinker-HP, a massively MPI parallel package dedicated to classical molecular dynamics (MD) and to multiscale simulations, using advanced polarizable force fields (PFF) encompassing distributed multipoles electrostatics. Tinker-HP is an evolution of the popular Tinker package code that conserves its simplicity of use and its reference double precision implementation for CPUs. Grounded on interdisciplinary efforts with applied mathematics, Tinker-HP allows for long polarizable MD simulations on large systems up to millions of atoms. We detail in the paper the newly developed extension of massively parallel 3D spatial decomposition to point dipole polarizable models as well as their coupling to efficient Krylov iterative and non-iterative polarization solvers. The design of the code allows the use of various computer systems ranging from laboratory workstations to modern petascale supercomputers with thousands of cores. Tinker-HP proposes therefore the first high-performance scalable CPU computing environment for the development of next generation point dipole PFFs and for production simulations. Strategies linking Tinker-HP to Quantum Mechanics (QM) in the framework of multiscale polarizable self-consistent QM/MD simulations are also provided. The possibilities, performances and scalability of the software are demonstrated via benchmarks calculations using the polarizable AMOEBA force field on systems ranging from large water boxes of increasing size and ionic liquids to (very) large biosystems encompassing several proteins as well as the complete satellite tobacco mosaic virus and ribosome structures. For small systems, Tinker-HP appears to be competitive with the Tinker-OpenMM GPU implementation of Tinker. As the system size grows, Tinker-HP remains operational thanks to its access to distributed memory and takes advantage of its new algorithmic enabling for stable long timescale polarizable simulations. Overall, a several thousand-fold acceleration over
Ab initio lattice dynamics of complex structures
DEFF Research Database (Denmark)
Voss, Johannes
2008-01-01
In this thesis, density functional theory is applied in a study of thermodynamic properties of so-called complex metal hydrides, which are promising materials for hydrogen storage applications. Since the unit cells of these crystals can be relatively large with many symmetrically inequivalent ato...
Complex dynamics in supervised work groups
Dal Forno, Arianna; Merlone, Ugo
2013-07-01
In supervised work groups many factors concur to determine productivity. Some of them may be economical and some psychological. According to the literature, the heterogeneity in terms of individual capacity seems to be one of the principal causes for chaotic dynamics in a work group. May sorting groups of people with same capacity for effort be a solution? In the organizational psychology literature an important factor is the engagement in the task, while expectations are central in the economics literature. Therefore, we propose a dynamical model which takes into account both engagement in the task and expectations. An important lesson emerges. The intolerance deriving from the exposure to inequity may not be only caused by differences in individual capacities, but also by these factors combined. Consequently, solutions have to be found in this new direction.
Controlling Uncertain Dynamical Systems
Indian Academy of Sciences (India)
Author Affiliations. N Ananthkrishnan1 Rashi Bansal2. Head, CAE Analysis & Design Zeus Numerix Pvt Ltd. M-03, SINE, IIT Bombay Powai Mumbai 400076, India. MTech (Aerospace Engineering) with specialization in Dynamics & Control from IIT Bombay.
Reliability assessment of complex electromechanical systems under epistemic uncertainty
International Nuclear Information System (INIS)
Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong
2016-01-01
The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.
The geometry of chaotic dynamics — a complex network perspective
Donner, R. V.; Heitzig, J.; Donges, J. F.; Zou, Y.; Marwan, N.; Kurths, J.
2011-12-01
Recently, several complex network approaches to time series analysis have been developed and applied to study a wide range of model systems as well as real-world data, e.g., geophysical or financial time series. Among these techniques, recurrence-based concepts and prominently ɛ-recurrence networks, most faithfully represent the geometrical fine structure of the attractors underlying chaotic (and less interestingly non-chaotic) time series. In this paper we demonstrate that the well known graph theoretical properties local clustering coefficient and global (network) transitivity can meaningfully be exploited to define two new local and two new global measures of dimension in phase space: local upper and lower clustering dimension as well as global upper and lower transitivity dimension. Rigorous analytical as well as numerical results for self-similar sets and simple chaotic model systems suggest that these measures are well-behaved in most non-pathological situations and that they can be estimated reasonably well using ɛ-recurrence networks constructed from relatively short time series. Moreover, we study the relationship between clustering and transitivity dimensions on the one hand, and traditional measures like pointwise dimension or local Lyapunov dimension on the other hand. We also provide further evidence that the local clustering coefficients, or equivalently the local clustering dimensions, are useful for identifying unstable periodic orbits and other dynamically invariant objects from time series. Our results demonstrate that ɛ-recurrence networks exhibit an important link between dynamical systems and graph theory.
Dynamic Reconfiguration in Mobile Systems
Smit, Gerardus Johannes Maria; Glesner, Manfred; Zipf, Peter; Smit, L.T.; Havinga, Paul J.M.; Heysters, P.M.; Renovell, Michel; Rosien, M.A.J.
Dynamically reconfigurable systems have the potential of realising efficient systems as well as providing adaptability to changing system requirements. Such systems are suitable for future mobile multimedia systems that have limited battery resources, must handle diverse data types, and must operate
Gao, Zilin; Wang, Yinhe; Zhang, Lili
2018-02-01
In the existing research results of the complex dynamical networks controlled, the controllers are mainly used to guarantee the synchronization or stabilization of the nodes’ state, and the terms coupled with connection relationships may affect the behaviors of nodes, this obviously ignores the dynamic common behavior of the connection relationships between the nodes. In fact, from the point of view of large-scale system, a complex dynamical network can be regarded to be composed of two time-varying dynamic subsystems, which can be called the nodes subsystem and the connection relationships subsystem, respectively. Similar to the synchronization or stabilization of the nodes subsystem, some characteristic phenomena can be also emerged in the connection relationships subsystem. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. This paper focuses on the structural balance in dynamic complex networks. Generally speaking, the state of the connection relationships subsystem is difficult to be measured accurately in practical applications, and thus it is not easy to implant the controller directly into the connection relationships subsystem. It is noted that the nodes subsystem and the relationships subsystem are mutually coupled, which implies that the state of the connection relationships subsystem can be affected by the controllable state of nodes subsystem. Inspired by this observation, by using the structural balance theory of triad, the controller with the parameter adaptive law is proposed for the nodes subsystem in this paper, which may ensure the connection relationship matrix to approximate a given structural balance matrix in the sense of the uniformly ultimately bounded (UUB). That is, the structural balance may be obtained by employing the controlling state of the nodes subsystem. Finally, the simulations are used to show the validity of the method in this paper.
