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.
Path Poincare inequality on an anchored finite metric graph
Statement
Assume the Axiom of Choice and assume every connected edge component of the finite metric graph has at least one anchor in . Put . Then every satisfies
Facts & Assumptions
Given: The Axiom of Choice, a finite metric graph with positive edge lengths, total length , an anchor set meeting each connected component, and .
Each edge restriction has an absolutely continuous representative with increment ; all endpoint-incidence representatives at a vertex have the common value prescribed by (One-dimensional functions have unique absolutely continuous representatives, Anchored finite metric graph and its H1 energy space).
Cauchy–Schwarz gives on any finite union of edge segments (Holder's inequality for integrals, including the endpoint cases).
Vertices in one connected edge component are joined by a finite graph path, as defined in Anchored finite metric graph and its H1 energy space.
The one-dimensional representative interface assumes the Axiom of Choice (The Axiom of Choice).
Proof
Given: The finite anchored graph and the edgewise absolutely continuous representatives of .
If , then and the inequality is . Otherwise fix an edge in a component containing an anchor. If is a loop, deleting its interior leaves the component connected because any path that traverses the loop can omit that closed excursion. If its endpoints are distinct, every original path that uses reaches one endpoint before traversing it; after deleting , vertices are therefore connected to one of its two endpoints. Thus removing either leaves the component connected or separates it into two components, one containing each endpoint. In the connected case choose either endpoint; in the separated case choose the endpoint in the component containing an anchor. By [F3] there is a finite path from an anchor to that endpoint avoiding . Deleting the portions between repeated vertices gives a simple path, so no edge is traversed twice. For a loop choose its tail incidence; otherwise use the incidence at the chosen endpoint. For any on , append the segment from that incidence to . The total length is at most , and the common vertex traces agree along the path by [F1]. Since at the anchor, [F1] and [F2] imply
Integrate the pointwise bound of step 1.1 over every edge and sum. The total measure of the disjoint edge interiors is , so Taking nonnegative square roots proves the statement.
Depends on
Used by
Dependency tree · two levels
37 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
- Mario Arioli and Michele Benzi, A Finite Element Method for Quantum Graphs, Emory CS Technical Report TR-2015-009 (44-page full text) (standard reference, not scraped)
- Peter Kuchment, Quantum graphs: an introduction and a brief survey, arXiv:0802.3442 (2008) (standard reference, not scraped)