The Emergence of Complexity
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What Is a Complex Adaptive System?
PROJECT GUTS What is a Complex Adaptive System? Introduction During the last three decades a leap has been made from the application of computing to help scientists ‘do’ science to the integration of computer science concepts, tools and theorems into the very fabric of science. The modeling of complex adaptive systems (CAS) is an example of such an integration of computer science into the very fabric of science; models of complex systems are used to understand, predict and prevent the most daunting problems we face today; issues such as climate change, loss of biodiversity, energy consumption and virulent disease affect us all. The study of complex adaptive systems, has come to be seen as a scientific frontier, and an increasing ability to interact systematically with highly complex systems that transcend separate disciplines will have a profound affect on future science, engineering and industry as well as in the management of our planet’s resources (Emmott et al., 2006). The name itself, “complex adaptive systems” conjures up images of complicated ideas that might be too difficult for a novice to understand. Instead, the study of CAS does exactly the opposite; it creates a unified method of studying disparate systems that elucidates the processes by which they operate. A complex system is simply a system in which many independent elements or agents interact, leading to emergent outcomes that are often difficult (or impossible) to predict simply by looking at the individual interactions. The “complex” part of CAS refers in fact to the vast interconnectedness of these systems. Using the principles of CAS to study these topics as related disciplines that can be better understood through the application of models, rather than a disparate collection of facts can strengthen learners’ understanding of these topics and prepare them to understand other systems by applying similar methods of analysis (Emmott et al., 2006). -
Dimensions of Ecosystem Complexity: Heterogeneity, Connectivity, and History
ecological complexity 3 (2006) 1–12 available at www.sciencedirect.com journal homepage: http://www.elsevier.com/locate/ecocom Viewpoint Dimensions of ecosystem complexity: Heterogeneity, connectivity, and history M.L. Cadenasso a,*, S.T.A. Pickett b, J.M. Grove c a Hixon Center for Urban Ecology, School of Forestry and Environmental Studies, Yale University, 205 Prospect Street, New Haven, CT 06511, United States b Institute of Ecosystem Studies, Box AB, Millbrook, NY 12545, United States c USDA Forest Service, Northeastern Research Station, 705 Spear Street, P.O. Box 968, Burlington, VT 05401, United States article info abstract Article history: Biocomplexity was introduced to most ecologists through the National Science Foundation’s Received 2 June 2005 grant program, and the literature intended to introduce that program. The generalities of that Received in revised form literature contrast with the abstract and mathematical sophistication of literature from 30 June 2005 physics, systems theory, and indeed even of pioneering ecologists who have translated the Accepted 2 July 2005 conceptintoecology. Thissituation leaves a middle ground, that isboth accessibletoecologists Published on line 23 January 2006 in general, and cognizant of the fundamentals of complexity, to be more completely explored. To help scope this middle ground, and to promote empirical explorations that may be located Keywords: there, we propose a non-exclusive framework for the conceptual territory. While recognizing Biocomplexity the deep foundations in the studies of complex behavior, we take ecological structure as the Framework entry point for framework development. This framework is based on a definition of biocom- Coupled systems plexity as the degree to which ecological systems comprising biological, social and physical Spatial heterogeneity components incorporate spatially explicit heterogeneity, organizational connectivity, and Legacies historical contingency through time. -
Jet Development in Leading Log QCD.Pdf
17 CALT-68-740 DoE RESEARCH AND DEVELOPMENT REPORT Jet Development in Leading Log QCD * by STEPHEN WOLFRAM California Institute of Technology, Pasadena. California 91125 ABSTRACT A simple picture of jet development in QCD is described. Various appli- cations are treated, including transverse spreading of jets, hadroproduced y* pT distributions, lepton energy spectra from heavy quark decays, soft parton multiplicities and hadron cluster formation. *Work supported in part by the U.S. Department of Energy under Contract No. DE-AC-03-79ER0068 and by a Feynman Fellowship. 18 According to QCD, high-energy e+- e annihilation into hadrons is initiated by the production from the decaying virtual photon of a quark and an antiquark, ,- +- each with invariant masses up to the c.m. energy vs in the original e e collision. The q and q then travel outwards radiating gluons which serve to spread their energy and color into a jet of finite angle. After a time ~ 1/IS, the rate of gluon emissions presumably decreases roughly inversely with time, except for the logarithmic rise associated with the effective coupling con 2 stant, (a (t) ~ l/log(t/A ), where It is the invariant mass of the radiating s . quark). Finally, when emissions have degraded the energies of the partons produced until their invariant masses fall below some critical ~ (probably c a few times h), the system of quarks and gluons begins to condense into the observed hadrons. The probability for a gluon to be emitted at times of 0(--)1 is small IS and may be est~mated from the leading terms of a perturbation series in a (s). -