Confluence and convergence: team effectiveness in complex systems.
Porter-OʼGrady, Tim
2015-01-01
Complex adaptive systems require nursing leadership to rethink organizational work and the viability and effectiveness of teams. Much of emergent thinking about complexity and systems and organizations alter the understanding of the nature and function of teamwork and the configuration and leadership of team effort. Reflecting on basic concepts of complexity and their application to team formation, dynamics, and outcomes lays an important foundation for effectively guiding the strategic activity of systems through the focused tactical action of teams. Basic principles of complexity, their impact on teams, and the fundamental elements of team effectiveness are explored.
Smart modeling and simulation for complex systems practice and theory
Ren, Fenghui; Zhang, Minjie; Ito, Takayuki; Tang, Xijin
2015-01-01
This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.
Complexity, Sustainability, Justice, and Meaning: Chronological Versus Dynamical Time
Directory of Open Access Journals (Sweden)
Horacio Velasco
2009-11-01
Full Text Available
Abstract: It is shown that time may be appreciated in at least two senses: chronological and dynamical. Chronological time is the time of our naïve acquaintance as transient beings. At its most extensive scale, it corresponds to history encompassing both the abiotic and the biotic universe. Dynamical time, deriving from classical mechanics, is the time embraced by most of the laws of physics. It concerns itself only with present conditions since it is held that that the past may be reconstructed from the present (literally and the future predicted from the present, a position known as Laplacian determinism.
Nonlinear dynamics has shown the fallacy of this supposition because, of necessity, the concrete values that may be assumed in the variables of the equations of motion constituting the laws of physics (i.e. the present or starting conditions as a result of the spontaneous or intentional interaction of subject (or measuring systems and of object (or measured systems, cannot be of infinite precision. Indeed, even if they could be, it is not at all clear that they would permit Laplacian determinism because of what is thought to be the ubiquity of K-flow dynamics in nature in which even infinite past information leading to the present cannot yield prediction of the future. In consequence, nonlinear dynamics, in rebellion against dynamical time, generates a primitive form of history distinguishing past, present, and future that may be termed nonlinear dynamical hysteresis.
Reliability Standards of Complex Engineering Systems
Galperin, E. M.; Zayko, V. A.; Gorshkalev, P. A.
2017-11-01
Production and manufacture play an important role in today’s modern society. Industrial production is nowadays characterized by increased and complex communications between its parts. The problem of preventing accidents in a large industrial enterprise becomes especially relevant. In these circumstances, the reliability of enterprise functioning is of particular importance. Potential damage caused by an accident at such enterprise may lead to substantial material losses and, in some cases, can even cause a loss of human lives. That is why industrial enterprise functioning reliability is immensely important. In terms of their reliability, industrial facilities (objects) are divided into simple and complex. Simple objects are characterized by only two conditions: operable and non-operable. A complex object exists in more than two conditions. The main characteristic here is the stability of its operation. This paper develops the reliability indicator combining the set theory methodology and a state space method. Both are widely used to analyze dynamically developing probability processes. The research also introduces a set of reliability indicators for complex technical systems.
Ng, Tony T.
The mammalian cortex is a highly structured network of densely packed neurons that interact strongly with each other in very specific ways. Loosely speaking, neurons are cells that fire clicks at each other as a means of communication. Common sites of communication, known as synapses, are enabled by transmitter molecules released from presynaptic sender cells, which bind to receptors on postsynaptic receiver cells. There are two major classes of neurons - excitatory ones that prompt their downstream neighbors to fire spikes through depolarization, and inhibitory ones that suppress spike activity of their postsynaptic partners via hyperpolarization. Depolarization and hyperpolarization make membrane potential of a cell more positive and more negative, respectively. A sufficiently depolarized neuron fires a spike, which technically is called an action potential. In this thesis, we focus on the interplay between three of the cortex's most ubiquitous features and examine some of the consequences that their interactions have on cortical dynamics. One of the features, widespread projections between clusters of excitatory neurons, is topological. The two remaining features, homeostasis and balance between the amount of excitatory and inhibitory activity are dynamical. Here, homeostasis refers to the regulatory mechanism of individual cells or collections of cells that maintains constant levels of spike activity over time. Simply by varying the average homeostatic firing rate in clusters of excitatory neurons or by tuning the common homoeostatic rate of individual inhibitory neurons, we show via simulation that cluster-based activity bursts can exhibit critical dynamics and display power-law distributions with exponents that are consistent with those found in in vivo experiments of awake animals. Criticality is an idea that originated in statistical physics. At the critical point, activity levels of sites across an entire system, such as those of different cortical regions
Infinite Particle Systems: Complex Systems III
Directory of Open Access Journals (Sweden)
Editorial Board
2008-06-01
Full Text Available In the years 2002-2005, a group of German and Polish mathematicians worked under a DFG research project No 436 POL 113/98/0-1 entitled "Methods of stochastic analysis in the theory of collective phenomena: Gibbs states and statistical hydrodynamics". The results of their study were summarized at the German-Polish conference, which took place in Poland in October 2005. The venue of the conference was Kazimierz Dolny upon Vistula - a lovely town and a popular place for various cultural, scientific, and even political events of an international significance. The conference was also attended by scientists from France, Italy, Portugal, UK, Ukraine, and USA, which predetermined its international character. Since that time, the conference, entitled "Infinite Particle Systems: Complex Systems" has become an annual international event, attended by leading scientists from Germany, Poland and many other countries. The present volume of the "Condensed Matter Physics" contains proceedings of the conference "Infinite Particle Systems: Complex Systems III", which took place in June 2007.
Multilevel Complex Networks and Systems
Caldarelli, Guido
2014-03-01
Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.
