Some Examples in Ergodic Theory
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Deterministic Brownian Motion: the Effects of Perturbing a Dynamical
1 Deterministic Brownian Motion: The Effects of Perturbing a Dynamical System by a Chaotic Semi-Dynamical System Michael C. Mackey∗and Marta Tyran-Kami´nska † October 26, 2018 Abstract Here we review and extend central limit theorems for highly chaotic but deterministic semi- dynamical discrete time systems. We then apply these results show how Brownian motion-like results are recovered, and how an Ornstein-Uhlenbeck process results within a totally determin- istic framework. These results illustrate that the contamination of experimental data by “noise” may, under certain circumstances, be alternately interpreted as the signature of an underlying chaotic process. Contents 1 Introduction 2 2 Semi-dynamical systems 5 2.1 Density evolution operators . ......... 5 2.2 Probabilistic and ergodic properties of density evolution ................ 12 2.3 Brownian motion from deterministic perturbations . ............... 16 2.3.1 Centrallimittheorems. ..... 16 2.3.2 FCLTfornoninvertiblemaps . ..... 20 2.4 Weak convergence criteria . ........ 31 3 Analysis 33 3.1 Weak convergence of v(tn) and vn. ............................ 35 3.2 Thelinearcaseinonedimension . ........ 36 3.2.1 Behaviour of the velocity variable . ......... 36 3.2.2 Behaviour of the position variable . ........ 38 4 Identifying the Limiting Velocity Distribution 41 4.1 Dyadicmap....................................... 42 arXiv:cond-mat/0408330v1 [cond-mat.stat-mech] 13 Aug 2004 4.2 Graphical illustration of the velocity density evolution with dyadic map perturbations 45 4.3 r-dyadicmap ..................................... 45 ∗e-mail: [email protected], Departments of Physiology, Physics & Mathematics and Centre for Nonlinear Dynamics, McGill University, 3655 Promenade Sir William Osler, Montreal, QC, CANADA, H3G 1Y6 †Corresponding author, email: [email protected], Institute of Mathematics, Silesian University, ul. -
Role of Nonlinear Dynamics and Chaos in Applied Sciences
v.;.;.:.:.:.;.;.^ ROLE OF NONLINEAR DYNAMICS AND CHAOS IN APPLIED SCIENCES by Quissan V. Lawande and Nirupam Maiti Theoretical Physics Oivisipn 2000 Please be aware that all of the Missing Pages in this document were originally blank pages BARC/2OOO/E/OO3 GOVERNMENT OF INDIA ATOMIC ENERGY COMMISSION ROLE OF NONLINEAR DYNAMICS AND CHAOS IN APPLIED SCIENCES by Quissan V. Lawande and Nirupam Maiti Theoretical Physics Division BHABHA ATOMIC RESEARCH CENTRE MUMBAI, INDIA 2000 BARC/2000/E/003 BIBLIOGRAPHIC DESCRIPTION SHEET FOR TECHNICAL REPORT (as per IS : 9400 - 1980) 01 Security classification: Unclassified • 02 Distribution: External 03 Report status: New 04 Series: BARC External • 05 Report type: Technical Report 06 Report No. : BARC/2000/E/003 07 Part No. or Volume No. : 08 Contract No.: 10 Title and subtitle: Role of nonlinear dynamics and chaos in applied sciences 11 Collation: 111 p., figs., ills. 13 Project No. : 20 Personal authors): Quissan V. Lawande; Nirupam Maiti 21 Affiliation ofauthor(s): Theoretical Physics Division, Bhabha Atomic Research Centre, Mumbai 22 Corporate authoifs): Bhabha Atomic Research Centre, Mumbai - 400 085 23 Originating unit : Theoretical Physics Division, BARC, Mumbai 24 Sponsors) Name: Department of Atomic Energy Type: Government Contd...(ii) -l- 30 Date of submission: January 2000 31 Publication/Issue date: February 2000 40 Publisher/Distributor: Head, Library and Information Services Division, Bhabha Atomic Research Centre, Mumbai 42 Form of distribution: Hard copy 50 Language of text: English 51 Language of summary: English 52 No. of references: 40 refs. 53 Gives data on: Abstract: Nonlinear dynamics manifests itself in a number of phenomena in both laboratory and day to day dealings. -
A Pseudo Random Numbers Generator Based on Chaotic Iterations