Organization, Self-Organization, Autonomy and Emergence: Status and Challenges
Organization, Self-Organization, Autonomy and Emergence: Status and Challenges Sven Brueckner 1 Hans Czap 2 1 New Vectors LLC 3520 Green Court, Suite 250, Ann Arbor, MI 48105-1579, USA Email: [email protected] http://www.altarum.net/~sbrueckner 2 University of Trier, FB IV Business Information Systems I D-54286 Trier, Germany Email: [email protected] http://www.wi.uni-trier.de/ Abstract: Development of IT-systems in application react and adapt autonomously to changing requirements. domains is facing an ever-growing complexity resulting from Therefore, approaches that rely on the fundamental principles a continuous increase in dynamics of processes, applications- of self-organization and autonomy are growing in acceptance. and run-time environments and scaling. The impact of this Following such approaches, software system functionality trend is amplified by the lack of central control structures. As is no longer explicitly designed into its component processes a consequence, controlling this complexity and dynamics is but emerges from lower-level interactions that are one of the most challenging requirements of today’s system purposefully unaware of the system-wide behavior. engineers. Furthermore, organization, the meaningful progression of The lack of a central control instance immediately raises local sensing, processing and action, is achieved by the the need for software systems which can react autonomously system components themselves at runtime and in response to to changing environmental requirements and conditions. the current state of the environment and the problem that is to Therefore, a new paradigm is necessary how to build be solved, rather than being enforced from the “outside” software systems changing radically the way one is used to through design or external control. -
A New Kind of Science; Stephen Wolfram, Wolfram Media, Inc., 2002
A New Kind of Science; Stephen Wolfram, Wolfram Media, Inc., 2002. Almost twenty years ago, I heard Stephen Wolfram speak at a Gordon Confer- ence about cellular automata (CA) and how they can be used to model seashell patterns. He had recently made a splash with a number of important papers applying CA to a variety of physical and biological systems. His early work on CA focused on a classification of the behavior of simple one-dimensional sys- tems and he published some interesting papers suggesting that CA fall into four different classes. This was original work but from a mathematical point of view, hardly rigorous. What he was essentially claiming was that even if one adds more layers of complexity to the simple rules, one does not gain anything be- yond these four simples types of behavior (which I will describe below). After a two decade hiatus from science (during which he founded Wolfram Science, the makers of Mathematica), Wolfram has self-published his magnum opus A New Kind of Science which continues along those lines of thinking. The book itself is beautiful to look at with almost a thousand pictures, 850 pages of text and over 300 pages of detailed notes. Indeed, one might suggest that the main text is for the general public while the notes (which exceed the text in total words) are aimed at a more technical audience. The book has an associated web site complete with a glowing blurb from the publisher, quotes from the media and an interview with himself to answer questions about the book. -
Jump Bifurcation and Hysteresis in an Infinite-Dimensional Dynamical System of Coupled Spins*
SIAM J. APPL. MATH. (C) 1990 Society for Industrial and Applied Mathematics Vol. 50, No. 1, pp. 108-124, February 1990 008 JUMP BIFURCATION AND HYSTERESIS IN AN INFINITE-DIMENSIONAL DYNAMICAL SYSTEM OF COUPLED SPINS* RENATO E. MIROLLOt AND STEVEN H. STROGATZ: Abstract. This paper studies an infinite-dimensional dynamical system that models a collection of coupled spins in a random magnetic field. A state of the system is given by a self-map of the unit circle. Critical states for the dynamical system correspond to equilibrium configurations of the spins. Exact solutions are obtained for all the critical states and their stability is characterized by analyzing the second variation of the system's potential function at those states. It is proven rigorously that the system exhibits a jump bifurcation and hysteresis as the coupling between spins is varied. Key words, bifurcation, dynamical system, phase transition, spin system AMS(MOS) subject classifications. 58F14, 82A57, 34F05 1. Introduction. There is currently a great deal of interest in the collective behavior of dynamical systems with many interacting subunits [2]. Such systems are very difficult to analyze rigorously unless some simplifying assumptions are made. "Phase models," in which each subunit is characterized by a single phase angle Oi, provide an analytically tractable class of many-body systems. Phase models have been used in a wide variety of scientific contexts, including charge-density wave transport [8], [9], [23], [24], magnetic spin systems [3], [26], oscillating chemical reactions 15], 18], [28], networks of biological oscillators [4], [7], [14], [27], [28], and arrays of Josephson junctions [11], [25]. -
