chaos - definition and classificationww2.odu.edu/~skuhn/phys603/coxe_chaos_abbrev.pdf ·...
TRANSCRIPT
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ChaosDefinition and Classification
Alexander Coxe
Physics 603; Classical MechanicsOld Dominion University
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Contents
Terminology
Defining ChaosSensitive DependenceTopological TransitivityDense Periodic Orbits
ClassificationEquilibriaLyapunov Numbers and Exponents
References
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Terminology
• Map: a single valued f (x) : F→ F on some set F.
• Iteration: application of a map eg f (3)(x) = f (f (f (x))).
• Orbit: S(x) = {x , x1, x2, · · · } = {x , f (x), f (f (x), · · · }.• Fixed point: x0 =⇒ f (x0) = x0.
• Periodic orbit: an orbit with f (n)(xp) = xp for n ≥ 0.
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Terminology
• Map: a single valued f (x) : F→ F on some set F.
• Iteration: application of a map eg f (3)(x) = f (f (f (x))).
• Orbit: S(x) = {x , x1, x2, · · · } = {x , f (x), f (f (x), · · · }.• Fixed point: x0 =⇒ f (x0) = x0.
• Periodic orbit: an orbit with f (n)(xp) = xp for n ≥ 0.
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Terminology
• Map: a single valued f (x) : F→ F on some set F.
• Iteration: application of a map eg f (3)(x) = f (f (f (x))).
• Orbit: S(x) = {x , x1, x2, · · · } = {x , f (x), f (f (x), · · · }.
• Fixed point: x0 =⇒ f (x0) = x0.
• Periodic orbit: an orbit with f (n)(xp) = xp for n ≥ 0.
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Terminology
• Map: a single valued f (x) : F→ F on some set F.
• Iteration: application of a map eg f (3)(x) = f (f (f (x))).
• Orbit: S(x) = {x , x1, x2, · · · } = {x , f (x), f (f (x), · · · }.• Fixed point: x0 =⇒ f (x0) = x0.
• Periodic orbit: an orbit with f (n)(xp) = xp for n ≥ 0.
![Page 7: Chaos - Definition and Classificationww2.odu.edu/~skuhn/PHYS603/Coxe_Chaos_abbrev.pdf · 2020-03-23 · Contents Terminology De ning Chaos Sensitive Dependence Topological Transitivity](https://reader034.vdocument.in/reader034/viewer/2022050406/5f838abe02339e02ca3590e1/html5/thumbnails/7.jpg)
Terminology
• Map: a single valued f (x) : F→ F on some set F.
• Iteration: application of a map eg f (3)(x) = f (f (f (x))).
• Orbit: S(x) = {x , x1, x2, · · · } = {x , f (x), f (f (x), · · · }.• Fixed point: x0 =⇒ f (x0) = x0.
• Periodic orbit: an orbit with f (n)(xp) = xp for n ≥ 0.
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Definition
A map is deemed “chaotic” if it has the following properties:
• Sensitive dependence on initial conditions,
• Topological transitivity,
• Dense periodic orbits.
Similarly, a chaotic orbit is not periodic, stationary, ordivergent.
Chaos is a property of orbits typical of systems with nonlineardynamics.
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Definition
A map is deemed “chaotic” if it has the following properties:
• Sensitive dependence on initial conditions,
• Topological transitivity,
• Dense periodic orbits.
Similarly, a chaotic orbit is not periodic, stationary, ordivergent.
Chaos is a property of orbits typical of systems with nonlineardynamics.
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Definition
A map is deemed “chaotic” if it has the following properties:
• Sensitive dependence on initial conditions,
• Topological transitivity,
• Dense periodic orbits.
Similarly, a chaotic orbit is not periodic, stationary, ordivergent.
Chaos is a property of orbits typical of systems with nonlineardynamics.
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Definition
A map is deemed “chaotic” if it has the following properties:
• Sensitive dependence on initial conditions,
• Topological transitivity,
• Dense periodic orbits.