Control of multidimensional systems on complex network
Bagnoli, Franco; Battistelli, Giorgio; Chisci, Luigi; Fanelli, Duccio
2017-01-01
Multidimensional systems coupled via complex networks are widespread in nature and thus frequently invoked for a large plethora of interesting applications. From ecology to physics, individual entities in mutual interactions are grouped in families, homogeneous in kind. These latter interact selectively, through a sequence of self-consistently regulated steps, whose deeply rooted architecture is stored in the assigned matrix of connections. The asymptotic equilibrium eventually attained by the system, and its associated stability, can be assessed by employing standard nonlinear dynamics tools. For many practical applications, it is however important to externally drive the system towards a desired equilibrium, which is resilient, hence stable, to external perturbations. To this end we here consider a system made up of N interacting populations which evolve according to general rate equations, bearing attributes of universality. One species is added to the pool of interacting families and used as a dynamical controller to induce novel stable equilibria. Use can be made of the root locus method to shape the needed control, in terms of intrinsic reactivity and adopted protocol of injection. The proposed method is tested on both synthetic and real data, thus enabling to demonstrate its robustness and versatility. PMID:28892493
Ergodic theory and dynamical systems
Coudène, Yves
2016-01-01
This textbook is a self-contained and easy-to-read introduction to ergodic theory and the theory of dynamical systems, with a particular emphasis on chaotic dynamics. This book contains a broad selection of topics and explores the fundamental ideas of the subject. Starting with basic notions such as ergodicity, mixing, and isomorphisms of dynamical systems, the book then focuses on several chaotic transformations with hyperbolic dynamics, before moving on to topics such as entropy, information theory, ergodic decomposition and measurable partitions. Detailed explanations are accompanied by numerous examples, including interval maps, Bernoulli shifts, toral endomorphisms, geodesic flow on negatively curved manifolds, Morse-Smale systems, rational maps on the Riemann sphere and strange attractors. Ergodic Theory and Dynamical Systems will appeal to graduate students as well as researchers looking for an introduction to the subject. While gentle on the beginning student, the book also contains a number of commen...
The Leadership Game : Experiencing Dynamic Complexity under Deep Uncertainty
Pruyt, E.; Segers, J.; Oruc, S.
2011-01-01
In this ever more complex, interconnected, and uncertain world, leadership is needed more than ever. But the literature and most leaders largely ignore dynamic complexity and deep uncertainty: only futures characterized by ever faster change, ever more (required) flexibility, and ever more scarcity
Spatial price dynamics: From complex network perspective
Li, Y. L.; Bi, J. T.; Sun, H. J.
2008-10-01
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.
The brain as a dynamic physical system.
McKenna, T M; McMullen, T A; Shlesinger, M F
1994-06-01
The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.
Noise-induced temporal dynamics in Turing systems
Schumacher, Linus J.; Woolley, Thomas E.; Baker, Ruth E.
2013-01-01
We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using
Stochastic runaway of dynamical systems
International Nuclear Information System (INIS)
Pfirsch, D.; Graeff, P.
1984-10-01
One-dimensional, stochastic, dynamical systems are well studied with respect to their stability properties. Less is known for the higher dimensional case. This paper derives sufficient and necessary criteria for the asymptotic divergence of the entropy (runaway) and sufficient ones for the moments of n-dimensional, stochastic, dynamical systems. The crucial implication is the incompressibility of their flow defined by the equations of motion in configuration space. Two possible extensions to compressible flow systems are outlined. (orig.)
Dynamical systems in classical mechanics
Kozlov, V V
1995-01-01
This book shows that the phenomenon of integrability is related not only to Hamiltonian systems, but also to a wider variety of systems having invariant measures that often arise in nonholonomic mechanics. Each paper presents unique ideas and original approaches to various mathematical problems related to integrability, stability, and chaos in classical dynamics. Topics include… the inverse Lyapunov theorem on stability of equilibria geometrical aspects of Hamiltonian mechanics from a hydrodynamic perspective current unsolved problems in the dynamical systems approach to classical mechanics
DEFF Research Database (Denmark)
Rodrigues, Vinicius Picanco; Morioka, S.; Pigosso, Daniela Cristina Antelmi
2016-01-01
In order to deal with the complex and dynamic nature of sustainability integration into the product development process, this research explore the use of a qualitative System Dynamics approach by using the causal loop diagram (CLD) tool. A literature analysis was followed by a case study, aiming ...
Increase of Organization in Complex Systems
Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder
2013-01-01
Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...
Coherence and chaos in extended dynamical systems
International Nuclear Information System (INIS)
Bishop, A.R.
1994-01-01
Coherence, chaos, and pattern formation are characteristic elements of the nonequilibrium statistical mechanics controlling mesoscopic order and disorder in many-degree-of-freedom nonlinear dynamical systems. Competing length scales and/or time scales are the underlying microscopic driving forces for many of these aspects of ''complexity.'' We illustrate the basic concepts with some model examples of classical and quantum, ordered and disordered, nonlinear systems
DEFF Research Database (Denmark)
Thomsen, Per Grove
1996-01-01
A one-dimensional model with axial discretization of engine components has been formulated using tha balance equations for mass energy and momentum and the ideal gas equation of state. ODE's that govern the dynamic behaviour of the regenerator matrix temperatures are included in the model. Known...
Computational complexity of symbolic dynamics at the onset of chaos
Lakdawala, Porus
1996-05-01
In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.
Advances in dynamics, patterns, cognition challenges in complexity
Pikovsky, Arkady; Rulkov, Nikolai; Tsimring, Lev
2017-01-01
This book focuses on recent progress in complexity research based on the fundamental nonlinear dynamical and statistical theory of oscillations, waves, chaos, and structures far from equilibrium. Celebrating seminal contributions to the field by Prof. M. I. Rabinovich of the University of California at San Diego, this volume brings together perspectives on both the fundamental aspects of complexity studies, as well as in applications in different fields ranging from granular patterns to understanding of the cognitive brain and mind dynamics. The slate of world-class authors review recent achievements that together present a broad and coherent coverage of modern research in complexity greater than the sum of its parts. Presents the most up-to-date developments in the studies of complexity Combines basic and applied aspects Links background nonlinear theory of oscillations and waves with modern approaches Allows readers to recognize general dynamical principles across the applications fields.
Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent
2011-06-01
Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized
"COUPLED PROCESSES" AS DYNAMIC CAPABILITIES IN SYSTEMS INTEGRATION
Chagas Jr, Milton de Freitas; Leite, Dinah Eluze Sales; Jesus, Gabriel Torres de
2017-01-01
ABSTRACT The dynamics of innovation in complex systems industries is becoming an independent research stream. Apart from conventional uncertainties related to commerce and technology, complex-system industries must cope with systemic uncertainty. This paper's objective is to analyze evolving technological paths from one product generation to the next through two case studies in the Brazilian aerospace industry, considering systems integration as an empirical instantiation of dynamic capabilit...
Challenges in the analysis of complex systems: introduction and overview
Hastings, Harold M.; Davidsen, Jörn; Leung, Henry
2017-12-01
One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.
XXIII International Conference on Nonlinear Dynamics of Electronic Systems
Stoop, Ruedi; Stramaglia, Sebastiano
2017-01-01
This book collects contributions to the XXIII international conference “Nonlinear dynamics of electronic systems”. Topics range from non-linearity in electronic circuits to synchronisation effects in complex networks to biological systems, neural dynamics and the complex organisation of the brain. Resting on a solid mathematical basis, these investigations address highly interdisciplinary problems in physics, engineering, biology and biochemistry.
Persistent topological features of dynamical systems
Energy Technology Data Exchange (ETDEWEB)
Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia); Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Rajković, Milan, E-mail: milanr@vinca.rs [Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia)
2016-05-15
Inspired by an early work of Muldoon et al., Physica D 65, 1–16 (1993), we present a general method for constructing simplicial complex from observed time series of dynamical systems based on the delay coordinate reconstruction procedure. The obtained simplicial complex preserves all pertinent topological features of the reconstructed phase space, and it may be analyzed from topological, combinatorial, and algebraic aspects. In focus of this study is the computation of homology of the invariant set of some well known dynamical systems that display chaotic behavior. Persistent homology of simplicial complex and its relationship with the embedding dimensions are examined by studying the lifetime of topological features and topological noise. The consistency of topological properties for different dynamic regimes and embedding dimensions is examined. The obtained results shed new light on the topological properties of the reconstructed phase space and open up new possibilities for application of advanced topological methods. The method presented here may be used as a generic method for constructing simplicial complex from a scalar time series that has a number of advantages compared to the mapping of the same time series to a complex network.
Cardea: Dynamic Access Control in Distributed Systems
Lepro, Rebekah
2004-01-01
Modern authorization systems span domains of administration, rely on many different authentication sources, and manage complex attributes as part of the authorization process. This . paper presents Cardea, a distributed system that facilitates dynamic access control, as a valuable piece of an inter-operable authorization framework. First, the authorization model employed in Cardea and its functionality goals are examined. Next, critical features of the system architecture and its handling of the authorization process are then examined. Then the S A M L and XACML standards, as incorporated into the system, are analyzed. Finally, the future directions of this project are outlined and connection points with general components of an authorization system are highlighted.
A dissipative particle dynamics method for arbitrarily complex geometries
Li, Zhen; Bian, Xin; Tang, Yu-Hang; Karniadakis, George Em
2018-02-01
Dissipative particle dynamics (DPD) is an effective Lagrangian method for modeling complex fluids in the mesoscale regime but so far it has been limited to relatively simple geometries. Here, we formulate a local detection method for DPD involving arbitrarily shaped geometric three-dimensional domains. By introducing an indicator variable of boundary volume fraction (BVF) for each fluid particle, the boundary of arbitrary-shape objects is detected on-the-fly for the moving fluid particles using only the local particle configuration. Therefore, this approach eliminates the need of an analytical description of the boundary and geometry of objects in DPD simulations and makes it possible to load the geometry of a system directly from experimental images or computer-aided designs/drawings. More specifically, the BVF of a fluid particle is defined by the weighted summation over its neighboring particles within a cutoff distance. Wall penetration is inferred from the value of the BVF and prevented by a predictor-corrector algorithm. The no-slip boundary condition is achieved by employing effective dissipative coefficients for liquid-solid interactions. Quantitative evaluations of the new method are performed for the plane Poiseuille flow, the plane Couette flow and the Wannier flow in a cylindrical domain and compared with their corresponding analytical solutions and (high-order) spectral element solution of the Navier-Stokes equations. We verify that the proposed method yields correct no-slip boundary conditions for velocity and generates negligible fluctuations of density and temperature in the vicinity of the wall surface. Moreover, we construct a very complex 3D geometry - the "Brown Pacman" microfluidic device - to explicitly demonstrate how to construct a DPD system with complex geometry directly from loading a graphical image. Subsequently, we simulate the flow of a surfactant solution through this complex microfluidic device using the new method. Its
Lectures on chaotic dynamical systems
Afraimovich, Valentin
2002-01-01
This book is devoted to chaotic nonlinear dynamics. It presents a consistent, up-to-date introduction to the field of strange attractors, hyperbolic repellers, and nonlocal bifurcations. The authors keep the highest possible level of "physical" intuition while staying mathematically rigorous. In addition, they explain a variety of important nonstandard algorithms and problems involving the computation of chaotic dynamics. The book will help readers who are not familiar with nonlinear dynamics to understand and appreciate sophisticated modern dynamical systems and chaos. Intended for courses in either mathematics, physics, or engineering, prerequisites are calculus, differential equations, and functional analysis.
Modelling the complex dynamics of vegetation, livestock and rainfall ...
African Journals Online (AJOL)
Open Access DOWNLOAD FULL TEXT ... In this paper, we present mathematical models that incorporate ideas from complex systems theory to integrate several strands of rangeland theory in a hierarchical framework. ... Keywords: catastrophe theory; complexity theory; disequilibrium; hysteresis; moving attractors
Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach
Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh
2012-01-01
Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…
Dynamical systems on networks a tutorial
Porter, Mason A
2016-01-01
This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Appli...
Dynamics robustness of cascading systems.
Directory of Open Access Journals (Sweden)
Jonathan T Young
2017-03-01
Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it
SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS
Directory of Open Access Journals (Sweden)
Petrus M.A. Sloot
2014-09-01
Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.
