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.
The column-interference graph and collision-free coloring for a sparse Jacobian
Definition
Let , be open, be differentiable at , and be its Jacobian as defined in The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case. A structural row pattern is a list of sets , one for each row , such that whenever . It is a safe pattern only when every actual nonzero lies in the declared support.
The column-interference graph has vertices and an edge between distinct columns exactly when some row support contains both. A proper coloring is a map to a set of color labels such that adjacent columns have different labels. For a color , its seed vector has coordinate when and otherwise. The compressed product is .
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
- Thomas F. Coleman and Jorge J. Moré, Estimation of Sparse Jacobian Matrices and Graph Coloring Problems, Argonne National Laboratory Report ANL-81-39 (standard reference, not scraped)
- Bradley M. Bell and Kasper Kristensen, Computing Sparse Jacobians and Hessians Using Algorithmic Differentiation (standard reference, not scraped)