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Nonlinear Dynamics and Chaos: Advances and Perspectives Series: Understanding Complex Systems
M. Thiel, J. Kurths, M.C. Romano, G. Károlyi, A. Moura (Eds.) Nonlinear Dynamics and Chaos: Advances and Perspectives Series: Understanding Complex Systems This book is a collection of contributions on various aspects of active frontier research in the field of dynamical systems and chaos. Each chapter examines a specific research topic and, in addition to reviewing recent results, also discusses future perspectives. The result is an invaluable snapshot of the state of the field by some of its most important researchers. The first contribution in this book, "How did you get into Chaos?", is actually a collection of personal accounts by a number of distinguished scientists on how they entered the field of chaos and dynamical systems, featuring comments and recollections by James Yorke, Harry Swinney, Floris Takens, Peter Grassberger, Edward Ott, Lou Pecora, Itamar Procaccia, Michael Berry, Giulio Casati, Valentin Afraimovich, Robert MacKay, and last but not least, 2010, XV, 293 p. 16 illus. in color. Celso Grebogi, to whom this volume is dedicated. Printed book Hardcover ▶ 139,99 € | £119.99 | $169.99 ▶ *149,79 € (D) | 153,99 € (A) | CHF 165.50 eBook Available from your bookstore or ▶ springer.com/shop MyCopy Printed eBook for just ▶ € | $ 24.99 ▶ springer.com/mycopy Order online at springer.com ▶ or for the Americas call (toll free) 1-800-SPRINGER ▶ or email us at: [email protected]. ▶ For outside the Americas call +49 (0) 6221-345-4301 ▶ or email us at: [email protected]. The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. -
Arxiv:2103.17058V2 [Physics.Pop-Ph] 3 Apr 2021 the Fodder for This Paper
My cat Chester’s dynamical systems analysyyyyy7777777777777777y7is of the laser pointer and the red dot on the wall: correlation, causation, or SARS-Cov-2 hallucination? Eve Armstrong*†‡1,2 and Chester 1Department of Physics, New York Institute of Technology, New York, NY 10023, USA 2Department of Astrophysics, American Museum of Natural History, New York, NY 10024, USA (Dated: April 1, 2021) Abstract My cat Chester investigates the elusive relationship between the appearance in my hand of a silver laser pointer and that of a red dot on the wall, or on the floor, or on any other object that resides within the vicinity of the laser pointer. Chester first assesses preliminary establishments for causality, including mutual information, temporal precedence, and control for third variables. These assessments are all inconclusive for various reasons. In particular, mutual information fails to illuminate the problem due to a dearth of information regarding what the laser pointer might have been doing at times following Chester’s first awareness of the dot. Next Chester performs a formal reconstruction of phase space via time-delay embedding, to unfold the gggggggggggfffgfgtredvteometry ,mmmm.........,.„......,.mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm of the underlying dynamical system giving rise to the red dot’s trajectory. The resulting attractor does not resemble a laser pointer. The reconstruction could, however, be flawed, for example, due to the short temporal duration of the dot’s observed trajectory. Finally, the red dot could be a hallucination: a symptom brought on by COVID-19 - because, well, these days pretty much anything might be a symptom brought on by COVID-19. On this note, Chester’s kitten brother Mad Dog Lapynski offers an independent check on the red dot’s existence. -
Arxiv:2010.05310V2 [Cond-Mat.Stat-Mech] 12 Feb 2021 Shown to Be Very Close to 1/2 [29], the Well-Known Critical [25]
Chase-Escape Percolation on the 2D Square Lattice Aanjaneya Kumar∗ Department of Physics, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune 411008, India Peter Grassbergery JSC, Forschungszentrum J¨ulich, D-52425 J¨ulich,Germany Deepak Dharz Department of Physics, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune 411008, India (Dated: February 15, 2021) Chase-escape percolation is a variation of the standard epidemic spread models. In this model, each site can be in one of three states: unoccupied, occupied by a single prey, or occupied by a single predator. Prey particles spread to neighboring empty sites at rate p, and predator particles spread only to neighboring sites occupied by prey particles at rate 1, killing the prey particle that existed at that site. It was found that the prey can survive with non-zero probability, if p > pc with pc < 1. Using Monte Carlo simulations on the square lattice, we estimate the value of pc = 0:49451±0:00001, and the critical exponents are consistent with the undirected percolation universality class. We define a discrete-time parallel-update version of the model, which brings out the relation between chase- escape and undirected bond percolation. For all p < pc in D-dimensions, the number of predators in the absorbing configuration has a stretched-exponential distribution in contrast to the exponential distribution in the standard percolation theory. We also study the problem starting from the line initial condition with predator particles on all lattice points of the line y = 0 and prey particles on the line y = 1. -
What Is a Complex System?
