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.
Countably many independent copies of a prescribed law exist
Statement
Assume countable choice and dependent choice. Every probability measure on is the common law of a countable independent family of -valued random elements.
Facts & Assumptions
Given: Countable choice, dependent choice, and a measurable probability space .
Under countable choice and dependent choice, the canonical countable product probability measure exists. (Assuming countable and dependent choice, countable products of arbitrary probability spaces)
Its canonical coordinates have their prescribed laws and are independent. (Coordinate random elements of a countable product are independent)
Proof
Apply [F1] with and for every , and write for its coordinate maps.
By [F2], every has law and every finite subfamily is independent; this is the required independent-copy sequence.
Depends on
- Assuming countable and dependent choice, countable products of arbitrary probability spaces
- Coordinate random elements of a countable product are independent
- Law or distribution of a random element
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The axiom of dependent choice: a relation in which every element is related to something admits an $\mathbb{N}$-indexed chain
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
20 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.
Sources
- Durrett, Probability: Theory and Examples, Section 2.1.4 (standard reference, not scraped)