2008-2009 Annual Report
ANNUAL REPORT 2008-2009 Photo: Shona Dion Photo: CONTENTS : annual report 2008-2009 Green College is a graduate residential college at the University of British Columbia, Principal’s Report............................p. 2 with a mandate to promote advanced 2008-2009 Highlights......................p. 4 interdisciplinary inquiry. The College offers Academic Programming................p. 5 resident membership to graduate students, Cecil H. and Ida Green Visiting Professorships........p. 6 Writer-in-Residence........................................................ p. 7 postdoctoral scholars and visiting faculty at Weekly Interdisciplinary Series.................................... p. 8 Monthly Interdisciplinary Series................................. p. 11 UBC, and (non-resident) faculty membership Conferences, Colloquia, and Workshops.................. p. 16 Special Lectures............................................................... p. 17 to UBC and other faculty. The College is committed to the cultivation ofintellectual College Committees......................p. 18 Standing Committees......................................................p. 18 and creative connections at the edge of the Faculty Council................................................................ p. 19 Residents’ Council.......................................................... p. 19 main disciplinary and academic space of the Resident Committees................... ................................. p. 20 university. To that end, it provides extracurricular Green -
PARTON and HADRON PRODUCTION in E+E- ANNIHILATION Stephen Wolfram California Institute of Technology, Pasadena, California 91125
549 * PARTON AND HADRON PRODUCTION IN e+e- ANNIHILATION Stephen Wolfram California Institute of Technology, Pasadena, California 91125 Ab stract: The production of showers of partons in e+e- annihilation final states is described according to QCD , and the formation of hadrons is dis cussed. Resume : On y decrit la production d'averses d� partons dans la theorie QCD qui forment l'etat final de !'annihilation e+ e , ainsi que leur transform ation en hadrons. *Work supported in part by the U.S. Department of Energy under contract no. DE-AC-03-79ER0068. SSt1 Introduction In these notes , I discuss some attemp ts e ri the cl!evellope1!1t of - to d s c be hadron final states in e e annihilation events ll>Sing. QCD. few featm11res A (barely visible at available+ energies} of this deve l"'P"1'ent amenab lle· are lt<J a precise and formal analysis in QCD by means of pe·rturbatirnc• the<J ry. lfor the mos t part, however, existing are quite inadle<!i""' lte! theoretical mett:l�ods one must therefore simply try to identify dl-iimam;t physical p.l:ten<0melilla tt:he to be expected from QCD, and make estll!att:es of dne:i.r effects , vi.th the hop·e that results so obtained will provide a good appro�::illliatimn to eventllLal'c ex act calculations . In so far as such estllma�es r necessa�y� pre�ise �r..uan- a e titative tests of QCD are precluded . On the ott:her handl , if QC!Ji is ass11l!med correct, then existing experimental data to inve•stigate its be may \JJ:SE•«f havior in regions not yet explored by theoreticalbe llJleaums . -
The Problem of Distributed Consensus: a Survey Stephen Wolfram*
The Problem of Distributed Consensus: A Survey Stephen Wolfram* A survey is given of approaches to the problem of distributed consensus, focusing particularly on methods based on cellular automata and related systems. A variety of new results are given, as well as a history of the field and an extensive bibliography. Distributed consensus is of current relevance in a new generation of blockchain-related systems. In preparation for a conference entitled “Distributed Consensus with Cellular Automata and Related Systems” that we’re organizing with NKN (= “New Kind of Network”) I decided to explore the problem of distributed consensus using methods from A New Kind of Science (yes, NKN “rhymes” with NKS) as well as from the Wolfram Physics Project. A Simple Example Consider a collection of “nodes”, each one of two possible colors. We want to determine the majority or “consensus” color of the nodes, i.e. which color is the more common among the nodes. A version of this document with immediately executable code is available at writings.stephenwolfram.com/2021/05/the-problem-of-distributed-consensus Originally published May 17, 2021 *Email: [email protected] 2 | Stephen Wolfram One obvious method to find this “majority” color is just sequentially to visit each node, and tally up all the colors. But it’s potentially much more efficient if we can use a distributed algorithm, where we’re running computations in parallel across the various nodes. One possible algorithm works as follows. First connect each node to some number of neighbors. For now, we’ll just pick the neighbors according to the spatial layout of the nodes: The algorithm works in a sequence of steps, at each step updating the color of each node to be whatever the “majority color” of its neighbors is. -
Question-And-Answer-Physics-Today
