Can Chaos Theory Truly Render Future Systems Unpredictable?

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Discussion Overview

The discussion revolves around Chaos Theory, specifically addressing the predictability of future systems based on initial variables. Participants explore the implications of chaotic behavior in various systems, including mathematical models and real-world applications, while seeking clarification on the nature of chaos and its defining characteristics.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant questions whether the future of a system is unpredictable if the initial variables exceed a certain finite number, seeking further elaboration on this premise.
  • Another participant argues that chaos is more about sensitivity to initial conditions rather than the number of input variables, highlighting that small changes can lead to significant unpredictable outcomes.
  • A third participant references the logistic difference equation as an example where chaos can emerge based on specific variable thresholds, while noting the ambiguity in the original statement about variables.
  • Further contributions emphasize that chaos involves sensitive dependence on initial conditions and the exponential growth of separation between nearby variables over time, illustrated by the butterfly effect.
  • Some participants clarify that chaos cannot be solely defined by the butterfly effect and present various definitions of chaos that highlight its complex nature and refusal to stabilize.
  • One participant suggests that while chaotic systems can exhibit predictability for a limited time, the accuracy of predictions diminishes exponentially, as seen in weather forecasting.
  • Another viewpoint introduces the idea that chaos theory is based on the observation of chain reactions but may overlook the tendency of larger systems to absorb disturbances.

Areas of Agreement / Disagreement

Participants express differing views on the relationship between the number of variables and chaos, with some agreeing that chaos is linked to sensitivity to initial conditions rather than the number of variables. The discussion remains unresolved regarding the precise definitions and implications of chaos theory.

Contextual Notes

Participants note that chaos is not a type of system but rather a description of a state, and there are limitations in understanding how chaotic behavior can emerge from specific conditions or thresholds. The discussion also highlights the complexity of defining chaos and its manifestations in different systems.

ion
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I am not too sure where to post this,and so have decided on the general category.
My question is on the Chaos theory. A very basic question as I have only recently come across this subject. Am I right in assuming that:

The future of a system is not predictable if the initial variables(that determine an event) exceed a certain finite number.

If this is true could someone please enlarge on the matter.If it is wrong please educate me. I am quite green on this subject.

Thank you.
 
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Typical examples of chaos are not concerned particularly with the size of the input variables. Rather, a chaotic process is typically one in which a small change in input results in a very large, usually unpredictable change in output.
 
Originally posted by ion
The future of a system is not predictable if the initial variables(that determine an event) exceed a certain finite number.
I am also green, being only about a third of the way into James Gleicks Chaos but your statement may be correct in certain instances of Chaos. He gives the example of the "logistic difference equation" used by ecologists, xnext=rx[1-x], which works well so long as the variable r (rate of population growth) has a relatively low value. Above a certain value r the formula refuses to arrive at an equilibrium.
x = population
r = rate of growth
xnext = next years populationThe chaos exhibited by fluid flow, to cite another example, seems only to come into play when one of the variables: speed of flow, exceed a certain rate, after which the fluid begins to behave "chaotically".

However, your statement is somewhat ambiguous and what I said may be off the mark if I misunderstood what you meant.

If you meant that some formulas and dynamic systems become chaotic when the value of a specific, important variable exceeds a certain threshold, then it would be true. If you meant that a formula yields chaotic results when the number of variables in the formula exceeds a certain number, then I wouldn't think so.

-Zooby
 
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It's not the number of variables that deterimes chos, but the sensitivity to initial conditions. Specifically if the rate of separation of nearby varianles grows exponentially as a function of the time and their intitial separation. This is the point of the butterfly's wing story. The tiny puff of the wing's effect on the atmosphere can grow exponentially and become huge after a while.
 
Noticing, and paying attention to, the butterfly effect was the first step in the science of Chaos, but all Chaos can, by no means, be boiled down to the butterfly effect. That would be akin to explaining Relativity as the photoelectric effect.

On page 306 of Gleick's Chaos he lists a few attempts at a definition of the new science by some of the men involved in it:

"The complicated, aperiodic, attracting orbits of certain (usually low-dimensional) dynamical systems."

"A kind of order without periodicity."

"Apparently random recurrent behavior in a simple deterministic (clockwork-like) system."

"The irregular, unpredictable behavior of deterministic, nonlinear dynamical systems."

"The translation from mathese is: behavior that produces information (amplifies small uncertainties), but is not utterly unpredictable."

What makes a system chaotic is not its sensitive dependence on initial conditions (when that is the case, which it isn't for all chaotic systems), but its refusal to settle down and stabilize. Chaotic systems are dynamic, yet they won't repeat. Not only that, they are sometimes subject to complete, unexpected reversals.
 
The future of a system is not predictable if the initial variables(that determine an event) exceed a certain finite number.
It is true that most chaotic systems are not always chaotic, and that they frequently show a gradual approach to chaos based on several bifurcations determined by the Feigenbaum constant. So I guess you are pretty right, but that is not the definition of chaos itself. Chaos is really not a type of system, but a description of a state of a system.

And chaos can be predicted to a reasonable degree of accuracy, for a while. We still have weather forecasts, don't we? However, our error increases exponentially with time.
 
It is a theory developed on the observation of how easily a chain reaction can occurr, yet ignores the tendency of the vastness of the world to "absorb."
 

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