Math 2.0

Dynamical systems and ergodic theory Definition

Ergodic transformation

Builds on Probability spaceMeasure-preserving transformation

Definition

Let (X,𝒜,μ)(X, \mathcal{A}, \mu) be a probability space, and let T ⁣:X→XT \colon X \to X be a measure-preserving transformation. A set A∈𝒜A \in \mathcal{A} is TT-invariant if T−1(A)=AT^{-1}(A) = A. The map TT is ergodic if every TT-invariant set A∈𝒜A \in \mathcal{A} satisfies μ(A)=0\mu(A) = 0 or μ(A)=1\mu(A) = 1.

Remarks

Equivalent forms: every measurable f ⁣:X→ℝf \colon X \to \R with f∘T=ff \circ T = f almost everywhere is constant almost everywhere. One can also require μ(T−1(A)△A)=0\mu(T^{-1}(A) \mathbin{\triangle} A) = 0 instead of T−1(A)=AT^{-1}(A) = A; this gives the same class of maps. Example: the rotation T(x)=x+α mod 1T(x) = x + \alpha \bmod 1 on [0,1)[0,1) with Lebesgue measure and α\alpha irrational. If AA is invariant, the Fourier coefficients of f=1Af = 1_A satisfy f^(k)e2πikα=f^(k)\hat f(k) e^{2 \pi i k \alpha} = \hat f(k). Since kα∉ℤk \alpha \notin \Z for k≠0k \ne 0, all f^(k)\hat f(k) with k≠0k \ne 0 vanish, so ff is constant almost everywhere and μ(A)∈{0,1}\mu(A) \in \set{0, 1}. Non-example: for α=1/2\alpha = 1/2 the set A=[0,1/4)∪[1/2,3/4)A = [0, 1/4) \cup [1/2, 3/4) is invariant with μ(A)=1/2\mu(A) = 1/2. The identity map is not ergodic on [0,1][0,1] either, since every measurable set is invariant. The definition extends to σ\sigma-finite measures: then an invariant set must be null or have null complement.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Ergodicity
About this page
TagH3SZ6VAJ6F
URIm2://H3SZ6VAJ6F
Kinddefinition
WritingW0 stub
MSC37A25, 28D05
DefinesErgodic transformation
UsesProbability space, Measure-preserving transformation
Changed2 November 2026

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