Help with a proof with discrete dynamical sysmtes / chaos theory.

In summary: Could you please explain it in more detail? Also, I believe there may be a typo in part 3, as the 2-cycle should be q1λ and q2λ, not qλ1 and qλ2. Other than that, everything seems to be correct so far. Keep up the good work!
  • #1
goosefrabbas
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Homework Statement


Consider the families of iterating functions Fλ(x) = λ(x3 - x). Fλ(x) undergoes a bifurcation at λ=1, about the fixed point x=0. Figure out what ilk of bifurcation is occurring for Fλ(x) and prove your assertion rigorously.

Homework Equations


My book says this about period-doubling bifurcations, and I need to prove all four of these to prove the problem.
Definition: A one-parameter family of functions Fλ undergoes a period-doubling bifurcation at the parameter value λ=λ0 if there is an open interval and an ε such that:
1. For each λ in the interval [λ0 - ε, λ0 + ε], there is a unique fixed point pλ for Fλ in I.
2.For λ0 - ε < λ < λ0, Fλ has no cycles of period 2 in I and pλ is attracting (resp. repelling).
3.For λ0 < λ < λ0 + ε, there is a unique 2-cycle q1λ,q2λ in I with Fλ(q1λ)=q2λ. This 2-cycle is attracting (resp. repelling). Meanwhile, the fixed point pλ is repelling (resp. attracting).
4.As λ -> λ0, we have qiλ -> pλ0
Also, these theorems are necessary (I think).
Chain Rule Along A Cycle: Suppose x0, x2, ..., xn-1 lie on a cycle of period n for F with xi = Fi(x0). Then
(Fn)'(x0) = F'(xn-1) * ... * F'(x1) * F'(x0).
The corollary for this is:
Suppose x0, x1, ..., xn-1 lie on an n-cycle for F. Then
(Fn)'(x0) = (Fn)'(x1) = ... = (Fn)'(xn-1)

The Attempt at a Solution

\
I have almost no idea where to start the proof. So far I have:
The interval I can = (-1, 1).

To answer 1., I know that there are fixed points at 0, +sqrt(2), -sqrt(2). So to have a unique fixed point pλ in the interval [λ0 - ε, λ0 + ε], 0<ε<sqrt(2). Can I just choose an arbitrary ε, like ε=1?

To answer 2., if ε=1, λ0 - ε < λ < λ0, so 0 - 1 < λ < 0, so -1<λ<0. I used algebra and got 2-cycles for x = -1, -.7548777, 0, 1 1.4655712, but all but x=1.4655712 lie in the interval I. Could someone check this? I may have made a mistake in my algebra. I don't see why else I would get this.

I really appreciate the help!
 
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  • #2
I changed my interval I to (-.5, .5) so that part 2 would work.

And for part 3, I got this far.
Fλ(x)=λ(x3-x) is an odd function, so the second iteration of Fλ(x0) = x0. Using algebra I got x = (1 +- sqrt(1 - 4λ))/(2λ), so this is the 2-cycle for Fλ, but only for 0<λ<1/4.

For part 4, As λ -> λ0, we have qiλ -> pλ0. So substituting, I get as λ -> 0, qiλ -> 0.

Is everything right so far?
I'm not sure how to prove part 4.
 

What is a discrete dynamical system?

A discrete dynamical system is a mathematical model that describes the evolution of a system over a sequence of discrete time steps. It involves a set of rules or equations that map the state of the system at one time step to the next time step.

What is chaos theory?

Chaos theory is a branch of mathematics that studies the behavior of dynamical systems that are highly sensitive to initial conditions. It explores the unpredictable and irregular behavior that can arise from simple, deterministic rules.

How are discrete dynamical systems and chaos theory related?

Discrete dynamical systems can exhibit chaotic behavior, meaning that small changes in initial conditions can lead to drastically different outcomes over time. Chaos theory provides tools and concepts to study and understand this behavior in discrete dynamical systems.

What is a proof in the context of discrete dynamical systems and chaos theory?

A proof is a logical and rigorous demonstration that a certain statement or conjecture is always true for a given set of assumptions. In the context of discrete dynamical systems and chaos theory, a proof can establish the existence or properties of chaotic behavior, or provide insights into the dynamics of a specific system.

What are some real-world applications of discrete dynamical systems and chaos theory?

Discrete dynamical systems and chaos theory have applications in various fields, including physics, biology, economics, and engineering. They can be used to model complex systems and phenomena, such as weather patterns, population dynamics, stock market fluctuations, and chemical reactions.

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