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.
A two-row hypercohomology spectral sequence
Example
Let be bounded below with except for , and supply the data of the second hypercohomology theorem for . Put , . The only rows are and . With , the target fits into where negative-index terms are zero. The values of and these extensions need additional input for a general .
Facts & Assumptions
Given: The functor, complex and supplied replacements, with DC or supplied comparisons for naturality.
The second hypercohomology theorem gives this , finite decreasing filtration and differential (Second hypercohomology spectral sequence).
A computation record must retain unknown differentials and extensions explicitly (Spectral-sequence computation record).
Verification
For the only possible nonzero arrows are from row one to row zero. Hence and . For , every outgoing arrow from either row has negative second coordinate and every incoming arrow starts above row one. These positions stay zero on successive pages, so .
In total degree , the only possible filtration quotients are at and . F1's zero/full endpoints identify the first as a subobject of the target and the second as its quotient, giving the displayed exact sequence. At it reduces to ; at its subobject is and its quotient is . Below zero there are no surviving quotients, so the finite target filtration forces vanishing. This proves convergence and identifies the unresolved extension, rather than assuming a splitting.
A fully numerical specialization takes abelian groups, the identity, and , with zero differential and supplied replacements. Exactness of identity means its positive derived objects vanish, since applying it preserves the exact resolution. Thus , , all other entries are zero, and every is zero. Each total degree has one nonzero quotient: the target is in degree zero, in degree one and zero otherwise. The upper edges are the identity under the augmentation identification. This specialization has no extension ambiguity and uses no choice beyond the supplied-data convention.
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
- Weibel, Section 5.7 (standard reference, not scraped)