Dynamical systems and ergodic theory Definition
Ergodic transformation
Builds on Probability spaceMeasure-preserving transformation
Definition
Let be a probability space, and let be a measure-preserving transformation. A set is -invariant if . The map is ergodic if every -invariant set satisfies or .
Remarks
Equivalent forms: every measurable with almost everywhere is constant almost everywhere. One can also require instead of ; this gives the same class of maps. Example: the rotation on with Lebesgue measure and irrational. If is invariant, the Fourier coefficients of satisfy . Since for , all with vanish, so is constant almost everywhere and . Non-example: for the set is invariant with . The identity map is not ergodic on either, since every measurable set is invariant. The definition extends to -finite measures: then an invariant set must be null or have null complement.
Reading path
To understand this page from the ground up, read these 3 pages in order. The foundations come first.
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- no evidence level
- Measure-preserving transformation concept
- Probability space concept
- Ergodic transformation definition
Further reading
About this page
| Tag | H3SZ6VAJ6F |
|---|---|
| URI | m2://H3SZ6VAJ6F |
| Kind | definition |
| Writing | W0 stub |
| MSC | 37A25, 28D05 |
| Defines | Ergodic transformation |
| Uses | Probability space, Measure-preserving transformation |
| Changed | 2 November 2026 |
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