Questions and answers with Steven Strogatz An applied mathematician notes that for many physics topics, including general relativity and climate science, the whole is often not equal to the sum of the parts. By Jeremy N. A. Matthews April 2015 Bookends: Questions and answers with Steven Strogatz Questions and answers with Peter Pesic Questions and answers with Marcelo Gleiser Questions and answers with Amit Hagar Questions and answers with A. Douglas Stone Steven Strogatz is the Jacob Schurman Professor of Applied Mathematics at Cornell University in Ithaca, New York. He conducts research on dynamical systems in physics, biology, and social science. His 1998 Nature article “Collective dynamics of ‘small-world’ networks” is considered a seminal contribution to complexity research. Strogatz is also an active communicator of mathematics and related topics to the public. He frequently appears on public radio and writes for The New Yorker and other publications. A 2015 recipient of the Lewis Thomas Prize for Writing About Science, he has written books that include Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Life (Hyperion, 2003) and The Joy of x: A Guided Tour of Math, from One to Infinity (Houghton Mifflin Harcourt, 2012). Strogatz recently published the second edition of a text he wrote more than two decades ago. The new edition of Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (Westview Press, 2015) contains new exercises on such topics as protein dynamics and superconductivity and covers applications in such emerging fields as sociophysics and systems biology. Physics Today reviewed the book in the April issue. -
Toward a New Science of Information
Data Science Journal, Volume 6, Supplement, 7 April 2007 TOWARD A NEW SCIENCE OF INFORMATION D Doucette1*, R Bichler 2, W Hofkirchner2, and C Raffl2 *1 The Science of Information Institute, 1737 Q Street, N.W. Washington, D.C. 20009, USA Email: [email protected] 2 ICT&S Center, University of Salzburg - Center for Advanced Studies and Research in Information and Communication Technologies & Society, Sigmund-Haffner-Gasse 18, 5020 Salzburg, Austria Email: [email protected], [email protected], [email protected] ABSTRACT The concept of information has become a crucial topic in several emerging scientific disciplines, as well as in organizations, in companies and in everyday life. Hence it is legitimate to speak of the so-called information society; but a scientific understanding of the Information Age has not had time to develop. Following this evolution we face the need of a new transdisciplinary understanding of information, encompassing many academic disciplines and new fields of interest. Therefore a Science of Information is required. The goal of this paper is to discuss the aims, the scope, and the tools of a Science of Information. Furthermore we describe the new Science of Information Institute (SOII), which will be established as an international and transdisciplinary organization that takes into consideration a larger perspective of information. Keywords: Information, Science of Information, Information Society, Transdisciplinarity, Science of Information Institute (SOII), Foundations of Information Science (FIS) 1 INTRODUCTION Information is emerging as a new and large prospective area of study. The notion of information has become a crucial topic in several emerging scientific disciplines such as Philosophy of Information, Quantum Information, Bioinformatics and Biosemiotics, Theory of Mind, Systems Theory, Internet Research, and many more. -
Emergence in Psychology: Lessons from the History of Non-Reductionist Science
Paper Human Development 2002;45:2-28 Human Development Emergence in Psychology: Lessons from the History of Non-Reductionist Science R. Keith Sawyer Washington University, St.louis, Mo., USA KeyWords Cognitive science. Emergence. History. Reductionism. Socioculturalism Abstract Theories of emergence have had a longstanding influence on psychological thought. Emergentism rejects both reductionism and holism; emergentists are scientific materialists, and yet argue that reductionist explanation may not always be scientifically feasible. I begin by summarizing the history of emergence in psy- chology and sociology, from the mid-19th century through the mid-20th century. I then demonstrate several parallels between this history and contemporary psy- chology, focusing on two recent psychological movements: socioculturalism and connectionist cognitive science. Placed in historical context, both sociocultural ism and connectionism are seen to be revivals of 19th and early 20th century emergen- tism. I then draw on this history to identify several unresolved issues facing socio- culturalists and connectionists, and to suggest several promising paths for future theory. Copyright @ 2002 S. Karger AG, Base! 1. Introduction Emergentism is a form of materialism which holds that some complex natural phe- nomena cannot be studied using reductionist methods. My first goal in this paper is to identify the historical roots of two emergentist paradigms in contemporary psychology: sociocultural psychology and cognitive science. My second goal is to draw on this histo- ry to explore several unresolved issues facing these contemporary paradigms. Sociocul- tural psychologists are sociological emergentists; they hold that group behavior is consti- KARG E R <92002 S. Karger AG, Basel R. Keith Sawyer, Washington University .OOI8-716X/02/0451-0()()2$18.50/0 Department of Education, Campus Box 1183 Fax+41613061234 St.