ergodic theorem
E582382
The ergodic theorem is a fundamental result in dynamical systems and probability theory that links long-term time averages of a system’s evolution to ensemble or space averages, underpinning the statistical behavior of many physical and stochastic processes.
All labels observed (6)
| Label | Occurrences |
|---|---|
| Birkhoff ergodic theorem | 2 |
| Birkhoff’s ergodic theorem | 1 |
| Birkhoff’s pointwise ergodic theorem | 1 |
| ergodic theorem canonical | 1 |
| von Neumann mean ergodic theorem | 1 |
| von Neumann’s mean ergodic theorem | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6293667 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
Target entity: ergodic theorem Context triple: [law of large numbers, relatesTo, ergodic theorem]
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A.
Kakutani equivalence in ergodic theory
Kakutani equivalence in ergodic theory is a notion of equivalence between measure-preserving dynamical systems based on the isomorphism of their induced transformations on subsets of positive measure.
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B.
Kakutani’s random ergodic theorem
Kakutani’s random ergodic theorem is a fundamental result in ergodic theory that extends classical ergodic theorems to sequences of randomly chosen measure-preserving transformations.
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C.
Lectures on Ergodic Theory
"Lectures on Ergodic Theory" is a classic mathematical monograph that systematically develops the foundations and key results of ergodic theory within dynamical systems.
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D.
Khinchin–Kolmogorov theorem
The Khinchin–Kolmogorov theorem is a fundamental result in probability theory that provides conditions under which series of independent random variables converge almost surely.
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E.
Poincaré recurrence theorem
The Poincaré recurrence theorem is a fundamental result in dynamical systems and ergodic theory stating that certain systems will, after a sufficiently long but finite time, return arbitrarily close to their initial state.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: ergodic theorem Target entity description: The ergodic theorem is a fundamental result in dynamical systems and probability theory that links long-term time averages of a system’s evolution to ensemble or space averages, underpinning the statistical behavior of many physical and stochastic processes.
-
A.
Kakutani equivalence in ergodic theory
Kakutani equivalence in ergodic theory is a notion of equivalence between measure-preserving dynamical systems based on the isomorphism of their induced transformations on subsets of positive measure.
-
B.
Kakutani’s random ergodic theorem
Kakutani’s random ergodic theorem is a fundamental result in ergodic theory that extends classical ergodic theorems to sequences of randomly chosen measure-preserving transformations.
-
C.
Lectures on Ergodic Theory
"Lectures on Ergodic Theory" is a classic mathematical monograph that systematically develops the foundations and key results of ergodic theory within dynamical systems.
-
D.
Khinchin–Kolmogorov theorem
The Khinchin–Kolmogorov theorem is a fundamental result in probability theory that provides conditions under which series of independent random variables converge almost surely.
-
E.
Poincaré recurrence theorem
The Poincaré recurrence theorem is a fundamental result in dynamical systems and ergodic theory stating that certain systems will, after a sufficiently long but finite time, return arbitrarily close to their initial state.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
mathematical theorem
ⓘ
result in ergodic theory ⓘ |
| appliesTo |
Markov chains with unique stationary distribution
ⓘ
ergodic transformations ⓘ measure-preserving dynamical systems ⓘ stationary ergodic processes ⓘ |
| field |
dynamical systems
ⓘ
ergodic theory ⓘ probability theory ⓘ statistical mechanics ⓘ |
| generalizationOf | law of large numbers ⓘ |
| hasConsequence |
almost sure convergence of time averages
ⓘ
existence of typical trajectories ⓘ law of large numbers for dynamical systems ⓘ |
| hasForm |
Birkhoff ergodic theorem
NERFINISHED
ⓘ
ergodic theorem for Markov chains ⓘ ergodic theorem for flows ⓘ ergodic theorem for group actions ⓘ ergodic theorem for stationary processes ⓘ mean ergodic theorem NERFINISHED ⓘ multiparameter ergodic theorem ⓘ pointwise ergodic theorem NERFINISHED ⓘ subadditive ergodic theorem NERFINISHED ⓘ von Neumann mean ergodic theorem NERFINISHED ⓘ |
| historicalDevelopment | formulated in modern form in the 20th century ⓘ |
| implies | equivalence of time and ensemble averages under ergodicity ⓘ |
| notableContributor |
George David Birkhoff
NERFINISHED
ⓘ
John von Neumann NERFINISHED ⓘ |
| relatedTo |
Kolmogorov–Sinai entropy
NERFINISHED
ⓘ
Poincaré recurrence theorem NERFINISHED ⓘ mixing ⓘ strong mixing ⓘ weak mixing ⓘ |
| relatesConcept |
ensemble average
ⓘ
ergodic measure ⓘ invariant measure ⓘ long-term statistical behavior ⓘ measure-preserving transformation ⓘ space average ⓘ stationary stochastic process ⓘ time average ⓘ |
| states | for an ergodic measure-preserving transformation, time averages converge almost surely to space averages ⓘ |
| usedIn |
Markov chain Monte Carlo
NERFINISHED
ⓘ
Monte Carlo methods NERFINISHED ⓘ chaos theory ⓘ information theory ⓘ probabilistic number theory ⓘ random dynamical systems ⓘ signal processing ⓘ statistical mechanics ⓘ thermodynamics ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Subject: ergodic theorem Description of subject: The ergodic theorem is a fundamental result in dynamical systems and probability theory that links long-term time averages of a system’s evolution to ensemble or space averages, underpinning the statistical behavior of many physical and stochastic processes.
Referenced by (7)
Full triples — surface form annotated when it differs from this entity's canonical label.