Dynamical systems and ergodic theory Definition
Mixing
Builds on Probability spaceMeasure-preserving transformation
Definition
Let be a probability space and let be a measure-preserving transformation. The map is mixing, or strongly mixing, if for all ,
Remarks
Example: let on with Lebesgue measure . Let and be dyadic intervals of length , that is, of the form . For , the set is a union of intervals of length , one in each interval . Exactly of them lie in , so . Dyadic intervals generate the Borel sets, and an approximation argument gives the limit for all and .
Non-example: let with irrational, and let . The numbers come arbitrarily close to for infinitely many , and for those the measure is close to . So it does not tend to , and the rotation is not mixing, although it is ergodic.
Taking with shows that a mixing map is ergodic: then , so . In terms of functions, is mixing if and only if for all .
Reading path
To understand this page from the ground up, read these 3 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Measure-preserving transformation concept
- Probability space concept
- Mixing definition
Further reading
About this page
| Tag | DFCJCRTTBR |
|---|---|
| URI | m2://DFCJCRTTBR |
| Kind | definition |
| Writing | W0 stub |
| MSC | 37A25, 28D05 |
| Defines | Mixing |
| Uses | Probability space, Measure-preserving transformation |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
- a source with a locator (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
No page links to this page yet.