Chaos like phenomena on a simple metric space?

In summary, the conversation discusses the concept of a metric space with no isolated points and a continuous function that separates points in the space. A concrete example is given to demonstrate this concept and the conversation shifts to finding a generalization or counterexample for the concept. The conversation ends with the mention of potential applications of the result.
  • #1
Zafa Pi
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Let M = {p, x1, x2, x3, ...} be a metric space with no isolated points.
f: M → M is continuous with f(xn) = xn+1, and f(p) = p.
We say f separates if ∃ δ > 0, ∋ for any y and z there is some n with |fn(y) - fn(z)| > δ, where fn+1(y) = f(fn(y)).
QUESTION: Does f separate?
 
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  • #2
I find it very hard to think about abstract problems like this without a concrete example.

Here's a concrete example I thought of:

Let M be a subspace of the unit circle ##S^1## in ##\mathbb R^2##, with the metric inherited from ##\mathbb R^2##. Since all points in M have radius 1 we can fully specify a point by its polar angle ##\theta##. We set the angles as ##\theta_p=0,\theta_1=1,\theta_{n+1}=2\theta_n##. Note that under this specification two points are identical if their angles differ by a multiple of ##2\pi##, so we deduct whatever multiple of ##2\pi## is necessary to ensure that a point's angle lies in the range ##[0,2\pi)##.

I am pretty confident that with this definition M is dense in the unit circle ##S^1## so that there are no isolated points, and that the map ##f## that doubles the angle of a point is continuous. So this space satisfies the premises of the problem.

I claim that this space separates. For a small ##\delta##, eg say ##\delta=0.01##, given any ##y,z\in M## we can find ##n## such that ##|f^n(y)-f^n(z)>\delta##. I have not proven this but I can see a way one would go about doing so.

Have a go at seeing if you can prove that this space and the function ##f## satisfy the premises and that ##f## separates.

Assuming that works, the next step would be to see if we can generalise that result to all space-function combinations that satisfy the premises or, alternatively, whether we can find a counterexample - a space and function that satisfy the premises but the function does not separate.
 
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  • #3
andrewkirk said:
We set the angles as θp=0,θ1=1,θn+1=2θnθp=0,θ1=1,θn+1=2θn\theta_p=0,\theta_1=1,\theta_{n+1}=2\theta_n.
I agree with what you say about this space and function. However, the same is true if 0 is eliminated, i.e. you don't need the fixed point.
Again, if we are on the circle group and this time θ1 = 1, θn+1 = θn + 1, we get density, f is continuous, no fixed point, and no separation.

There are many examples where the result is true (everyone I've tried), but I've been unable to show it is always true. I have spent a lot of time trying.
I think the result would have cool applications.
 

1. What is chaos on a simple metric space?

Chaos on a simple metric space refers to the unpredictable and irregular behavior of a system that is governed by simple rules or equations. It is characterized by sensitive dependence on initial conditions, meaning that small changes in the starting conditions can lead to vastly different outcomes.

2. How is chaos different from randomness?

While chaos may appear random, it is actually a deterministic process. This means that the behavior of a chaotic system is governed by fixed rules or equations, whereas randomness has no underlying pattern or rules.

3. Can chaos be found in natural systems?

Yes, chaos can be found in many natural systems, such as weather patterns, population dynamics, and even the movement of planets and stars. In fact, chaos is a fundamental aspect of complex systems and can be seen as a driving force behind their behavior.

4. How is chaos studied in mathematics and science?

Chaos is studied through mathematical models and simulations, as well as through observations of real-world systems. Scientists use tools such as phase space diagrams, Lyapunov exponents, and bifurcation diagrams to analyze and understand chaotic systems.

5. Can chaos be controlled or predicted?

While chaos is inherently unpredictable, there are certain techniques that can be used to control or manipulate chaotic systems. These include controlling the initial conditions, identifying and exploiting patterns in the chaos, and using feedback mechanisms. However, predicting the exact behavior of a chaotic system is still a challenge and is subject to the limitations of our current understanding and technology.

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