Alphabeta Math
DefinitionDefinition: AI-adaptedProof: Not applicablePipeline-generatedjudge pass (gpt-5.6-terra)
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.

Strong convergence of a spectral sequence

Definition

A spectral sequence converges strongly to (Hn,F) on this page if it converges weakly with specified identifications as in Weak convergence of a spectral sequence, is two-sided regular as in Regular spectral sequence, and for each n its target filtration is exhaustive, separated and complete. Here exhaustiveness and separatedness mean pFpHn=Hn,pFpHn=0, as in Exhaustive separated bounded and finite filtration, and completeness means that the canonical map HnlimpHn/FpHn is an isomorphism. All indicated subobject meets, joins and inverse limits must exist. The limit has the universal-property meaning of Limits and colimits as terminal cones and initial cocones, with existence and uniqueness in their universal properties: the transition for pp is the quotient Hn/FpHnHn/FpHn. In modules the limit is the module of compatible residue classes. All these conditions are required; the weak-convergence identifications remain part of the data.

A finite filtration is complete: if FaHn=0, every quotient with pa is canonically Hn, with identity transitions. A cone is determined by its component at any such index, and its components at larger indices are its quotient maps. Thus Hn itself is the inverse limit, even if the ambient category does not admit arbitrary inverse limits. The same finite lower endpoint gives separatedness, and a finite upper endpoint FbHn=Hn gives exhaustiveness. This includes Hn=0 and repeated filtration terms.

For decreasing cohomological filtrations use Hnlimp+Hn/FpHn and graded pieces Fp/Fp+1. No splitting of the filtration and no choice axiom is included. The two-sided regularity convention is stronger than the outgoing-only meaning of regularity in Stacks, Definition 12.24.9; a source criterion must be checked against every condition above.

Depends on

Used by

Dependency tree · two levels

5 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