How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
A divergent probability sum does not force infinitely many occurrences without independence
Statement refuted
If is a sequence of events with then
Facts & Assumptions
Given: An event with , and define for every .
The event is the event that infinitely many of the occur. (Limsup and the infinitely often event)
Probability measures respect complements and monotone set identities. (Basic identities for a probability measure)
Counterexample
Since every equals , one has
For every outcome , either and then for all , or and then for all . Hence the infinitely-often event is exactly itself:
Therefore and the chosen hypothesis makes this probability strictly between and . So the displayed implication is false without an independence hypothesis.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
10 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.