Why is the sum of Lyapunov exponents negative in dissipative systems?

In summary, the discussion in this forum is helpful for solving questions, but there is confusion about the significance of the sum of Lyapunov exponents in a dynamical system. It is often said that for a chaotic system, the sum of the exponents is positive and for a dissipative system it is negative. However, this is not equivalent to the overall exponent for the trajectory through phase space. The maximum Lyapunov exponent must be positive and the system must have positive topological entropy. The sum of positive Lyapunov exponents is related to Kolomogorov-Sinai entropy by Pesin's formula.
  • #1
waofy
4
0
Hi, the discussions in this forum have always been a great help to me as it seems there's always someone who's answered my question. However, this time I'm still puzzled.

People often talk about the sum of the Lyapunov exponents of a dynamical system (i.e. adding the exponents from each dimension in phase space) giving an indication of the overall behaviour of the system. For example, it is said that for a chaotic system the sum of the Lyapunov exponents is positive and for a dissipative system it is negative.

However, this doesn't make sense as the sum of the exponents is not the same as the exponent for the net trajectory through phase space.

e.g. in the case of a 3-dimensional phase space (x,y,z) with the system trajectory \begin{equation}
{\bf r}(t)=[x(t),y(t),z(t)]
\end{equation}
the separation between two trajectories is given by:
\begin{equation}
|\delta{\bf r}(t)|=e^{\lambda(t-t_{o})}|\delta{\bf r}(t_{o})|
\end{equation}
where lambda is the Lyapunov exponent of the trajectory. Now considering each dimension separately,
\begin{equation}
|\delta{\bf r}(t)|=|[\delta{x}(t),\delta{y}(t),\delta{z}(t)]|=|[e^{\lambda_{x}(t-t_{o})}\delta x(t_{o}),e^{\lambda_{y}(t-t_{o})}\delta y(t_{o}),e^{\lambda_{z}(t-t_{o})}\delta z(t_{o})]|=\sqrt{e^{2\lambda_{x}(t-t_{o})}\delta x(t_{o})^{2}+e^{2\lambda_{y}(t-t_{o})}\delta y(t_{o})^{2}+e^{2\lambda_{z}(t-t_{o})}\delta z(t_{o})^{2}}
\end{equation}(1)

where the lambdas are the exponent for each dimension. However, if the exponent of the trajectory was equal to the sum of exponents from each dimension,
\begin{equation}
|\delta{\bf r}(t)|=e^{(\lambda_{x}+\lambda_{y}+\lambda_{z})(t-t_{o})}|\delta{\bf r}(t_{o})|=e^{(\lambda_{x}+\lambda_{y}+\lambda_{z})(t-t_{o})}|[\delta x(t_{o}),\delta y(t_{o}),\delta z(t_{o})]|=e^{(\lambda_{x}+\lambda_{y}+\lambda_{z})(t-t_{o})}\sqrt{\delta x(t_{o})^{2}+\delta y(t_{o})^{2}+\delta z(t_{o})^{2}}
\end{equation}(2)

Clearly (1)=/=(2).

Am I missing something here? The only thing I can think of is that I haven't understood the meaning of the Lyapunov spectrum correctly. I've always assumed each exponent represents the the behaviour of trajectories moving in a single dimension but I could be wrong?
 
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  • #2
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  • #3
atyy said:
It's the maximum Lyapunov exponent that has to be positive, not the sum.

In addition, the system must have positive topological entropy. http://chaosbook.org/ (section 1.3.1).

The sum of the positive Lyapunov exponents is related to Kolomogorov-Sinai entropy by Pesin's formula http://www.scholarpedia.org/article/Pesin_entropy_formula.


Thanks, that makes more sense.

I think it is still true that in dissipative systems the sum of the Lyapunov exponents is negative though (http://books.google.co.uk/books?id=Uqc7zC7NULMC&pg=PA212&lpg=PA212#v=onepage&q&f=false" - first line). It makes sense that the overall exponent for the trajectory would be negative (which would also be true for a stable limit cycle) but I can't quite see why the sum should be. I'm just trying to work out what significance the sum has.
 
Last edited by a moderator:

What is the "Sum of Lyapunov exponents"?

The Sum of Lyapunov exponents is a mathematical concept used to measure the rate of change of a dynamical system. It is a sum of all the Lyapunov exponents, which are used to quantify the stability of a system.

Why is the "Sum of Lyapunov exponents" important?

The Sum of Lyapunov exponents is important because it allows us to predict the behavior of complex systems. By measuring the rate of change, we can determine whether a system is stable or chaotic, and make predictions about its future behavior.

How is the "Sum of Lyapunov exponents" calculated?

The Sum of Lyapunov exponents is calculated by taking the sum of all the Lyapunov exponents, which are found by solving a set of differential equations. These equations describe the behavior of the system over time, and the Lyapunov exponents represent the average rate of change of the system at a specific point in time.

What is the significance of a positive or negative "Sum of Lyapunov exponents"?

A positive Sum of Lyapunov exponents indicates that the system is chaotic, meaning that small changes in initial conditions can lead to drastically different outcomes. A negative Sum of Lyapunov exponents indicates that the system is stable, meaning that small changes in initial conditions will not significantly alter the system's behavior.

How is the "Sum of Lyapunov exponents" used in real-world applications?

The Sum of Lyapunov exponents has applications in various fields, including physics, biology, economics, and engineering. It can be used to predict the behavior of complex systems, such as weather patterns, stock market fluctuations, and biological systems. It is also used in control theory to design stable systems and in cryptography to generate secure codes.

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