Feigenbaum function

From HandWiki

In the study of dynamical systems the term Feigenbaum function has been used to describe two different functions introduced by the physicist Mitchell Feigenbaum:[1]

  • the solution to the Feigenbaum-Cvitanović functional equation; and
  • the scaling function that described the covers of the attractor of the logistic map

Feigenbaum-Cvitanović functional equation

This functional equation arises in the study of one-dimensional maps that, as a function of a parameter, go through a period-doubling cascade. Discovered by Mitchell Feigenbaum and Predrag Cvitanović,[2] the equation is the mathematical expression of the universality of period doubling. It specifies a function g and a parameter α by the relation

[math]\displaystyle{ g(x) = - \alpha g( g(-x/\alpha ) ) }[/math]

with the initial conditions[math]\displaystyle{ \begin{cases} g(0) = 1, \\ g'(0) = 0, \\ g''(0) \lt 0. \end{cases} }[/math]For a particular form of solution with a quadratic dependence of the solution near x = 0, α = 2.5029... is one of the Feigenbaum constants.

The power series of [math]\displaystyle{ g }[/math] is approximately[3][math]\displaystyle{ g(x) = 1 - 1.52763 x^2 + 0.104815 x^4 + 0.026705 x^6 + O(x^{8}) }[/math]

Renormalization

The Feigenbaum function can be derived by a renormalization argument.[4]

The Feigenbaum function satisfies[5][math]\displaystyle{ g(x)=\lim _{n \rightarrow \infty} \frac{1}{F^{\left(2^n\right)}(0)} F^{\left(2^n\right)}\left(x F^{\left(2^n\right)}(0)\right) }[/math]for any map on the real line [math]\displaystyle{ F }[/math] at the onset of chaos.

Scaling function

The Feigenbaum scaling function provides a complete description of the attractor of the logistic map at the end of the period-doubling cascade. The attractor is a Cantor set, and just as the middle-third Cantor set, it can be covered by a finite set of segments, all bigger than a minimal size dn. For a fixed dn the set of segments forms a cover Δn of the attractor. The ratio of segments from two consecutive covers, Δn and Δn+1 can be arranged to approximate a function σ, the Feigenbaum scaling function.

See also

Notes

Bibliography