Directory of Open Access Journals (Sweden)
Thomas Bochynek
Full Text Available The evolution of nest weaving, the inclusion of larval silk in the nest walls, is considered one of the pinnacles of cooperative behaviour in social insects. Within the four ant genera in which this has evolved, Oecophylla are unique in being the only group that precedes the deposition of larval silk by actively manipulating the leaf substrate to form a nest chamber. Here we provide the first descriptions of the manipulation process within a complex-systems framework. Substrate manipulation involves individual ants selecting, grasping and attempting to pull the edge of the substrate. These individuals are then joined by nest mates at the work site, who either select a site beside the first individual or grasp the body of the first or preceding worker to form a chain of pulling ants that together drag and bend the substrate. Site selection by individual workers is not random when confronted with an artificial leaf, with individuals more likely to grasp a substrate at its tip rather than along a more broad edge. The activity of additional individuals is also not random, with their activity being grouped in both space and time. Additional individuals are more likely to join an existing biting individual or pulling group. The positive feedback associated with the early stages of pulling behaviour appears typical for many of the collective actions observed in social insects.
Dynamic Ocean Track System Plus -
Department of Transportation — Dynamic Ocean Track System Plus (DOTS Plus) is a planning tool implemented at the ZOA, ZAN, and ZNY ARTCCs. It is utilized by Traffic Management Unit (TMU) personnel...
Dynamical systems and linear algebra
Colonius, Fritz (Prof.)
2007-01-01
Dynamical systems and linear algebra / F. Colonius, W. Kliemann. - In: Handbook of linear algebra / ed. by Leslie Hogben. - Boca Raton : Chapman & Hall/CRC, 2007. - S. 56,1-56,22. - (Discrete mathematics and its applications)
Metasynthetic computing and engineering of complex systems
Cao, Longbing
2015-01-01
Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy thro
Directory of Open Access Journals (Sweden)
Z. Ertinger
1995-09-01
Full Text Available Our aim is to present some aspects of the mathematical theory of strange behaviour of nonlinear systems, especially of systems with symmetry. Proofs are emitted, the interested reader is advised to references. Our presentation is inevitably selective. We focus on parts of the theory with possible applications to electronic circuits and systems which may display chaotic behaviour.
Modelling the crop: from system dynamics to systems biology
Yin, X.; Struik, P.C.
2010-01-01
There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models
Dynamical systems in population biology
Zhao, Xiao-Qiang
2017-01-01
This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology. Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied...
Sulis, William H
2017-10-01
Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.
Intensity approximation of random fluctuation in complex systems
Yulmetyev, R. M.; Gafarov, F. M.; Yulmetyeva, D. G.; Emeljanova, N. A.
2002-01-01
The Markov and non-Markov processes in complex systems are examined with the help of dynamical information Shannon entropy method. Here we consider the essential role of two mutually independent channels of entropy involving creation of correlation and annihilation of correlation. The developed method has been used to analyze the intensity fluctuation of the complex systems of various nature: in psychology (to analyze numerical and pattern short-time human memory, to study the effect of stress on the parameters of the dynamical taping-test) and in cardiology (to analyze the random dynamics of RR-intervals in human ECG's and to diagnose various diseases of human cardiovascular systems). The received results show that the application of intensity approximation allows to improve essentially the diagnostics of parameters in the evolution of human dynamic states.
Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems
Energy Technology Data Exchange (ETDEWEB)
Jinqing, Fang [Academia Sinica, Beijing, BJ (China). Inst. of Atomic Energy
1995-03-01
Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.).
Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems
International Nuclear Information System (INIS)
Fang Jinqing
1995-03-01
Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.)
Environmental coupling and population dynamics in the PE545 light-harvesting complex
Energy Technology Data Exchange (ETDEWEB)
Aghtar, Mortaza; Kleinekathöfer, Ulrich, E-mail: u.kleinekathoefer@jacobs-university.de
2016-01-15
Long-lived quantum coherences have been shown experimentally in the Fenna–Matthews–Olson (FMO) complex of green sulfur bacteria as well as in the phycoerythrin 545 (PE545) photosynthetic antenna system of marine algae. A combination of classical molecular dynamics simulations, quantum chemistry and quantum dynamical calculations is employed to determine the excitation transfer dynamics in PE545. One key property of the light-harvesting system concerning the excitation transfer and dephasing phenomena is the spectral density. This quantity is determined from time series of the vertical excitation energies of the aggregate. In the present study we focus on the quantum dynamical simulations using the earlier QM/MM calculations as input. Employing an ensemble-averaged classical path-based wave packet dynamics, the excitation transfer dynamics between the different bilins in the PE545 complex is determined and analyzed. Furthermore, the nature of the environmental fluctuations determining the transfer dynamics is discussed. - Highlights: • Modeling of excitation energy transfer in the light-harvesting system PE545. • Combination of molecular dynamics simulations, quantum chemistry and quantum dynamics. • Spectral densities for bilins in the PE545 complex.
Systems Approach to Tourism: A Methodology for Defining Complex Tourism System
Directory of Open Access Journals (Sweden)
Jere Jakulin Tadeja
2017-08-01
Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.
Complex dynamics of semantic memory access in reading.
Baggio, Giosué; Fonseca, André
2012-02-07
Understanding a word in context relies on a cascade of perceptual and conceptual processes, starting with modality-specific input decoding, and leading to the unification of the word's meaning into a discourse model. One critical cognitive event, turning a sensory stimulus into a meaningful linguistic sign, is the access of a semantic representation from memory. Little is known about the changes that activating a word's meaning brings about in cortical dynamics. We recorded the electroencephalogram (EEG) while participants read sentences that could contain a contextually unexpected word, such as 'cold' in 'In July it is very cold outside'. We reconstructed trajectories in phase space from single-trial EEG time series, and we applied three nonlinear measures of predictability and complexity to each side of the semantic access boundary, estimated as the onset time of the N400 effect evoked by critical words. Relative to controls, unexpected words were associated with larger prediction errors preceding the onset of the N400. Accessing the meaning of such words produced a phase transition to lower entropy states, in which cortical processing becomes more predictable and more regular. Our study sheds new light on the dynamics of information flow through interfaces between sensory and memory systems during language processing.
