Are Chaotic and Stochastic processes related?

In summary: A deterministic dynamical system is one in which all its states are known in advance. A stochastic dynamical system is one in which some of its states are not known in advance.A deterministic dynamical system can be chaotic if its limit state is fractal.
  • #1
JorgeM
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Hello everyone.
I have read on the web some people that mention something about "stochastic chaos" but I am not that sure about what it really means or if that actually exists. Two months ago , I started to study some chaotic systems but in stochastic systems I am not that familiarized in order to figure out how may be this two math areas related.
If someone could tell me ( or to explain) if both are related somehow or if that is actually impossible, I would be grateful.
Thanks for reading my post.
Mtze
 
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  • #2
There is a lot to say about this, but this has been done better in the literature, so I will be brief.

A purely deterministic dynamical system - for example, a map from a complete metric space to itself, or a (semi)flow defined on a metric space - can display chaotic behavior in a well-defined sense.

One way to understand this behavior, is by studying the associated Frobenius-Perron and Koopman operators (physicists sometimes speak of "transfer operators") or more generally Markov operators that act on a space of (usually absolutely continuous) measures. For this perspective, the book by Lasota and Mackey, Chaos, Fractals and Noise is highly recommended as an introduction to "applied" ergodic theory. (Do not let the catchy title fool you.)

Of course, it is possible to start with a deterministic system and introduce a co-dependence on some discrete or continuous time stochastic process to obtain a stochastic dynamical system. The associated operator on a space of measures is called the Foias operator.

My recommendation would be to first understand stochasticity of purely deterministic dynamical systems by studying the associated measure or density dynamics along the above lines, and only then move forward to include stochasticity at the level of the original deterministic dynamical system.
 
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  • #3
Thanks for your reply, I will try to start with the purely deterministic one, and I am going to read the books you menctioned. Thanks a lot for your advise!
 
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  • #4
As I understand it a chaotic system is a dynamical system in which the limit state is fractal, i.e., of non-integer Hausdorff dimension. A Stochastic process is just a random process, i.e., described by a Random variable.
 
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1. What is the difference between chaotic and stochastic processes?

Chaotic processes are deterministic and follow a specific set of rules, but are highly sensitive to initial conditions, making them unpredictable in the long term. Stochastic processes, on the other hand, involve random elements and are inherently unpredictable.

2. Can a chaotic process also be stochastic?

Yes, a chaotic process can also have stochastic elements. For example, weather patterns are chaotic due to the sensitivity to initial conditions, but there are also random factors such as wind patterns and temperature fluctuations that make it a stochastic process.

3. How are chaotic and stochastic processes related?

Chaotic and stochastic processes are related in that they both involve elements of unpredictability. However, they differ in the underlying causes of this unpredictability. Chaotic processes are driven by sensitivity to initial conditions, while stochastic processes are driven by random elements.

4. What are some real-world examples of chaotic and stochastic processes?

Examples of chaotic processes include the stock market, population growth, and weather patterns. Stochastic processes can be seen in radioactive decay, Brownian motion, and gambling games.

5. Can chaotic or stochastic processes be controlled or predicted?

It is difficult to control or predict chaotic processes due to their sensitivity to initial conditions. However, it is possible to make probabilistic predictions about the behavior of stochastic processes based on statistical analysis and modeling.

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