Similarly, a chaotic orbit is not periodic, stationary, ordivergent.
Chaos is a property of orbits typical of systems with nonlineardynamics.
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Sensitive DependenceDefinition
For any orbit of any map sensitive dependence on initial conditionsmeans that for |x1 − x2| < ε for ε as small as we like,|f (n)(x1)− f (n)(x2)| > δ for any δ > 0 we choose.
In the words of Edward Lorenz, “Chaos: When the presentdetermines the future, but the approximate present does notapproximately determine the future.”
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Sensitive DependenceExample
A very simple example of a map with sensitive dependence oninitial conditions is a doubling map: f (x) = 2x .
Figure 1: Double Steps
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Topological TransitivityDefinition
A map is topologically transitive if for any two nonempty sets Aand B, there is some integer n such that f (n)(A) ∩ B 6= 0.In other words, any value plugged into a topologically transitivemap may produce any other value (at all) if the map is iteratedenough times.
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Topological TransitivityExample
The logistic map xn+1 = rxn(1− xn):
Figure 2: Logistic Map
This is a bifurcation plot. 0 < r < 4 is on the horizontal axis, and0 < x < 1 is on the vertical axis. For 0 < r <∼ 3 there is only afixed point, but for ∼ 3 < r <∼ 3.5 there is a period 2 orbit.
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Dense Periodic OrbitsDefinition
Density of periodic orbits means that no matter what startingvalue is chosen (x , for f (n)(x)), the distance between x and apoint on some periodic orbit is arbitrarily small: that is for anyε > 0, |x − xR | < ε for some xR .
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ClassificationEquilibria: Stability
The stability of any orbit S of a map f is determined by thefirst derivative of the map over the orbit. That is to say
• if (f (n))′(x1) < 1 then S(x1) = f (n)(x1) is an attractive orbit:
• if (f (n))′(x1) > 1 then S(x1) = f (n)(x1) is a source.
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ClassificationEquilibria: Stability
The stability of any orbit S of a map f is determined by thefirst derivative of the map over the orbit. That is to say
• if (f (n))′(x1) < 1 then S(x1) = f (n)(x1) is an attractive orbit:
• if (f (n))′(x1) > 1 then S(x1) = f (n)(x1) is a source.
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ClassificationEquilibria: Stability
The stability of any orbit S of a map f is determined by thefirst derivative of the map over the orbit. That is to say
• if (f (n))′(x1) < 1 then S(x1) = f (n)(x1) is an attractive orbit:
• if (f (n))′(x1) > 1 then S(x1) = f (n)(x1) is a source.
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ClassificationLorenz Attractor
Figure 3: Lorenz Attractor
The Lorenz attractor is a chaotic orbit with (f (n))′(x) < 1.
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ClassificationLyapunov Numbers and Exponents
Lyapunov numbers and exponents are a measure of the stability ofan orbit. The Lyapunov exponent λ = ln L where L is theLyapunov number.
For any point on any orbit {x1, x2, x3, · · · }, the Lyapunov numberis given by:
L(x1) = limn→∞
(|f ′(x1)| · · · |f ′(xn)|)1/n.
So the Lyapunov Exponent is:
λ(x1) = limn→∞
1
nln(|f ′(x1)| · · · |f ′(xn)|)
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References
For this slide show I referenced:
1. Goldstein, H., and Poole, C.P., and Safko, J.:Classical Mechanics,3rd ed. Pearson 2011
2. Alligood, K.T., and Sauer, T.D., and Yorke, J.A.:Chaos - An Introduction to Dynamical SystemsSpringer 1996
Figure 2: https://www.researchgate.net/publication/
306226253_Visual_Analysis_of_Nonlinear_Dynamical_
Systems_Chaos_Fractals_Self-Similarity_and_the_
Limits_of_Prediction/figures?lo=1
Figure 3: https://matplotlib.org/3.1.0/gallery/
mplot3d/lorenz_attractor.html