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.
FALSE: a positive-semidefinite Hessian gives strict convexity
Statement
False claim: an everywhere-positive-semidefinite Hessian forces a function on an open convex set to be strictly convex.
Facts & Assumptions
Given: No assumptions beyond the false claim.
The Hessian of is positive semidefinite everywhere, but is not strictly convex (A positive-semidefinite Hessian need not give strict convexity).
Refutation
The function in [L1] satisfies the Hessian hypothesis of the false claim.
It is constant along every vertical line and therefore violates strict convexity by [L1]. Hence the claim is false.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
6 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
- S. Boyd and L. Vandenberghe, Convex Optimization, §3.1.4 (standard reference, not scraped)