Variational Equations, Chaos Indicators

In summary, the author is investigating how to compute a fast lyapunov indicator for chaotic orbits in a system, and is unsure of whether it is necessary to use a higher order variational equation or just two trajectories subtracted.
  • #1
dreens
40
11
I work with an electromagnetic molecule trap, and I'd like to determine which orbits are chaotic. To this end, I intend to study the evolution of a perturbation on a trajectory with time.

I'd like to compute something called the fast lyapunov indicator for various trajectories y(t), where I have a force law y''(t)=f(y).

I'm told I need to consider a variation dy, and follow its evolution d(dy)/dt = df(y)/dy * dy.

My questions are:
1. how do I deal with the fact that I have a second order equation not first.
2. Could I just evolve two trajectories separated by dy initially in order to evolve dy, or is this much less precise than evolving dy according to its specific higher order evolution equation?
 
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  • #2
By the way, I've heard that chaotic orbits only exist in a conservative system like mine when they can escape eventually. Can anyone confirm this or point me to a reference? I think I read it in this article, they say something about Arnold's webs and KAM tori but I couldn't follow it.
 
  • #3
Dynamical chaos is a very large set of very different effects that express a complicated behavior of the trajectories. Chaos in Hamiltonian systems is not the same as chaos in general systems; chaos in infinite dimensional systems is not the same as in finite dimensional ones. In each concrete system or concrete class of systems one should specify what one means when he says "chaos". One must formulate a mathematical definition of chaos basing on physical phenomena which one sees. It does not make sense to use the term "chaos" before this
 
  • #4
I mean variation of initial conditions, and my definition of chaos is that dy increases exponentially with time. For conservative hamiltonian systems people often adopt less strict definitions, such as linear increase of dy with time, but I'd rather leave that out for now.
 
  • #5
ok. trajectories of a system ##\dot x=x## diverge exponentially. Thus it is a chaotic system in accordance to your definition.
Studying of the dynamical chaos requires for professional mathematical background
 
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  • #6
I'm interested in systems that support stable orbits, for example traps, unlike the anti trap force example you've brought up. I don't think I need to be a professional mathematician in order to use chaos indicators to learn about orbits in my trap. I can follow the work of other professionals, who have established lyapunov based indicators as a useful tool for quantifying the chaos present in a system.

My question pertains to the details of computation of these indicators. In particular whether it is sufficient to calculate two different trajectories and subtract them to get the evolution of the variational vector, or whether evolving the variational vector on its own with a higher order equation is essential.
 
  • #7
I'm answering my own questions just in case someone else comes across this.

1. Always treat the dynamical system as a first order one when taking derivatives of the flow function f (where y' = f(t,y) ).

2. It may not be absolutely necessary to use the higher order variational equations compared with say a trajectory subtraction technique, but the former provides much higher numerical precision for the same tolerances, and worked well for my application.
 

1. What are variational equations?

Variational equations are a set of mathematical equations used to describe the behavior of a system over time. These equations are derived from the original equations of motion and are used to study the sensitivity of the system to initial conditions.

2. How do variational equations relate to chaos?

Variational equations play a crucial role in the study of chaos in dynamical systems. They help to identify the sensitive dependence on initial conditions that is a defining characteristic of chaotic systems.

3. What are chaos indicators?

Chaos indicators are numerical quantities that are used to measure the degree of chaos in a system. These can include Lyapunov exponents, correlation dimensions, and other measures of sensitivity to initial conditions.

4. How are chaos indicators used in practice?

Chaos indicators are used to quantify the degree of chaos in a system and to identify the presence of chaotic behavior. They can also be used to predict the long-term behavior of a system and to detect patterns or structures within chaotic systems.

5. What are some real-world applications of variational equations and chaos indicators?

Variational equations and chaos indicators have many practical applications, including weather forecasting, stock market analysis, and the study of biological systems. They are also used in engineering to analyze the stability and predictability of complex systems.

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