Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-generatedPipeline-generatedjudge pass (gpt-6-luna)
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 graded shuffle coproduct is coassociative, cocommutative, and conilpotent

Statement

Let Sc(W) and Δˉ be as in Reduced graded symmetric coalgebra with its shuffle coproduct. The reduced coproduct is well-defined on the graded-symmetric quotient, is coassociative and graded-cocommutative, and is conilpotent: every element is killed by a sufficiently long iterated reduced coproduct. Its primitive subspace (ker⁡Δˉ) is exactly S1(W)=W.

Facts & Assumptions

Given: A graded vector space W over a characteristic-zero field and the shuffle coproduct formula.

[F1]

Reduced graded symmetric coalgebra with its shuffle coproduct: the coproduct sums over (p,n−p)-unshuffles with the displayed Koszul signs.

[F2]

Koszul sign rule for graded tensor products and permutations: a graded permutation has the sign obtained by multiplying (−1)∣x∣∣y∣ over its transpositions.

Proof

1.1F1F2algebra

The quotient relations are generated by adjacent graded swaps. In each unshuffle summand of [F1], swapping adjacent inputs either changes their order inside one output block, where the same quotient relation applies, or moves them between blocks, where the graded flip in the target tensor product contributes exactly (−1)∣x∣∣y∣. The unshuffle terms are reindexed by this swap, so [F1] and [F2] give the same output class; hence Δˉ descends to Sn(W).

1.2F1F2algebra

Both iterated coproducts (Δˉ⊗1)Δˉ and (1⊗Δˉ)Δˉ on a length-n tensor sum over the same ordered decompositions of its labels into three nonempty, internally ordered blocks. In either parenthesization the sign is the Koszul sign of the single permutation that places those labels into the same three blocks. The terms therefore agree one by one, proving coassociativity.

1.3F1F2algebra

The graded flip interchanging the two tensor factors sends a (p,n−p)-unshuffle to the complementary (n−p,p)-unshuffle. Its block-swap sign is exactly the Koszul sign for moving every factor in the first block past every factor in the second. Thus the terms pair with identical coefficients after the graded flip, proving graded cocommutativity.

1.4F1algebra

Each application of Δˉ splits a length-n tensor into two positive lengths. An iterated coproduct into r factors is consequently a sum over ordered decompositions into r nonempty blocks; if r>n there are no such decompositions. Every element of Sc(W) is a finite sum of lengths, so a sufficiently long iterated reduced coproduct kills it.

1.5F1F2algebra

The length-one component of Δˉ on Sn(W) is Sn(W)→W⊗Sn−1(W). Compose it with concatenation W⊗Sn−1(W)→Sn(W). For a pure tensor, each of the n choices of the singleton factor returns the same graded-symmetric class: the Koszul sign used to move that factor to the front is canceled by the same sign in concatenating it back. The composite is therefore n idSn(W).

2.1F1F3step 1.5∎

If x∈Sn(W) with n≥2 is primitive, its reduced coproduct is zero, so the composite in step 1.5 gives nx=0. By [F3], multiplication by n is invertible, hence x=0. Lengths are a direct sum and every element has finite length support; the only primitives are therefore the length-one elements W. Conversely, [F1] gives Δˉ(w)=0 for each w∈W.

Depends on

Used by

Cited to discharge well-definedness by Reduced graded symmetric coalgebra with its shuffle coproduct.

Dependency tree · two levels

24 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