Glossary of Some Terms in Dynamical Systems Theory
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CHAOS and DYNAMICAL SYSTEMS Spring 2021 Lectures: Monday, Wednesday, 11:00–12:15PM ET Recitation: Friday, 12:30–1:45PM ET
MATH-UA 264.001 – CHAOS AND DYNAMICAL SYSTEMS Spring 2021 Lectures: Monday, Wednesday, 11:00–12:15PM ET Recitation: Friday, 12:30–1:45PM ET Objectives Dynamical systems theory is the branch of mathematics that studies the properties of iterated action of maps on spaces. It provides a mathematical framework to characterize a great variety of time-evolving phenomena in areas such as physics, ecology, and finance, among many other disciplines. In this class we will study dynamical systems that evolve in discrete time, as well as continuous-time dynamical systems described by ordinary di↵erential equations. Of particular focus will be to explore and understand the qualitative properties of dynamics, such as the existence of attractors, periodic orbits and chaos. We will do this by means of mathematical analysis, as well as simple numerical experiments. List of topics • One- and two-dimensional maps. • Linearization, stable and unstable manifolds. • Attractors, chaotic behavior of maps. • Linear and nonlinear continuous-time systems. • Limit sets, periodic orbits. • Chaos in di↵erential equations, Lyapunov exponents. • Bifurcations. Contact and office hours • Instructor: Dimitris Giannakis, [email protected]. Office hours: Monday 5:00-6:00PM and Wednesday 4:30–5:30PM ET. • Recitation Leader: Wenjing Dong, [email protected]. Office hours: Tuesday 4:00-5:00PM ET. Textbooks • Required: – Alligood, Sauer, Yorke, Chaos: An Introduction to Dynamical Systems, Springer. Available online at https://link.springer.com/book/10.1007%2Fb97589. • Recommended: – Strogatz, Nonlinear Dynamics and Chaos. – Hirsch, Smale, Devaney, Di↵erential Equations, Dynamical Systems, and an Introduction to Chaos. Available online at https://www.sciencedirect.com/science/book/9780123820105. -
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods Yi Ding Panos Toulis University of Chicago University of Chicago Department of Computer Science Booth School of Business Abstract In this paper, we adopt results in nonlinear time series analysis for causal inference in dynamical settings. Our motivation is policy analysis with panel data, particularly through the use of “synthetic control” methods. These methods regress pre-intervention outcomes of the treated unit to outcomes from a pool of control units, and then use the fitted regres- sion model to estimate causal effects post- intervention. In this setting, we propose to screen out control units that have a weak dy- Figure 1: A Lorenz attractor plotted in 3D. namical relationship to the treated unit. In simulations, we show that this method can mitigate bias from “cherry-picking” of control However, in many real-world settings, different vari- units, which is usually an important concern. ables exhibit dynamic interdependence, sometimes We illustrate on real-world applications, in- showing positive correlation and sometimes negative. cluding the tobacco legislation example of Such ephemeral correlations can be illustrated with Abadie et al.(2010), and Brexit. a popular dynamical system shown in Figure1, the Lorenz system (Lorenz, 1963). The trajectory resem- bles a butterfly shape indicating varying correlations 1 Introduction at different times: in one wing of the shape, variables X and Y appear to be positively correlated, and in the In causal inference, we compare outcomes of units who other they are negatively correlated. Such dynamics received the treatment with outcomes from units who present new methodological challenges for causal in- did not. -
A Gentle Introduction to Dynamical Systems Theory for Researchers in Speech, Language, and Music
A Gentle Introduction to Dynamical Systems Theory for Researchers in Speech, Language, and Music. Talk given at PoRT workshop, Glasgow, July 2012 Fred Cummins, University College Dublin [1] Dynamical Systems Theory (DST) is the lingua franca of Physics (both Newtonian and modern), Biology, Chemistry, and many other sciences and non-sciences, such as Economics. To employ the tools of DST is to take an explanatory stance with respect to observed phenomena. DST is thus not just another tool in the box. Its use is a different way of doing science. DST is increasingly used in non-computational, non-representational, non-cognitivist approaches to understanding behavior (and perhaps brains). (Embodied, embedded, ecological, enactive theories within cognitive science.) [2] DST originates in the science of mechanics, developed by the (co-)inventor of the calculus: Isaac Newton. This revolutionary science gave us the seductive concept of the mechanism. Mechanics seeks to provide a deterministic account of the relation between the motions of massive bodies and the forces that act upon them. A dynamical system comprises • A state description that indexes the components at time t, and • A dynamic, which is a rule governing state change over time The choice of variables defines the state space. The dynamic associates an instantaneous rate of change with each point in the state space. Any specific instance of a dynamical system will trace out a single trajectory in state space. (This is often, misleadingly, called a solution to the underlying equations.) Description of a specific system therefore also requires specification of the initial conditions. In the domain of mechanics, where we seek to account for the motion of massive bodies, we know which variables to choose (position and velocity). -
