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 disconnected unanchored network gives a singular steady solve
Example
Let a closed four-vertex network have edges and with conductances and . Its steady stiffness is singular: each disconnected positive-conductance component contributes an independent constant kernel mode. The load is incompatible with the first component's Neumann balance, so it has no steady solution.
The two disconnected edges and their conductances are shown below; all vertex masses are one, and the right-hand side is .
\begin{center} \begin{tikzpicture}[every node/.style={font=\small}] \node[circle,draw] (v1) at (0,0) {}; \node[circle,draw] (v2) at (1.7,0) {}; \node[circle,draw] (v3) at (3.5,0) {}; \node[circle,draw] (v4) at (5.2,0) {}; \draw[->] (v1) -- node[above] {} (v2); \draw[->] (v3) -- node[above] {} (v4); \node[below=4pt] at (v1) {}; \node[below=4pt] at (v2) {}; \node[below=4pt] at (v3) {}; \node[below=4pt] at (v4) {}; \end{tikzpicture} \end{center}
Facts & Assumptions
Given: Vertices , oriented edges and , conductances , no Dirichlet vertices, and mass matrix .
The stiffness is ; its kernel consists of componentwise constants on positive-conductance components, and its left kernel is the same because it is symmetric (Finite weighted network diffusion data, Energy, kernel, and weighted mass balance for a finite network).
Verification
Given: The disconnected weighted path-pair network and the stated load.
Direct multiplication gives The two independent component indicator vectors and lie in its kernel by [F1], so the steady matrix is singular.
The vector has dot product with the first component indicator, while every vector in the image of the symmetric matrix is orthogonal to its kernel: for and , . Thus this load is not in the image and the Neumann steady equation has no solution.
Depends on
Used by
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Dependency tree · two levels
8 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
- Fan R. K. Chung, Spectral Graph Theory, Chapter 1: Eigenvalues and the Laplacian of a Graph, CBMS 92 (1997), complete chapter text (standard reference, not scraped)
- Ward Whitt, Continuous-Time Markov Chains, full lecture notes (2006) (standard reference, not scraped)