A Pseudo Random Numbers Generator Based on Chaotic Iterations. Application to Watermarking Christophe Guyeux, Qianxue Wang, Jacques Bahi To cite this version: Christophe Guyeux, Qianxue Wang, Jacques Bahi. A Pseudo Random Numbers Generator Based on Chaotic Iterations. Application to Watermarking. WISM 2010, Int. Conf. on Web Information Systems and Mining, 2010, China. pp.202–211. hal-00563317 HAL Id: hal-00563317 https://hal.archives-ouvertes.fr/hal-00563317 Submitted on 4 Feb 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A Pseudo Random Numbers Generator Based on Chaotic Iterations. Application to Watermarking Christophe Guyeux, Qianxue Wang, and Jacques M. Bahi University of Franche-Comte, Computer Science Laboratory LIFC, 25030 Besanc¸on Cedex, France {christophe.guyeux,qianxue.wang, jacques.bahi}@univ-fcomte.fr Abstract. In this paper, a new chaotic pseudo-random number generator (PRNG) is proposed. It combines the well-known ISAAC and XORshift generators with chaotic iterations. This PRNG possesses important properties of topological chaos and can successfully pass NIST and TestU01 batteries of tests. This makes our generator suitable for information security applications like cryptography. As an illustrative example, an application in the field of watermarking is presented. -
Arxiv:0705.0033V3 [Math.DS]
ERGODIC THEORY: RECURRENCE NIKOS FRANTZIKINAKIS AND RANDALL MCCUTCHEON Contents 1. Definition of the Subject and its Importance 3 2. Introduction 3 3. Quantitative Poincaré Recurrence 5 4. Subsequence Recurrence 7 5. Multiple Recurrence 11 6. Connections with Combinatorics and Number Theory 14 7. Future Directions 17 References 19 Almost every, essentially: Given a Lebesgue measure space (X, ,µ), a property P (x) predicated of elements of X is said to hold for almostB every x X, if the set X x: P (x) holds has zero measure. Two sets A, B are∈ essentially disjoint\ { if µ(A B) =} 0. ∈B Conservative system: Is an∩ infinite measure preserving system such that for no set A with positive measure are A, T −1A, T −2A, . pairwise essentially disjoint.∈ B (cn)-conservative system: If (cn)n∈N is a decreasing sequence of posi- tive real numbers, a conservative ergodic measure preserving transforma- 1 tion T is (cn)-conservative if for some non-negative function f L (µ), ∞ n ∈ n=1 cnf(T x)= a.e. arXiv:0705.0033v3 [math.DS] 4 Nov 2019 ∞ PDoubling map: If T is the interval [0, 1] with its endpoints identified and addition performed modulo 1, the (non-invertible) transformation T : T T, defined by Tx = 2x mod 1, preserves Lebesgue measure, hence induces→ a measure preserving system on T. Ergodic system: Is a measure preserving system (X, ,µ,T ) (finite or infinite) such that every A that is T -invariant (i.e. T −B1A = A) satisfies ∈B either µ(A) = 0 or µ(X A) = 0. (One can check that the rotation Rα is ergodic if and only if α is\ irrational, and that the doubling map is ergodic.) Ergodic decomposition: Every measure preserving system (X, ,µ,T ) can be expressed as an integral of ergodic systems; for example,X one can 2000 Mathematics Subject Classification. -
Dissipative Dynamical Systems and Their Attractors
Dissipative dynamical systems and their attractors Grzegorz ukaszewicz, University of Warsaw MIM Qolloquium, 05.11.2020 Plan of the talk Context: conservative and dissipative systems 3 Basic notions 10 Important problems of the theory. G.ukaszewicz Dissipative dynamical systems and their attractors Qolloquium 2 / 14 Newtonian mechanics ∼ conservative system of ODEs in Rn system reversible in time ∼ groups ∼ deterministic chaos From P. S. de Laplace to H. Poincaré, and ... Evolution of a conservative system Example 1. Motivation: Is our solar system stable? (physical system) G.ukaszewicz Dissipative dynamical systems and their attractors Qolloquium 3 / 14 Evolution of a conservative system Example 1. Motivation: Is our solar system stable? (physical system) Newtonian mechanics ∼ conservative system of ODEs in Rn system reversible in time ∼ groups ∼ deterministic chaos From P. S. de Laplace to H. Poincaré, and ... G.ukaszewicz Dissipative dynamical systems and their attractors Qolloquium 3 / 14 Mech. of continuous media ∼ dissipative system of PDEs in a Hilbert phase space system irreversible in time ∼ semigroups ∼ innite dimensional dynamical systems ∼ deterministic chaos Since O. Ladyzhenskaya's papers on the NSEs (∼ 1970) Evolution of a dissipative system Example 2. Motivation: How does turbulence in uids develop? G.ukaszewicz Dissipative dynamical systems and their attractors Qolloquium 4 / 14 Evolution of a dissipative system Example 2. Motivation: How does turbulence in uids develop? Mech. of continuous media ∼ dissipative system of PDEs in a Hilbert phase space system irreversible in time ∼ semigroups ∼ innite dimensional dynamical systems ∼ deterministic chaos Since O. Ladyzhenskaya's papers on the NSEs (∼ 1970) G.ukaszewicz Dissipative dynamical systems and their attractors Qolloquium 4 / 14 Let us compare the above problems Example 1. -
