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DefinitionDefinition: Literature-sourcedProof: Not applicablePipeline-generatedjudge pass (gpt-6.1-sol)
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 content of a node and the content vector of a standard tableau

Definition

Let λ⊢n with Young diagram [λ] (Partitions, English diagrams, and conjugation), so that the nodes of [λ] are the pairs (r,c) with r,c≥1 and c≤λr (rows numbered downward, columns rightward).

The content of a node (r,c)∈[λ] is c(r,c):=c−r, the column index minus the row index. The node (r,c) therefore has content t exactly when it lies on the diagonal c−r=t; the content of (1,1) is 0, contents increase by 1 along a row and decrease by 1 down a column.

Now let T be a standard tableau of shape λ (Tableaux and standard tableaux). For 1≤k≤n let (rk,ck) be the node of [λ] carrying the entry k, so that T(rk,ck)=k. The content vector of T is Cont⁡(T):=(cT(1),…,cT(n))∈Zn,cT(k):=c(rk,ck)=ck−rk, the list of contents of the nodes read in the order of the entries 1,2,…,n. For the empty tableau of shape ∅ the content vector is the empty vector, the unique element of Z0.

Remarks

  • Well-definedness. A tableau T of shape λ is a bijection [λ]→{1,…,n}, so each k∈{1,…,n} occupies exactly one node (rk,ck) and the integers cT(k)=ck−rk are determined by T. The map T↦Cont⁡(T) uses the fixed row and column coordinates and the labels of T: it depends only on which entry stands in which node.

  • The entries of the content vector are the contents of the shape. Since T is a bijection onto the n nodes of [λ], the multiset of entries of Cont⁡(T) equals the multiset of node contents {c(x):x∈[λ]}, independent of T. In particular two standard tableaux of the same shape have content vectors that differ by a permutation of their entries, and the multiset of contents of a tableau is an invariant of its shape.

  • Two extreme examples. The row tableau of shape (n) carries k in (1,k), so its content vector is (0,1,2,…,n−1); the column tableau of shape (1n) carries k in (k,1), so its content vector is (0,−1,−2,…,−(n−1)).

  • First entries. The entry 1 always occupies the node (1,1), because every other node has a node weakly to its left and weakly above it, whose entry would be smaller. Hence cT(1)=0 for every nonempty standard tableau T. Similarly, cT(k) need not be monotone in k: for the tableau 123 of shape (2,1) one has Cont⁡=(0,1,−1).

Depends on

Used by

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Sources