Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicableaudited 2026-08-02
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 Jacobian matrix of partial derivatives and the gradient in the scalar-valued case

Definition

If every partial derivative ∂jfi(a) of f:U→Rn exists, the Jacobian matrix is Jf(a)=(∂jfi(a))i<n,j<m. For scalar-valued f, its gradient is

∇f(a):=(∂0f(a),…,∂m−1f(a))∈Rm,

with coordinates understood in the standard basis (The standard list e:n→Fn with ei(i)=1F and ei(j)=0F for j≠i is an ordered basis of Fn; hence dim⁡FFn=n, and F0 is the zero space with basis ∅ and dimension 0). The partial derivatives are those of Directional derivatives and partial derivatives of a map U⊆Rm→Rn.

Depends on

Used by

…and 16 more results.

Dependency tree · two levels

31 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