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.
Existence and uniqueness of the full Palm law and the refined Campbell identity
Statement
Assume AC and Countable Choice as carried by the point-process supplier. For every stationary locally finite point process on with finite positive intensity , there is a unique probability law on the configuration space satisfying
for every nonnegative product-measurable . Moreover, -almost every configuration has at least one occurrence at the origin.
Facts & Assumptions
Given: AC, Countable Choice, a stationary locally finite point process with finite positive intensity , and its configuration space.
AC is carried by the transitive random-point-process supplier dependencies; the local Palm construction uses no selection. (The Axiom of Choice)
Countable Choice is carried by the transitive random-point-process and Lebesgue-measure supplier dependencies. (The Axiom of Countable Choice ())
A point process is a measurable random locally finite counting measure, and the evaluation maps generate its configuration sigma-algebra. (Random measures and locally finite point processes)
Stationarity is invariance under the stated recentering action; its intensity mean measure is . (Stationarity, finite intensity, and spatial ergodicity, A stationary point process of finite intensity has mean measure rho times Lebesgue measure)
The recentering action is jointly measurable. (Recentering a point configuration at a spatial location, The spatial recentering action is jointly measurable)
Every locally finite translation-invariant Borel measure on is its unit-cube mass times Lebesgue measure. (A locally finite translation-invariant Borel measure on is a multiple of Lebesgue measure)
Parameterized nonnegative integration against the evaluation kernel is measurable, and increasing limits pass through expectations. (Measure kernel and probability kernel, Measurability of integration against a kernel, Monotone convergence for the integral)
Sigma-finite product measures exist and are determined by their values on a generating pi-system with a finite-measure exhaustion. (The product sigma-algebra and its finite iterates, For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique, Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system)
Proof
Given: AC, Countable Choice, a stationary point process with , , and the recentering action.
For each configuration event and Borel set , define The integrand is measurable by [F3], so this is defined. For disjoint , the indicators of their finite unions increase to the indicator of their union; monotone convergence [F5] and countable additivity of each give . Also by [F2], so is locally finite.
For any , recentering has the flow property . Changing the location variable in the integral gives where the last equality uses stationarity of . Thus is translation invariant.
By [F4] there is a constant such that for every Borel . For disjoint configuration events , monotone convergence in the indicator sum gives . Also and . Hence is a probability measure on the configuration sigma-algebra.
For Borel and configuration event , the definition gives Define the Campbell measure on the product space. Joint measurability [F3] and monotone convergence [F5] make a measure. It is sigma-finite since for the increasing bounded cubes . The product measure is sigma-finite by [F6] and agrees with on rectangles by the displayed identity; uniqueness on the generating rectangle pi-system therefore gives equality of these measures. Integrating any nonnegative product-measurable against them proves the refined Campbell identity.
If is another probability law satisfying the refined identity, use to obtain for every configuration event ; since , .
Let . For every counted occurrence of , the recentered configuration has an occurrence at , so the left side of the refined identity with is zero. Its right side is because . Hence : the full Palm law retains at least the distinguished occurrence at the origin, even when other occurrences coincide there.
The constructed law satisfies the defining identity by step 4.1, is unique by step 5.1, and has the origin-atom property by step 5.2. AC and Countable Choice [A1]–[A2] are inherited supplier assumptions; the construction itself uses no choice beyond the Lebesgue-measure supplier.
Sources
Last and Penrose, Chapter 9, Theorem 9.1 and Lemma 9.2; Baddeley, Lecture 3, §3.2. The construction is given locally rather than by conditioning on a null event.
Depends on
- Random measures and locally finite point processes
- The full Palm distribution defined by the refined Campbell identity
- Stationarity, finite intensity, and spatial ergodicity
- A stationary point process of finite intensity has mean measure rho times Lebesgue measure
- Recentering a point configuration at a spatial location
- The spatial recentering action is jointly measurable
- A locally finite translation-invariant Borel measure on $\mathbb R^d$ is a multiple of Lebesgue measure
- Mean measures and measurable nonnegative integrals of random measures
- Measures on sigma-algebras
- The product sigma-algebra and its finite iterates
- Measure kernel and probability kernel
- Measurability of integration against a kernel
- Measures agreeing on a generating pi-system are equal under an increasing finite-measure exhaustion from that pi-system
- For sigma-finite factors, the product measure exists, has the rectangle formula, is sigma-finite, and is unique
- Monotone convergence for the integral
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The Axiom of Choice
Used by
- Pair-correlation density and Ripley K-function Definition
- A translated lattice exposes recentering, atomic pair measures, and one-occurrence deletion Example
- A pair-correlation density integrates to Ripley K Theorem
- Ripley K for a homogeneous Poisson process is Euclidean ball volume Theorem
- The reduced second factorial moment measure is the Palm expectation after one-occurrence deletion Theorem
Cited to discharge well-definedness by The full Palm distribution defined by the refined Campbell identity.
Dependency tree · two levels
67 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
- Günter Last and Mathew Penrose, Lectures on the Poisson Process (2017 author-hosted version) (standard reference, not scraped)
- Adrian Baddeley, Spatial Point Processes and their Applications (standard reference, not scraped)