The Celestial Mechanics of Newton
GENERAL I ARTICLE The Celestial Mechanics of Newton Dipankar Bhattacharya Newton's law of universal gravitation laid the physical foundation of celestial mechanics. This article reviews the steps towards the law of gravi tation, and highlights some applications to celes tial mechanics found in Newton's Principia. 1. Introduction Newton's Principia consists of three books; the third Dipankar Bhattacharya is at the Astrophysics Group dealing with the The System of the World puts forth of the Raman Research Newton's views on celestial mechanics. This third book Institute. His research is indeed the heart of Newton's "natural philosophy" interests cover all types of which draws heavily on the mathematical results derived cosmic explosions and in the first two books. Here he systematises his math their remnants. ematical findings and confronts them against a variety of observed phenomena culminating in a powerful and compelling development of the universal law of gravita tion. Newton lived in an era of exciting developments in Nat ural Philosophy. Some three decades before his birth J 0- hannes Kepler had announced his first two laws of plan etary motion (AD 1609), to be followed by the third law after a decade (AD 1619). These were empirical laws derived from accurate astronomical observations, and stirred the imagination of philosophers regarding their underlying cause. Mechanics of terrestrial bodies was also being developed around this time. Galileo's experiments were conducted in the early 17th century leading to the discovery of the Keywords laws of free fall and projectile motion. Galileo's Dialogue Celestial mechanics, astronomy, about the system of the world was published in 1632. -
Arxiv:0705.1142V1 [Math.DS] 8 May 2007 Cases New) and Are Ripe for Further Study
A PRIMER ON SUBSTITUTION TILINGS OF THE EUCLIDEAN PLANE NATALIE PRIEBE FRANK Abstract. This paper is intended to provide an introduction to the theory of substitution tilings. For our purposes, tiling substitution rules are divided into two broad classes: geometric and combi- natorial. Geometric substitution tilings include self-similar tilings such as the well-known Penrose tilings; for this class there is a substantial body of research in the literature. Combinatorial sub- stitutions are just beginning to be examined, and some of what we present here is new. We give numerous examples, mention selected major results, discuss connections between the two classes of substitutions, include current research perspectives and questions, and provide an extensive bib- liography. Although the author attempts to fairly represent the as a whole, the paper is not an exhaustive survey, and she apologizes for any important omissions. 1. Introduction d A tiling substitution rule is a rule that can be used to construct infinite tilings of R using a finite number of tile types. The rule tells us how to \substitute" each tile type by a finite configuration of tiles in a way that can be repeated, growing ever larger pieces of tiling at each stage. In the d limit, an infinite tiling of R is obtained. In this paper we take the perspective that there are two major classes of tiling substitution rules: those based on a linear expansion map and those relying instead upon a sort of \concatenation" of tiles. The first class, which we call geometric tiling substitutions, includes self-similar tilings, of which there are several well-known examples including the Penrose tilings. -
Curriculum Overview Physics/Pre-AP 2018-2019 1St Nine Weeks
Curriculum Overview Physics/Pre-AP 2018-2019 1st Nine Weeks RESOURCES: Essential Physics (Ergopedia – online book) Physics Classroom http://www.physicsclassroom.com/ PHET Simulations https://phet.colorado.edu/ ONGOING TEKS: 1A, 1B, 2A, 2B, 2C, 2D, 2F, 2G, 2H, 2I, 2J,3E 1) SAFETY TEKS 1A, 1B Vocabulary Fume hood, fire blanket, fire extinguisher, goggle sanitizer, eye wash, safety shower, impact goggles, chemical safety goggles, fire exit, electrical safety cut off, apron, broken glass container, disposal alert, biological hazard, open flame alert, thermal safety, sharp object safety, fume safety, electrical safety, plant safety, animal safety, radioactive safety, clothing protection safety, fire safety, explosion safety, eye safety, poison safety, chemical safety Key Concepts The student will be able to determine if a situation in the physics lab is a safe practice and what appropriate safety equipment and safety warning signs may be needed in a physics lab. The student will be able to determine the proper disposal or recycling of materials in the physics lab. Essential Questions 1. How are safe practices in school, home or job applied? 2. What are the consequences for not using safety equipment or following safe practices? 2) SCIENCE OF PHYSICS: Glossary, Pages 35, 39 TEKS 2B, 2C Vocabulary Matter, energy, hypothesis, theory, objectivity, reproducibility, experiment, qualitative, quantitative, engineering, technology, science, pseudo-science, non-science Key Concepts The student will know that scientific hypotheses are tentative and testable statements that must be capable of being supported or not supported by observational evidence. The student will know that scientific theories are based on natural and physical phenomena and are capable of being tested by multiple independent researchers. -