Introduction to Focus Issue: Complex network perspectives on flow systems.
Donner, Reik V; Hernández-García, Emilio; Ser-Giacomi, Enrico
2017-03-01
During the last few years, complex network approaches have demonstrated their great potentials as versatile tools for exploring the structural as well as dynamical properties of dynamical systems from a variety of different fields. Among others, recent successful examples include (i) functional (correlation) network approaches to infer hidden statistical interrelationships between macroscopic regions of the human brain or the Earth's climate system, (ii) Lagrangian flow networks allowing to trace dynamically relevant fluid-flow structures in atmosphere, ocean or, more general, the phase space of complex systems, and (iii) time series networks unveiling fundamental organization principles of dynamical systems. In this spirit, complex network approaches have proven useful for data-driven learning of dynamical processes (like those acting within and between sub-components of the Earth's climate system) that are hidden to other analysis techniques. This Focus Issue presents a collection of contributions addressing the description of flows and associated transport processes from the network point of view and its relationship to other approaches which deal with fluid transport and mixing and/or use complex network techniques.
Harel, Elad; Engel, Gregory S
2012-01-17
Light-harvesting antenna complexes transfer energy from sunlight to photosynthetic reaction centers where charge separation drives cellular metabolism. The process through which pigments transfer excitation energy involves a complex choreography of coherent and incoherent processes mediated by the surrounding protein and solvent environment. The recent discovery of coherent dynamics in photosynthetic light-harvesting antennae has motivated many theoretical models exploring effects of interference in energy transfer phenomena. In this work, we provide experimental evidence of long-lived quantum coherence between the spectrally separated B800 and B850 rings of the light-harvesting complex 2 (LH2) of purple bacteria. Spectrally resolved maps of the detuning, dephasing, and the amplitude of electronic coupling between excitons reveal that different relaxation pathways act in concert for optimal transfer efficiency. Furthermore, maps of the phase of the signal suggest that quantum mechanical interference between different energy transfer pathways may be important even at ambient temperature. Such interference at a product state has already been shown to enhance the quantum efficiency of transfer in theoretical models of closed loop systems such as LH2.
Reduction of Subjective and Objective System Complexity
Watson, Michael D.
2015-01-01
Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached
Nonlinear dynamic macromodeling techniques for audio systems
Ogrodzki, Jan; Bieńkowski, Piotr
2015-09-01
This paper develops a modelling method and a models identification technique for the nonlinear dynamic audio systems. Identification is performed by means of a behavioral approach based on a polynomial approximation. This approach makes use of Discrete Fourier Transform and Harmonic Balance Method. A model of an audio system is first created and identified and then it is simulated in real time using an algorithm of low computational complexity. The algorithm consists in real time emulation of the system response rather than in simulation of the system itself. The proposed software is written in Python language using object oriented programming techniques. The code is optimized for a multithreads environment.
Dynamics of Financial System: A System Dynamics Approach
Girish K. Nair; Lewlyn Lester Raj Rodrigues
2013-01-01
There are several ratios which define the financial health of an organization but the importance of Net cash flow, Gross income, Net income, Pending bills, Receivable bills, Debt, and Book value can never be undermined as they give the exact picture of the financial condition. While there are several approaches to study the dynamics of these variables, system dynamics based modelling and simulation is one of the modern techniques. The paper explores this method to simulate the before mentione...
Directory of Open Access Journals (Sweden)
Xianjun Shen
Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.
Complex dynamics in Duffing-Van der Pol equation
International Nuclear Information System (INIS)
Jing Zhujun; Yang, Zhiyan; Jiang Tao
2006-01-01
Duffing-Van der Pol equation with fifth nonlinear-restoring force and two external forcing terms is investigated. The threshold values of existence of chaotic motion are obtained under the periodic perturbation. By second-order averaging method and Melnikov method, we prove the criterion of existence of chaos in averaged system under quasi-periodic perturbation for ω 2 nω 1 + εσ, n = 1, 3, 5, and cannot prove the criterion of existence of chaos in second-order averaged system under quasi-periodic perturbation for ω 2 = nω 1 + εσ, n = 2, 4, 6, 7, 8, 9, 10, where σ is not rational to ω 1 , but can show the occurrence of chaos in original system by numerical simulation. Numerical simulations including heteroclinic and homoclinic bifurcation surfaces, bifurcation diagrams, Lyapunov exponent, phase portraits and Poincare map, not only show the consistence with the theoretical analysis but also exhibit the more new complex dynamical behaviors. We show that cascades of interlocking period-doubling and reverse period-doubling bifurcations from period-2 to -4 and -6 orbits, interleaving occurrence of chaotic behaviors and quasi-periodic orbits, transient chaos with a great abundance of period windows, symmetry-breaking of periodic orbits in chaotic regions, onset of chaos which occurs more than one, chaos suddenly disappearing to period orbits, interior crisis, strange non-chaotic attractor, non-attracting chaotic set and nice chaotic attractors. Our results show many dynamical behaviors and some of them are strictly departure from the behaviors of Duffing-Van der Pol equation with a cubic nonlinear-restoring force and one external forcing
Opinion Dynamics on Complex Networks with Communities
International Nuclear Information System (INIS)
Ru, Wang; Li-Ping, Chi
2008-01-01
The Ising or Potts models of ferromagnetism have been widely used to describe locally interacting social or economic systems. We consider a related model, introduced by Sznajd to describe the evolution of consensus in the scale-free networks with the tunable strength (noted by Q) of community structure. In the Sznajd model, the opinion or state of any spins can only be changed by the influence of neighbouring pairs of similar connection spins. Such pairs can polarize their neighbours. Using asynchronous updating, it is found that the smaller the community strength Q, the larger the slope of the exponential relaxation time distribution. Then the effect of the initial up- spin concentration p as a function of the final all up probability E is investigated by taking different initialization strategies, the random node-chosen initialization strategy has no difference under different community strengths, while the strategies of community node-chosen initialization and hub node-chosen initialization are different in final probability under different Q, and the latter one is more effective in reaching final state
Energy Technology Data Exchange (ETDEWEB)
Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Maths, Yunyang Teacher' s College, Hubei 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Fang Jian' an [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Lu Hongqian [Shandong Institute of Light Industry, Shandong Jinan 250353 (China)
2009-12-28
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
International Nuclear Information System (INIS)
Xu Yuhua; Zhou Wuneng; Fang Jian'an; Lu Hongqian
2009-01-01
This Letter proposes an approach to identify the topological structure and unknown parameters for uncertain general complex networks simultaneously. By designing effective adaptive controllers, we achieve synchronization between two complex networks. The unknown network topological structure and system parameters of uncertain general complex dynamical networks are identified simultaneously in the process of synchronization. Several useful criteria for synchronization are given. Finally, an illustrative example is presented to demonstrate the application of the theoretical results.
