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 one-node coarse space misses a high-conductance channel
Statement refuted
A bounded-size one-node coarse space, together with bounded-overlap exact local solves, guarantees an additive Schwarz condition number uniform in every positive diffusion contrast.
Facts & Assumptions
Given: A contrast parameter , global space , a coarse space , and one local space .
For full-column-rank prolongations, the exact additive preconditioner is with (Finite-dimensional Schwarz subspace-correction data).
Counterexample
The grounded two-node graph with unit conductance from each node to ground and conductance between the nodes has matrix For , , so is SPD. The coarse and local injections are and , hence . The additive preconditioner from [F1] is therefore . There is one local subspace, so its pairwise overlap matrix is the fixed matrix , independent of .
The vectors and are eigenvectors of with eigenvalues and . Thus has eigenvalues and , so . The low-energy channel vector is not in the one-node coarse space , and the growing condition number disproves the claim.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
11 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
- Jinchao Xu, Iterative Methods by Space Decomposition and Subspace Correction, SIAM Review 34(4) (1992) (standard reference, not scraped)
- Peter Bastian, Lecture Notes on Parallel Solution of Large Sparse Linear Systems, University of Heidelberg (2015) (standard reference, not scraped)