Handbook of Dynamical Systems
Handbook Of Dynamical Systems Parochial Chrisy dunes: he waggles his medicine testily and punctiliously. Draggled Bealle engirds her impuissance so ding-dongdistractively Allyn that phagocytoseOzzie Russianizing purringly very and inconsumably. perhaps. Ulick usually kotows lineally or fossilise idiopathically when Modern analytical methods in handbook of skeleton signals that Ale Jan Homburg Google Scholar. Your wishlist items are not longer accessible through the associated public hyperlink. Bandelow, L Recke and B Sandstede. Dynamical Systems and mob Handbook Archive. Are neurodynamic organizations a fundamental property of teamwork? The i card you entered has early been redeemed. Katok A, Bernoulli diffeomorphisms on surfaces, Ann. Routledge, Taylor and Francis Group. NOTE: Funds will be deducted from your Flipkart Gift Card when your place manner order. Attendance at all activities marked with this symbol will be monitored. As well as dynamical system, we must only when interventions happen in. This second half a Volume 1 of practice Handbook follows Volume 1A which was published in 2002 The contents of stain two tightly integrated parts taken together. This promotion has been applied to your account. Constructing dynamical systems having homoclinic bifurcation points of codimension two. You has not logged in origin have two options hinari requires you to log in before first you mean access to articles from allowance of Dynamical Systems. Learn more about Amazon Prime. Dynamical system in nLab. Dynamical Systems Mathematical Sciences. In this volume, the authors present a collection of surveys on various aspects of the theory of bifurcations of differentiable dynamical systems and related topics. Since it contains items is not enter your country yet. -
Writing the History of Dynamical Systems and Chaos
Historia Mathematica 29 (2002), 273–339 doi:10.1006/hmat.2002.2351 Writing the History of Dynamical Systems and Chaos: View metadata, citation and similar papersLongue at core.ac.uk Dur´ee and Revolution, Disciplines and Cultures1 brought to you by CORE provided by Elsevier - Publisher Connector David Aubin Max-Planck Institut fur¨ Wissenschaftsgeschichte, Berlin, Germany E-mail: [email protected] and Amy Dahan Dalmedico Centre national de la recherche scientifique and Centre Alexandre-Koyre,´ Paris, France E-mail: [email protected] Between the late 1960s and the beginning of the 1980s, the wide recognition that simple dynamical laws could give rise to complex behaviors was sometimes hailed as a true scientific revolution impacting several disciplines, for which a striking label was coined—“chaos.” Mathematicians quickly pointed out that the purported revolution was relying on the abstract theory of dynamical systems founded in the late 19th century by Henri Poincar´e who had already reached a similar conclusion. In this paper, we flesh out the historiographical tensions arising from these confrontations: longue-duree´ history and revolution; abstract mathematics and the use of mathematical techniques in various other domains. After reviewing the historiography of dynamical systems theory from Poincar´e to the 1960s, we highlight the pioneering work of a few individuals (Steve Smale, Edward Lorenz, David Ruelle). We then go on to discuss the nature of the chaos phenomenon, which, we argue, was a conceptual reconfiguration as -
Classical Particle Trajectories‡
1 Variational approach to a theory of CLASSICAL PARTICLE TRAJECTORIES ‡ Introduction. The problem central to the classical mechanics of a particle is usually construed to be to discover the function x(t) that describes—relative to an inertial Cartesian reference frame—the positions assumed by the particle at successive times t. This is the problem addressed by Newton, according to whom our analytical task is to discover the solution of the differential equation d2x(t) m = F (x(t)) dt2 that conforms to prescribed initial data x(0) = x0, x˙ (0) = v0. Here I explore an alternative approach to the same physical problem, which we cleave into two parts: we look first for the trajectory traced by the particle, and then—as a separate exercise—for its rate of progress along that trajectory. The discussion will cast new light on (among other things) an important but frequently misinterpreted variational principle, and upon a curious relationship between the “motion of particles” and the “motion of photons”—the one being, when you think about it, hardly more abstract than the other. ‡ The following material is based upon notes from a Reed College Physics Seminar “Geometrical Mechanics: Remarks commemorative of Heinrich Hertz” that was presented February . 2 Classical trajectories 1. “Transit time” in 1-dimensional mechanics. To describe (relative to an inertial frame) the 1-dimensional motion of a mass point m we were taught by Newton to write mx¨ = F (x) − d If F (x) is “conservative” F (x)= dx U(x) (which in the 1-dimensional case is automatic) then, by a familiar line of argument, ≡ 1 2 ˙ E 2 mx˙ + U(x) is conserved: E =0 Therefore the speed of the particle when at x can be described 2 − v(x)= m E U(x) (1) and is determined (see the Figure 1) by the “local depth E − U(x) of the potential lake.” Several useful conclusions are immediate. -