Self-supervised dynamical systems
International Nuclear Information System (INIS)
Zak, Michail
2004-01-01
A new type of dynamical systems which capture the interactions via information flows typical for active multi-agent systems is introduced. The mathematical formalism is based upon coupling the classical dynamical system (with random components caused by uncertainties in initial conditions as well as by Langevin forces) with the corresponding Liouville or the Fokker-Planck equations describing evolution of these uncertainties in terms of probability density. The coupling is implemented by information-based supervising forces which fundamentally change the patterns of probability evolution. It is demonstrated that the probability density can approach prescribed attractors while exhibiting such patterns as shock waves, solitons and chaos in probability space. Applications of these phenomena to information-based neural nets, expectation-based cooperation, self-programmed systems, control chaos using terminal attractors as well as to games with incomplete information, are addressed. A formal similarity between the mathematical structure of the introduced dynamical systems and quantum mechanics is discussed
Complex-Dynamic Cosmology and Emergent World Structure
Kirilyuk, Andrei P.
2004-01-01
Universe structure emerges in the unreduced, complex-dynamic interaction process with the simplest initial configuration (two attracting homogeneous fields, quant-ph/9902015). The unreduced interaction analysis gives intrinsically creative cosmology, describing the real, explicitly emerging world structure with dynamic randomness on each scale. Without imposing any postulates or entities, we obtain physically real space, time, elementary particles with their detailed structure and intrinsic p...
Symmetric and Asymmetric Tendencies in Stable Complex Systems.
Tan, James P L
2016-08-22
A commonly used approach to study stability in a complex system is by analyzing the Jacobian matrix at an equilibrium point of a dynamical system. The equilibrium point is stable if all eigenvalues have negative real parts. Here, by obtaining eigenvalue bounds of the Jacobian, we show that stable complex systems will favor mutualistic and competitive relationships that are asymmetrical (non-reciprocative) and trophic relationships that are symmetrical (reciprocative). Additionally, we define a measure called the interdependence diversity that quantifies how distributed the dependencies are between the dynamical variables in the system. We find that increasing interdependence diversity has a destabilizing effect on the equilibrium point, and the effect is greater for trophic relationships than for mutualistic and competitive relationships. These predictions are consistent with empirical observations in ecology. More importantly, our findings suggest stabilization algorithms that can apply very generally to a variety of complex systems.
Empirical and theoretical analysis of complex systems
Zhao, Guannan
This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group
Directory of Open Access Journals (Sweden)
Joshua Rodewald
2016-10-01
Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.
Nonlinear dynamics in biological systems
Carballido-Landeira, Jorge
2016-01-01
This book presents recent research results relating to applications of nonlinear dynamics, focusing specifically on four topics of wide interest: heart dynamics, DNA/RNA, cell mobility, and proteins. The book derives from the First BCAM Workshop on Nonlinear Dynamics in Biological Systems, held in June 2014 at the Basque Center of Applied Mathematics (BCAM). At this international meeting, researchers from different but complementary backgrounds, including molecular dynamics, physical chemistry, bio-informatics and biophysics, presented their most recent results and discussed the future direction of their studies using theoretical, mathematical modeling and experimental approaches. Such was the level of interest stimulated that the decision was taken to produce this publication, with the organizers of the event acting as editors. All of the contributing authors are researchers working on diverse biological problems that can be approached using nonlinear dynamics. The book will appeal especially to applied math...
Dynamic Stability of Maglev Systems,
1992-04-01
AD-A259 178 ANL-92/21 Materials and Components Dynamic Stability of Technology Division Materials and Components Maglev Systems Technology Division...of Maglev Systems Y. Cai, S. S. Chen, and T. M. Mulcahy Materials and Components Technology Division D. M. Rote Center for Transportation Research...of Maglev System with L-Shaped Guideway ......................................... 6 3 Stability of M aglev System s
European Conference on Complex Systems 2012
Kirkilionis, Markus; Nicolis, Gregoire
2013-01-01
The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered: 1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.
Self-Supervised Dynamical Systems
Zak, Michail
2003-01-01
Some progress has been made in a continuing effort to develop mathematical models of the behaviors of multi-agent systems known in biology, economics, and sociology (e.g., systems ranging from single or a few biomolecules to many interacting higher organisms). Living systems can be characterized by nonlinear evolution of probability distributions over different possible choices of the next steps in their motions. One of the main challenges in mathematical modeling of living systems is to distinguish between random walks of purely physical origin (for instance, Brownian motions) and those of biological origin. Following a line of reasoning from prior research, it has been assumed, in the present development, that a biological random walk can be represented by a nonlinear mathematical model that represents coupled mental and motor dynamics incorporating the psychological concept of reflection or self-image. The nonlinear dynamics impart the lifelike ability to behave in ways and to exhibit patterns that depart from thermodynamic equilibrium. Reflection or self-image has traditionally been recognized as a basic element of intelligence. The nonlinear mathematical models of the present development are denoted self-supervised dynamical systems. They include (1) equations of classical dynamics, including random components caused by uncertainties in initial conditions and by Langevin forces, coupled with (2) the corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces, denoted supervising forces, composed of probability densities and functionals thereof. The equations of classical mechanics represent motor dynamics that is, dynamics in the traditional sense, signifying Newton s equations of motion. The evolution of the probability densities represents mental dynamics or self-image. Then the interaction between the physical and
Complex biological and bio-inspired systems
Energy Technology Data Exchange (ETDEWEB)
Ecke, Robert E [Los Alamos National Laboratory
2009-01-01
The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to
Dynamically reconfigurable photovoltaic system
Okandan, Murat; Nielson, Gregory N.
