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.
SOR on a positive-definite system with relaxation parameter in (0, 2)
Example
Take
The matrix is positive definite and . For the fixed order , the SOR iteration matrix is
with eigenvalues , both of modulus . Thus the error converges to zero for every initial vector.
Facts & Assumptions
Given: The displayed matrix, right-hand side, initial vector, and relaxation parameter.
SOR uses and (Finite-budget successive over-relaxation stationary iteration).
For Hermitian with positive diagonal, SOR converges for every start if and only if is positive definite and (SOR converges exactly for positive-definite A and relaxation parameter in (0, 2)).
Hermitian positive definite means and for every nonzero (Hermitian positive-definite matrices and Cholesky factorisation A = LL* with positive diagonal).
Verification
For , , so [L2] shows that is positive definite; its diagonal is positive and .
Here , , and . By [F1], and , hence . Its characteristic polynomial is , whose roots are and have modulus .
The hypotheses of [L1] hold by step 1.1, so SOR converges for every start; in particular the stated start converges to the solution .
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
14 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
- Yousef Saad, Iterative Methods for Sparse Linear Systems, 2nd ed., §§4.1 and 4.2.4 (standard reference, not scraped)