Energy Cycle for the Lorenz Attractor
Energy cycle for the Lorenz attractor Vinicio Pelino, Filippo Maimone Italian Air Force, CNMCA Aeroporto “De Bernardi”, Via di Pratica Di Mare, I-00040 Pratica di Mare (Roma) Italy In this note we study energetics of Lorenz-63 system through its Lie-Poisson structure. I. INTRODUCTION In 1955 E. Lorenz [1] introduced the concept of energy cycle as a powerful instrument to understand the nature of atmospheric circulation. In that context conversions between potential, kinetic and internal energy of a fluid were studied using atmospheric equations of motion under the action of an external radiative forcing and internal dissipative processes. Following these ideas, in this paper we will illustrate that chaotic dynamics governing Lorenz-63 model can be described introducing an appropriate energy cycle whose components are kinetic, potential energy and Casimir function derived from Lie-Poisson structure hidden in the system; Casimir functions, like enstrophy or potential vorticity in fluid dynamical context, are very useful in analysing stability conditions and global description of a dynamical system. A typical equation describing dissipative-forced dynamical systems can be written in Einstein notation as: x&ii=−Λ+{xH, } ijji x f i = 1,2...n (1) Equations (1) have been written by Kolmogorov, as reported in [2], in a fluid dynamical context, but they are very common in simulating natural processes as useful in chaos synchronization [3]. Here, antisymmetric brackets represent the algebraic structure of Hamiltonian part of a system described by function H , and a cosymplectic matrix J [4], {}F,G = J ik ∂ i F∂ k G . (2) Positive definite diagonal matrix Λ represents dissipation and the last term f represents external forcing. -
Transformations)
TRANSFORMACJE (TRANSFORMATIONS) Transformacje (Transformations) is an interdisciplinary refereed, reviewed journal, published since 1992. The journal is devoted to i.a.: civilizational and cultural transformations, information (knowledge) societies, global problematique, sustainable development, political philosophy and values, future studies. The journal's quasi-paradigm is TRANSFORMATION - as a present stage and form of development of technology, society, culture, civilization, values, mindsets etc. Impacts and potentialities of change and transition need new methodological tools, new visions and innovation for theoretical and practical capacity-building. The journal aims to promote inter-, multi- and transdisci- plinary approach, future orientation and strategic and global thinking. Transformacje (Transformations) are internationally available – since 2012 we have a licence agrement with the global database: EBSCO Publishing (Ipswich, MA, USA) We are listed by INDEX COPERNICUS since 2013 I TRANSFORMACJE(TRANSFORMATIONS) 3-4 (78-79) 2013 ISSN 1230-0292 Reviewed journal Published twice a year (double issues) in Polish and English (separate papers) Editorial Staff: Prof. Lech W. ZACHER, Center of Impact Assessment Studies and Forecasting, Kozminski University, Warsaw, Poland ([email protected]) – Editor-in-Chief Prof. Dora MARINOVA, Sustainability Policy Institute, Curtin University, Perth, Australia ([email protected]) – Deputy Editor-in-Chief Prof. Tadeusz MICZKA, Institute of Cultural and Interdisciplinary Studies, University of Silesia, Katowice, Poland ([email protected]) – Deputy Editor-in-Chief Dr Małgorzata SKÓRZEWSKA-AMBERG, School of Law, Kozminski University, Warsaw, Poland ([email protected]) – Coordinator Dr Alina BETLEJ, Institute of Sociology, John Paul II Catholic University of Lublin, Poland Dr Mirosław GEISE, Institute of Political Sciences, Kazimierz Wielki University, Bydgoszcz, Poland (also statistical editor) Prof. -
On the Topological Conjugacy Problem for Interval Maps