2016-05-31
A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.
Dynamically reconfigurable photovoltaic system
Energy Technology Data Exchange (ETDEWEB)
Okandan, Murat; Nielson, Gregory N.
2016-12-27
A PV system composed of sub-arrays, each having a group of PV cells that are electrically connected to each other. A power management circuit for each sub-array has a communications interface and serves to connect or disconnect the sub-array to a programmable power grid. The power grid has bus rows and bus columns. A bus management circuit is positioned at a respective junction of a bus column and a bus row and is programmable through its communication interface to connect or disconnect a power path in the grid. As a result, selected sub-arrays are connected by selected power paths to be in parallel so as to produce a low system voltage, and, alternately in series so as to produce a high system voltage that is greater than the low voltage by at least a factor of ten.
Systemic Resilience of Complex Urban Systems
Directory of Open Access Journals (Sweden)
Serge Salat
2012-07-01
Full Text Available Two key paradigms emerge out of the variety of urban forms: certain cities resemble trees, others leaves. The structural difference between a tree and a leaf is huge: one is open, the other closed. Trees are entirely disconnected on a given scale: even if two twigs are spatially close, if they do not belong to the same branch, to go from one to the other implies moving down and then up all the hierarchy of branches. Leaves on the contrary are entirely connected on intermediary scales. The veins of a leaf are disconnected on the two larger scales but entirely connected on the two or three following intermediary scales before presenting tiny tree-like structures on the finest capillary scales. Deltas are leaves not trees. Neither galaxies nor whirlpools are trees. We will see in this paper that historical cities, like leaves, deltas, galaxies, lungs, brains and vein systems are all fractal structures, multiply connected and complex on all scales. These structures display the same degree of complexity and connectivity, regardless of the magnification scale on which we observe them. We say that these structures are scale free. Mathematical fractal forms are often generated recursively by applying again and again the same generator to an initiator. The iteration creates an arborescence. But scale free structure is not synonymous with a recursive tree-like structure. The fractal structure of the leaf is much more complex than that of the tree by its multiconnectivity on three or more intermediary levels. In contrast, trees in the virgin forest, even when they seem to be entangled, horizontal, and rhizomic, have branches that are not interconnected to form a lattice. As we will see, the history of urban planning has evolved from leaf-like to tree-like patterns, with a consequent loss of efficiency and resilience. Indeed, in a closed foliar path structure, the formation of cycles enables internal complexification and flow fluctuations due to the
Using system dynamics simulation for assessment of hydropower system safety
King, L. M.; Simonovic, S. P.; Hartford, D. N. D.
2017-08-01
Hydropower infrastructure systems are complex, high consequence structures which must be operated safely to avoid catastrophic impacts to human life, the environment, and the economy. Dam safety practitioners must have an in-depth understanding of how these systems function under various operating conditions in order to ensure the appropriate measures are taken to reduce system vulnerability. Simulation of system operating conditions allows modelers to investigate system performance from the beginning of an undesirable event to full system recovery. System dynamics simulation facilitates the modeling of dynamic interactions among complex arrangements of system components, providing outputs of system performance that can be used to quantify safety. This paper presents the framework for a modeling approach that can be used to simulate a range of potential operating conditions for a hydropower infrastructure system. Details of the generic hydropower infrastructure system simulation model are provided. A case study is used to evaluate system outcomes in response to a particular earthquake scenario, with two system safety performance measures shown. Results indicate that the simulation model is able to estimate potential measures of system safety which relate to flow conveyance and flow retention. A comparison of operational and upgrade strategies is shown to demonstrate the utility of the model for comparing various operational response strategies, capital upgrade alternatives, and maintenance regimes. Results show that seismic upgrades to the spillway gates provide the largest improvement in system performance for the system and scenario of interest.
Operationalizing sustainability in urban coastal systems: a system dynamics analysis.
Mavrommati, Georgia; Bithas, Kostas; Panayiotidis, Panayiotis
2013-12-15
We propose a system dynamics approach for Ecologically Sustainable Development (ESD) in urban coastal systems. A systematic analysis based on theoretical considerations, policy analysis and experts' knowledge is followed in order to define the concept of ESD. The principles underlying ESD feed the development of a System Dynamics Model (SDM) that connects the pollutant loads produced by urban systems' socioeconomic activities with the ecological condition of the coastal ecosystem that it is delineated in operational terms through key biological elements defined by the EU Water Framework Directive. The receiving waters of the Athens Metropolitan area, which bears the elements of typical high population density Mediterranean coastal city but which currently has also new dynamics induced by the ongoing financial crisis, are used as an experimental system for testing a system dynamics approach to apply the concept of ESD. Systems' thinking is employed to represent the complex relationships among the components of the system. Interconnections and dependencies that determine the potentials for achieving ESD are revealed. The proposed system dynamics analysis can facilitate decision makers to define paths of development that comply with the principles of ESD. Copyright © 2013 Elsevier Ltd. All rights reserved.
Howard, Ronald A
2007-01-01
This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory.Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University
Dynamical system approach to phyllotaxis
DEFF Research Database (Denmark)
D'ovidio, Francesco; Mosekilde, Erik
2000-01-01
and not a dynamical system, mainly because new active elements are added at each step, and thus the dimension of the "natural" phase space is not conserved. Here a construction is presented by which a well defined dynamical system can be obtained, and a bifurcation analysis can be carried out. Stable and unstable...... of the Jacobian, and thus the eigenvalues, is given. It is likely that problems of the above type often arise in biology, and especially in morphogenesis, where growing systems are modeled....
Experimental Modeling of Dynamic Systems
DEFF Research Database (Denmark)
Knudsen, Morten Haack
2006-01-01
An engineering course, Simulation and Experimental Modeling, has been developed that is based on a method for direct estimation of physical parameters in dynamic systems. Compared with classical system identification, the method appears to be easier to understand, apply, and combine with physical...