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 point-process law is determined by its finite-dimensional count laws
Statement
Let and be point processes on with the evaluation sigma algebra on . If every finite vector of Borel-set counts has the same distribution under and , then their laws on are equal.
Facts & Assumptions
Given: Point processes with equal finite-dimensional laws of their count evaluations.
The evaluation maps generate the configuration sigma-algebra, and the law of a point process is its push-forward probability measure. (Random measures and locally finite point processes, Law or distribution of a random element, The law of a random element is a probability measure)
A probability measure is determined by its values on a generating pi-system. (Dynkin's pi-lambda theorem)
Proof
Let , the range of every count evaluation, and let consist of the cylinder sets for finite Borel families and subsets . Each such constraint is measurable because this countable range consists of Borel singletons in . The family is a pi-system: intersecting two cylinders concatenates their finite coordinate lists, and if a Borel set occurs twice its two constraints are replaced by their intersection. Every evaluation preimage is a one-coordinate cylinder of this form, so by definition of the evaluation sigma-algebra is the full configuration sigma-algebra.
The hypothesis says the laws and assign the same probability to every member of , since membership in a cylinder is a finite-vector count event. Both are probability measures by [F1]. Applying [F2] to this generating pi-system gives .
Depends on
Used by
Dependency tree · two levels
24 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
- Gunter Last and Mathew Penrose, Lectures on the Poisson Process, author-hosted 2017 version (standard reference, not scraped)
- Adrian Baddeley, Spatial Point Processes and their Applications, complete lecture notes (standard reference, not scraped)