On the topological conjugacy problem for interval maps Roberto Venegeroles1, ∗ 1Centro de Matem´atica, Computa¸c~aoe Cogni¸c~ao,UFABC, 09210-170, Santo Andr´e,SP, Brazil (Dated: November 6, 2018) We propose an inverse approach for dealing with interval maps based on the manner whereby their branches are related (folding property), instead of addressing the map equations as a whole. As a main result, we provide a symmetry-breaking framework for determining topological conjugacy of interval maps, a well-known open problem in ergodic theory. Implications thereof for the spectrum and eigenfunctions of the Perron-Frobenius operator are also discussed. PACS numbers: 05.45.Ac, 02.30.Tb, 02.30.Zz Introduction - From the ergodic point of view, a mea- there exists a homeomorphism ! such that sure describing a chaotic map T is rightly one that, after S ! = ! T: (2) iterate a randomly chosen initial point, the iterates will ◦ ◦ be distributed according to this measure almost surely. Of course, the problem refers to the task of finding !, if This means that such a measure µ, called invariant, is it exists, when T and S are given beforehand. −1 preserved under application of T , i.e., µ[T (A)] = µ(A) Fundamental aspects of chaotic dynamics are pre- for any measurable subset A of the phase space [1, 2]. served under conjugacy. A map is chaotic if is topo- Physical measures are absolutely continuous with respect logical transitive and has sensitive dependence on initial to the Lebesgue measure, i.e., dµ(x) = ρ(x)dx, being the conditions. Both properties are preserved under conju- invariant density ρ(x) an eigenfunction of the Perron- gacy, then T is chaotic if and only if S is also. -
Arxiv:2108.08461V1 [Math.DS] 19 Aug 2021 References 48
THE BOOTSTRAP FOR DYNAMICAL SYSTEMS KASUN FERNANDO AND NAN ZOU Abstract. Despite their deterministic nature, dynamical systems often exhibit seemingly random behaviour. Consequently, a dynamical system is usually represented by a probabilistic model of which the unknown parameters must be estimated using statistical methods. When measuring the uncertainty of such parameter estimation, the bootstrap stands out as a simple but powerful technique. In this paper, we develop the bootstrap for dynamical systems and establish not only its consistency but also its second-order efficiency via a novel continuous Edgeworth expansion for dynamical systems. This is the first time such continuous Edgeworth expansions have been studied. Moreover, we verify the theoretical results about the bootstrap using computer simulations. Contents 1. Introduction 1 2. Notation and Preliminaries5 I Continuous Edgeworth Expansions 7 3. Spectral Assumptions8 4. First-order Continuous Edgeworth Expansions 19 5. Examples 24 II The Bootstrap 33 6. The Bootstrap Algorithm 33 7. Asymptotic Accuracy of the Bootstrap 35 8. Application of the Bootstrap to our Examples 39 9. Computer Simulation of the Bootstrap 42 arXiv:2108.08461v1 [math.DS] 19 Aug 2021 References 48 1. Introduction After its establishment in late 19th century through the efforts of Poincar´e[64] and Lyapunov [49], the theory of dynamical systems was applied to study the qualitative behaviour of dynamical processes in the real world. For example, the theory of dynamical systems has proved useful in, 2010 Mathematics Subject Classification. 62F40, 37A50, 62M05. Key words and phrases. dynamical systems, the bootstrap, continuous Edgeworth expansions, expanding maps, Markov chains. 1 2 KASUN FERNANDO AND NAN ZOU among many others, astronomy [12], chemical engineering [3], biology [51], ecology [74], demography [81], economics [75], language processing [65], neural activity [71], and machine learning [9], [16]. -
Strong Chaos Without Butter Y E Ect in Dynamical Systems with Feedback
