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 stationary splitting converges for every start if and only if its iteration matrix has spectral radius below
Statement
Let be a matrix splitting in with stationary iteration
and let be its iteration matrix. Then the following are equivalent:
- For every right-hand side and every initial vector , the iterates converge to the unique solution of .
- The spectral radius is strictly less than .
Facts & Assumptions
Given: A complex matrix splitting with invertible , its stationary iteration, and its iteration matrix .
The stationary iteration is with (Stationary iteration from a matrix splitting ).
The field is algebraically closed (The complex numbers are algebraically closed).
Over an algebraically closed field, every endomorphism has Jordan form (Every finite-dimensional endomorphism over an algebraically closed field has Jordan form).
The spectrum is the root set of the characteristic polynomial (For every finite-dimensional space, is exactly the set of roots in of ).
Proof
A vector is a fixed point of the stationary iteration if and only if it solves : indeed, by [F1], Therefore, whenever solves , the error satisfies
Assume . By [L1], [L2], and [L3], we may write with Jordan and every eigenvalue of satisfying . On a Jordan block with nilpotent , one has Because , each scalar factor tends to , so every Jordan block tends to . Hence and therefore . Since , the matrix is invertible by [L3]. Define Then , so , and step 1.1 shows that solves . For any initial vector , step 1.1 gives , so the iterates converge to . If is another solution of , then step 1.1 also gives , hence Iterating and using yields , so . Thus the iterates converge to the unique solution of for every and every .
Conversely, assume the iteration converges for every and every . Taking , statement 1 gives convergence to the unique solution of . By step 1.1 that unique solution is also the unique fixed point of , so it is . Hence for every start one has , which means . If with , then so and therefore . By [L3], every spectral value of is such an eigenvalue over , and thus .
Depends on
Used by
Dependency tree · two levels
28 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
- Gilbert Strang, 18.086 Mathematical Methods for Engineers II, Section 6.2 Iterative Methods (standard reference, not scraped)