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.
Finite-budget Gauss–Seidel stationary iteration
Definition
Input , , , and an
iteration budget . Use the fixed order . Check
dimensions; on a mismatch return invalid-input. Form by
Diagonal, lower, and upper parts in the stationary-iteration convention. If some diagonal entry of
is zero, return pivot-failure(i) for the least such index .
Otherwise set and , so . For each , solve the lower-triangular system
by forward substitution in increasing index order. Equivalently, the component updates are
Return completed with . The lower-triangular solve is unique after
the pivot check by Forward and backward substitution for triangular linear systems
and Forward and backward substitution are correct, unique, and quadratic in scalar operations.
After the dimension and pivot checks succeed, a zero budget returns
completed with . The procedure reports no convergence or accuracy
certificate.
Depends on
Used by
Dependency tree · two levels
7 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 (standard reference, not scraped)
- David Bindel, Matrix Computations (CS 6210), Cornell University, Fall 2012, Lecture 31 (standard reference, not scraped)
- Rutgers University MATH 574, Lecture Notes, §3 Matrix iterative methods (standard reference, not scraped)