What is a Complex System? James Ladyman, James Lambert Department of Philosophy, University of Bristol, U.K. Karoline Wiesner Department of Mathematics and Centre for Complexity Sciences, University of Bristol, U.K. (Dated: March 8, 2012) Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with complex systems in the literature and by those in the field. We argue that some of these features are neither necessary nor sufficient for complexity, and that some of them are too vague or confused to be of any analytical use. In order to bring mathematical rigour to the issue we then review some standard measures of complexity from the scientific literature, and offer a taxonomy for them, before arguing that the one that best captures the qualitative notion of the order produced by complex systems is that of the Statistical Complexity. Finally, we offer our own list of necessary conditions as a characterization of complexity. These conditions are qualitative and may not be jointly sufficient for complexity. We close with some suggestions for future work. I. INTRODUCTION The idea of complexity is sometimes said to be part of a new unifying framework for science, and a revolution in our understanding of systems the behaviour of which has proved difficult to predict and control thus far, such as the human brain and the world economy. -
Technological Alliance Networks Analysis Under Complex Network Perspective—— Case of China’S TD-SCDMA Industry
Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) Technological Alliance Networks Analysis under Complex Network Perspective—— Case of China’s TD-SCDMA Industry Liang Mei School of Public Administration Zhejiang University Hangzhou, 310027, China E-mail: [email protected] Abstract—This paper discusses the structure characteristics of China’s TD-SCDMA industry alliance from complex A. Complex Network Theory network perspective. We use the basic two parameters—— With the development of society and information average path length and clustering coefficient to do the revolution, the complex network behavior of artificial and analysis. Results show that comparing to the different types nature networking needs more and more comprehension. of complex network, China’s TD-SCDMA industry alliance Nowadays, researchers spend efforts to seek the general has relatively high clustering coefficient and low average characteristic of networks in different fields such as path length, implicating the obvious “small-world” telecommunication network, electric network, biology characteristic. network, and social network, and the complex network theory provides a suitable analysis perspective [6]. Table I Keywords-complex network; average path length; summarizes the brief history of the development of clustering coefficient; China’s TD-SCDMA industry alliance complex network theory. I. INTRODUCTION TABLE I. BRIEF HISTORY OF COMPLEX NETWORK THEORY In the globalization and network economy era, with the complexity of technology, high risk of innovation, a single company becomes difficult to have all the possible resources of the innovation activity. As no organization is Source: Wang Xiaofan, Li Xiang and Chen Guanrong. Complex Network and Its an island [1], networks of collaborative relationships Application. -
Stochastic to Deterministic Crossover of Fractal Dimension for a Langevin
Stochastic to Deterministic Crossover of Fractal Dimensions for a Langevin Equation David A. Egolf and Henry S. Greenside∗ Department of Physics and Center for Nonlinear and Complex Systems Duke University, Durham, NC 27706 [email protected]; [email protected] Using algorithms of Higuchi and of Grassberger and Procaccia, we study numer- ically how fractal dimensions cross over from finite-dimensional Brownian noise at short time scales to finite values of deterministic chaos at longer time scales for data generated from a Langevin equation that has a strange attractor in the limit of zero noise. Our results suggest that the crossover occurs at such short time scales that there is little chance of finite-dimensional Brownian noise being incorrectly identified arXiv:chao-dyn/9303004v1 12 Mar 1993 as deterministic chaos. 2.50.+s, 5.40.+j, 5.45.+b, 47.25.Mr Typeset Using REVTEX 1 A significant recent effort in nonlinear dynamics has been devoted to analyzing time series so as to determine whether they are chaotic or stochastic [1]. Chaotic time series arise from deterministic strange attractors whose underlying geometric structure in state space can be used to improve short term forecasting [1], to remove noise [1], or to stabilize unstable periodic orbits by small perturbations of parameters [2]. Stochastic time series such as Gaussian white noise or Brownian motion can not be obtained from any finite set of deterministic equations, and are less amenable to prediction and control. An early expectation was that fractal dimensions of time series would provide a tool for distinguishing chaotic from stochastic behavior. -