Failure of Engineering Artifacts: a Life Cycle Approach
Sci Eng Ethics DOI 10.1007/s11948-012-9360-0 ORIGINAL PAPER Failure of Engineering Artifacts: A Life Cycle Approach Luca Del Frate Received: 30 August 2011 / Accepted: 13 February 2012 Ó The Author(s) 2012. This article is published with open access at Springerlink.com Abstract Failure is a central notion both in ethics of engineering and in engi- neering practice. Engineers devote considerable resources to assure their products will not fail and considerable progress has been made in the development of tools and methods for understanding and avoiding failure. Engineering ethics, on the other hand, is concerned with the moral and social aspects related to the causes and consequences of technological failures. But what is meant by failure, and what does it mean that a failure has occurred? The subject of this paper is how engineers use and define this notion. Although a traditional definition of failure can be identified that is shared by a large part of the engineering community, the literature shows that engineers are willing to consider as failures also events and circumstance that are at odds with this traditional definition. These cases violate one or more of three assumptions made by the traditional approach to failure. An alternative approach, inspired by the notion of product life cycle, is proposed which dispenses with these assumptions. Besides being able to address the traditional cases of failure, it can deal successfully with the problematic cases. The adoption of a life cycle perspective allows the introduction of a clearer notion of failure and allows a classification of failure phenomena that takes into account the roles of stakeholders involved in the various stages of a product life cycle. -
Homogeneous Dynamical Systems Theory Bijoy K
462 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 47, NO. 3, MARCH 2002 Homogeneous Dynamical Systems Theory Bijoy K. Ghosh, Fellow, IEEE, and Clyde F. Martin, Fellow, IEEE Abstract—In this paper, we study controlled homogeneous dy- where the scalar output may be considered to be the slope namical systems and derive conditions under which the system is of the line spanned by the vector and where perspective controllable. We also derive conditions under which the system is observable in the presence of a control over the com- plex base field. In the absence of any control input, we derive a nec- essary and sufficient condition for observability of a homogeneous (1.3) dynamical system over the real base field. The observability crite- rion obtained generalizes a well known Popov–Belevitch–Hautus (PBH) rank criterion to check the observability of a linear dynam- ical system. Finally, we introduce rational, exponential, interpola- For a dynamical system of the form (1.1), (1.2), one is tion problems as an important step toward solving the problem of interested in controlling only the direction of the state vector realizing homogeneous dynamical systems with minimum state di- and such problems are, therefore, of interest in mensions. gaze control. To generalize the control problem, we consider a Index Terms—Author, please supply your own keywords or send dynamical system with state variable , control variable a blank e-mail to [email protected] to receive a list of suggested and observation function , the projective keywords. space of homogeneous lines in , where we assume that . The dynamical system is described as I. -
Topic 6: Projected Dynamical Systems
Topic 6: Projected Dynamical Systems Professor Anna Nagurney John F. Smith Memorial Professor and Director – Virtual Center for Supernetworks Isenberg School of Management University of Massachusetts Amherst, Massachusetts 01003 SCH-MGMT 825 Management Science Seminar Variational Inequalities, Networks, and Game Theory Spring 2014 c Anna Nagurney 2014 Professor Anna Nagurney SCH-MGMT 825 Management Science Seminar Projected Dynamical Systems A plethora of equilibrium problems, including network equilibrium problems, can be uniformly formulated and studied as finite-dimensional variational inequality problems, as we have seen in the preceding lectures. Indeed, it was precisely the traffic network equilibrium problem, as stated by Smith (1979), and identified by Dafermos (1980) to be a variational inequality problem, that gave birth to the ensuing research activity in variational inequality theory and applications in transportation science, regional science, operations research/management science, and, more recently, in economics. Professor Anna Nagurney SCH-MGMT 825 Management Science Seminar Projected Dynamical Systems Usually, using this methodology, one first formulates the governing equilibrium conditions as a variational inequality problem. Qualitative properties of existence and uniqueness of solutions to a variational inequality problem can then be studied using the standard theory or by exploiting problem structure. Finally, a variety of algorithms for the computation of solutions to finite-dimensional variational inequality problems are now available (see, e.g., Nagurney (1999, 2006)). Professor Anna Nagurney SCH-MGMT 825 Management Science Seminar Projected Dynamical Systems Finite-dimensional variational inequality theory by itself, however, provides no framework for the study of the dynamics of competitive systems. Rather, it captures the system at its equilibrium state and, hence, the focus of this tool is static in nature.