Is it possible to define a universal formula for chaos?

Question

I've been working on a chaos project. I have noticed that there are several formulas to find the behavior of chaos, for example:

The logistic map is a simple equation that exhibits chaotic behavior when certain parameters are adjusted: $$x_{n+1} = rx_n(1-x_n)$$ where

• $x_n$: Value at iteration $n$
• $r$: Growth parameter (when $r\gt 3.57$, the system becomes chaotic)

Lyapunov's exponent measures sensitivity to initial conditions, which is a key characteristic of chaos. A positive Lyapunov exponent indicates chaotic behavior. $$\lambda=\lim_{t\to\infty}\frac{1}{t}\ln\frac{d(t)}{d(0)}$$ where

• $\lambda$: Lyapunov exponent
• $d(t)$: Separation between two nearby trajectories at time $t$.
• $d(0)$: Initial separation between the trajectories.

And there are more formulae such as

Kolmogorov-Sinai entropy (KS): Used to quantify the amount of information generated by a dynamical system. A positive KS entropy indicates the presence of chaos.

Fractals and Fractal Dimension (Hausdorff dimension): Chaotic systems usually have fractal structures, which can be measured using the fractal dimension.

Lorenz equation: This system of equations describes the behavior of the climate and is one of the first examples of chaos in a physical system.

My question is the following: Is there a single formula that can measure chaos in any type of system? Or, does chaos always depend on the context of the system in which it is studied?

Excuse me if there is a mistake in the texts, it is that I had to convert it from Spanish to English.

Answer 1

There is no single formula that can measure chaos in any type of system, as chaos is a phenomenon that depends on the specific context of the system in question. Each of the concepts you mentioned—such as the logistic map, the Lyapunov exponent, the Kolmogorov-Sinai entropy, and the Lorenz equations—applies to different types of systems and provides information about their chaotic behavior from different perspectives.

For example, Lyapunov's exponent measures sensitivity to initial conditions, which is fundamental in dynamical systems. On the other hand, the Kolmogorov-Sinai entropy quantifies the information generated by the system and may be more appropriate for certain contexts. Fractals, on the other hand, describe the geometry of certain chaotic systems and are useful in the visual and quantitative analysis of patterns.

Answer 2

So let's try to clarify things:

1. Chaos is a type of behavior, and there is an infinity number of models (typically described by equations) that exhibit this behavior. So in this sense there couldn't be "an universal formula", because these systems are different and described by different equations.
2. Among these models are the logistic map and the Lorenz system. They are simply two prominent examples of chaotic systems.
3. Fractals are geometrical objects, just like squares or paraboloids. Some structures in the phase space of systems that exhibit chaos often have fractal dimensions.
4. For detecting or characterizing chaos, Lyapunov exponents are indeed a very important measure. For some other ones you may check, e.g., Is it possible to quantify how chaotic a system is?.