Morphological Transitions in Supercritical Generalized Percolation and Moving Interfaces in Media with Frozen Randomness
PHYSICAL REVIEW RESEARCH 2, 043150 (2020) Morphological transitions in supercritical generalized percolation and moving interfaces in media with frozen randomness Peter Grassberger JSC, FZ Jülich, D-52425 Jülich, Germany (Received 15 May 2020; revised 12 August 2020; accepted 17 September 2020; published 28 October 2020) We consider the growth of clusters in disordered media at zero temperature, as exemplified by supercritical generalized percolation and by the T = 0 random field Ising model. We show that the morphology of such clusters and of their surfaces can be of different types: They can be standard compact clusters with rough or smooth surfaces, but there exists also a completely different “spongy” phase. Clusters in the spongy phase are compact as far as the size-mass relation M ∼ RD is concerned (with D being the space dimension) but have an outer surface (or “hull”) whose fractal dimension is also D and which is indeed dense in the interior of the entire cluster. This behavior is found in all dimensions D 3. Slightly supercritical clusters can be of either type in D = 3, while they are always spongy in D 4. Possible consequences for the applicability of Kardar-Parisi- Zhang (KPZ) scaling to interfaces in media with frozen pinning centers are studied in detail. In particular, we find—in contrast to KPZ—a weak-coupling phase in 2+1 dimensions. DOI: 10.1103/PhysRevResearch.2.043150 I. INTRODUCTION sality class of critical percolation and thus fractal and isotropic on large scales. More precisely, the interfaces are in the class Rough surfaces and interfaces have a huge number of ap- of percolation hulls, i.e., of externally accessible surfaces of plications in nature and in technology. -
Peter Grassberger Physics Department, University of Wuppertal, Wuppertal, West-Germany Z
On Symbolic Dynamics of One-Humped Maps of the Interval Peter Grassberger Physics Department, University of Wuppertal, Wuppertal, West-Germany Z. Naturforsch. 43a, 671-680 (1988); received May 16, 1988 We present an explicit construction of minimal deterministic automata which accept the languages of L-R symbolic sequences of unimodal maps resp. arbitrarily close approximations thereof. They are used to study a recently introduced complexity measure of this language which we conjecture to be a new invariant under diffeomorphisms. On each graph corresponding to such an automaton, the evolution is a topological Markov chain which does not seem to correspond to a partition of the interval into a countable number of intervals. 1. Introduction at x = 0 also for other unimodal maps. Denote One of the most interesting discoveries of the last L if < 0, decades is that formally deterministic but "chaotic" C if = 0, systems can behave in a way which only can be de R if > 0. scribed as random. In particular, there occurs an information loss dur Since nearly all (in the sense of Lebesgue measure) ing the evolution of the system. If it is not permanently trajectories will avoid the point x = 0, they can be observed, any prediction can only be made with a encoded as sequences of R's and L's only. The Shan precision worse than the precision with which the ini non information stored in such a sequence is propor tial conditions were known. If one keeps to some fixed tional to its length, with the proportionality constant precision by making a finite partition of phase space, being the Kolmogorov entropy. -
Toc Carry Overs (Print, Part 2)
CONTENTS - Continued PHYSICAL REVIEW E THIRD SERIES, VOLUME 79, NUMBER 5 MAY 2009 Using detrended fluctuation analysis for lagged correlation analysis of nonstationary signals (4 pages) ....... 057202 Jose Alvarez-Ramirez, Eduardo Rodriguez, and Juan Carlos Echeverria Plasma physics Positive and negative streamers in air: Velocity-diameter relation (4 pages) ............................. 057401 G. V. Naidis Computational physics Relationship between Hirsch-Fye and weak-coupling diagrammatic quantum Monte Carlo methods (4 pages) ................................................................................... 057701 K. Mikelsons, A. Macridin, and M. Jarrell Distance of closest approach of two arbitrary hard ellipsoids (4 pages) ................................ 057702 Xiaoyu Zheng, Wilder Iglesias, and Peter Palffy-Muhoray ERRATA Erratum: Nanorheology of viscoelastic shells: Applications to viral capsids ͓Phys. Rev. E. 77, 031921 ͑2008͔͒ (1 page) ................................................................................... 059901͑E͒ Tatiana Kuriabova and Alex J. Levine CONTENTS - Continued PHYSICAL REVIEW E THIRD SERIES, VOLUME 79, NUMBER 5 MAY 2009 Computational physics Theoretical considerations on the free-surface role in the smoothed-particle-hydrodynamics model (13 pages) .................................................................................. 056701 Andrea Colagrossi, Matteo Antuono, and David Le Touzé Computation of the response functions of spiral waves in active media (10 pages) ....................... 056702 I. -