Strong Chaos without Buttery Eect in Dynamical Systems with Feedback 1 2 3 Guido Boetta Giovanni Paladin and Angelo Vulpiani 1 Istituto di Fisica Generale Universita di Torino Via PGiuria I Torino Italy 2 Dipartimento di Fisica Universita del lAquila Via Vetoio I Coppito LAquila Italy 3 Dipartimento di Fisica Universita di Roma La Sapienza Ple AMoro I Roma Italy ABSTRACT We discuss the predictability of a conservative system that drives a chaotic system with p ositive maximum Lyapunov exp onent such as the erratic motion of an asteroid 0 in the gravitational eld of two b o dies of much larger mass We consider the case where in absence of feedback restricted mo del the driving system is regular and completely predictable A small feedback of strength still allows a go o d forecasting in the driving system up to a very long time T where dep ends on the details of the system p The most interesting situation happ ens when the Lyapunov exp onent of the total system is strongly chaotic with practically indep endent of Therefore an exp onential tot 0 amplication of a small incertitude on the initial conditions in the driving system for any co exists with very long predictability times The paradox stems from saturation eects in the evolution for the growth of the incertitude as illustrated in a simple mo del of coupled maps and in a system of three p oint vortices in a disk PACS NUMBERS b It is commonly b elieved that a sensible dep endence on initial condition makes foreca sting imp ossible even in systems with few degrees -
Contents Ilorpy
From Deterministic Chaos to Anomalous Diffusion Dr. habil. Rainer Klages Queen Mary University of London School of Mathematical Sciences Mile End Road, London E1 4NS e-mail: [email protected] Contents 1 Introduction...................................... ........................ 2 2 Deterministic chaos................................ ....................... 3 2.1 Dynamicsofsimplemaps. .. .. 3 2.2 Ljapunovchaos .................................. 5 2.3 Entropies ..................................... 9 2.4 Opensystems, fractalsandescaperates. ....... 14 3 Deterministic diffusion............................. ....................... 19 3.1 What is deterministic diffusion? . ..... 20 3.2 Escape rate formalism for deterministic diffusion . ........... 22 3.2.1 Thediffusionequation . 22 arXiv:0804.3068v3 [nlin.CD] 20 Jul 2009 3.2.2 Basicideaoftheescaperateformalism . .... 24 3.2.3 The escape rate formalism worked out for a simple map . ...... 25 4 Anomalous diffusion................................. ..................... 29 4.1 Anomalous diffusion in intermittent maps . ...... 30 4.1.1 Whatisanomalousdiffusion? . 30 4.1.2 Continuoustimerandomwalktheory . 32 4.1.3 Afractionaldiffusionequation . 36 4.2 Anomalous diffusion of migrating biological cells . ........... 38 4.2.1 Cellmigration............................... 38 4.2.2 Experimentalresults . 39 4.2.3 Theoreticalmodeling . 41 5 Summary ........................................... ..................... 43 Bibliography....................................... ....................... 45 1 Introduction Over -
Frequently Asked Questions About Nonlinear Science J.D
Frequently Asked Questions about Nonlinear Science J.D. Meiss Sept 2003 [1] About Sci.nonlinear FAQ This is version 2.0 (Sept. 2003) of the Frequently Asked Questions document for the newsgroup s ci.nonlinear. This document can also be found in Html format from: http://amath.colorado.edu/faculty/jdm/faq.html Colorado, http://www-chaos.engr.utk.edu/faq.html Tennessee, http://www.fen.bris.ac.uk/engmaths/research/nonlinear/faq.html England, http://www.sci.usq.edu.au/mirror/sci.nonlinear.faq/faq.html Australia, http://www.faqs.org/faqs/sci/nonlinear-faq/ Hypertext FAQ Archive Or in other formats: http://amath.colorado.edu/pub/dynamics/papers/sci.nonlinearFAQ.pdf PDF Format, http://amath.colorado.edu/pub/dynamics/papers/sci.nonlinearFAQ.rtf RTF Format, http://amath.colorado.edu/pub/dynamics/papers/sci.nonlinearFAQ.tex old version in TeX, http://www.faqs.org/ftp/faqs/sci/nonlinear-faq the FAQ's site, text version ftp://rtfm.mit.edu/pub/usenet/news.answers/sci/nonlinear-faq text format. This FAQ is maintained by Jim Meiss [email protected]. Copyright (c) 1995-2003 by James D. Meiss, all rights reserved. This FAQ may be posted to any USENET newsgroup, on-line service, or BBS as long as it is posted in its entirety and includes this copyright statement. This FAQ may not be distributed for financial gain. This FAQ may not be in cluded in commercial collections or compilations without express permission from the author. [1.1] What's New? Fixed lots of broken and outdated links. A few sites seem to be gone, and some new sites appeare d.