Mechanical Engineering
World Scientific Connecting Great Minds 2021 MECHANICAL ENGINEERING New books available on WorldSciNet HighlightsHighlights Mechanical Engineering Catalogue 2021 page 4 page 10 page 10 page 10 page 10 edited by Tugrul U Daim (Portland State by Christopher Bailey, by James D Lee edited by Prasenjit Chatterjee edited by Yong Huang University, USA & Higher School of Stoyan Stoyanov & (The George Washington (MCKV Institute of Engineering, (University of Florida, USA), Economics, Russia & Chaoyang University Hua Lu (University of University, USA) & India), Morteza Yazdani Lihui Wang (KTH Royal of Technology, Taiwan) & Alexander Brem (Universidad Loyola Andalucía, Greenwich, UK) Jiaoyan Li (Idaho National Institute of Technology, Sweden) (Friedrich-Alexander-Universität Erlangen- Laboratory, USA) Spain) & Shankar Chakraborty & Steven Y Liang (Georgia Nürnberg, Germany) (Jadavpur University, India) Institute of Tech., USA) page 11 page 11 page 14 page 14 page 14 by Michael Z Q Chen (Nanjing by Wolfgang Kühn by Gao Bai by Jay F Tu by Lei Cui (Curtin University, University of Science and Technology, (University of Wuppertal, (Duke University, USA) (North Carolina State Australia) & Jian S Dai China), Kai Wang (Jiangnan University, Germany) University, USA) (King’s College London, UK) China) & Guanrong Chen (City University of Hong Kong, China) page 14 page 14 page 14 page 15 page 15 by John Dirk Walecka by Isaac Elishakoff edited by S Erik Offerman by David Basco by J William Kamphuis (College of William and (Florida Atlantic University, (Delft -
How Nature Works: the Science of Self-Organized Criticality/ Per Bak
how nature works c Springer Science+Business Media, LLC PERBAK how nature works © 1996 Springer Science+Business Media New York Originally published by Springer-Verlag New York Inc. in 1996 Softcover reprint of the hardcover 1st edition 1996 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. All characters except for historical personages are ficticious. Library of Congress Cataloging-in-Publication Data Bak,P. (Per), 194?- How nature works: the science of self-organized criticality/ Per Bak. p. em. Includes bibliographical references and index. ISBN 978-0-387-98738-5 ISBN 978-1-4757-5426-1 (eBook) DOI 10.1007/978-14757-5426-1 r. Critical phenomena (Physics) 2. Complexity (Philosophy) 3· Physics-Philosophy. I. Title. QC173+C74B34 1996 00 31 .7-dc2o Printed on acid-free paper. Designed by N ikita Pristouris 9 8 7 6 5 4 3 2 SPIN 10523741 ISBN 978-o-387-98738-5 Who could ever calculate the path of a molecule? How do we know that the creations of worlds are not determined by falling grains of sand? -Victor Hugo, Les M;serables Contents Preface and Acknowledgments Xl Chapter 1 Complex~ty and Cr~t~cal~ty 1 The Laws of Physics Are Simple, but Nature Is Complex . .3 . Storytelling Versus Science . 7. What Can a Theory of Complexity Explain? . 9 Power Laws and Criticality . .27 . Systems in Balance Are Not Complex . .28 . -
Chen System As a Controlled Weather Model - Physical Principle, Engineering Design and Real Applications
Chen System as a Controlled Weather Model - Physical Principle, Engineering Design and Real Applications Sooraksa, Pitikhate; Chen, Guanrong Published in: International Journal of Bifurcation and Chaos Published: 01/04/2018 Document Version: Final Published version, also known as Publisher’s PDF, Publisher’s Final version or Version of Record License: CC BY Publication record in CityU Scholars: Go to record Published version (DOI): 10.1142/S0218127418300094 Publication details: Sooraksa, P., & Chen, G. (2018). Chen System as a Controlled Weather Model - Physical Principle, Engineering Design and Real Applications. International Journal of Bifurcation and Chaos, 28(4), [1830009]. https://doi.org/10.1142/S0218127418300094 Citing this paper Please note that where the full-text provided on CityU Scholars is the Post-print version (also known as Accepted Author Manuscript, Peer-reviewed or Author Final version), it may differ from the Final Published version. When citing, ensure that you check and use the publisher's definitive version for pagination and other details. General rights Copyright for the publications made accessible via the CityU Scholars portal is retained by the author(s) and/or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Users may not further distribute the material or use it for any profit-making activity or commercial gain. Publisher permission Permission for previously published items are in accordance with publisher's copyright policies sourced from the SHERPA RoMEO database. Links to full text versions (either Published or Post-print) are only available if corresponding publishers allow open access.