Alphabeta Math
LemmaStatement: Literature-sourcedProof: AI-adaptedPipeline-generatedjudge pass (gpt-5.6-terra)audited 2026-09-14
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.

Soundness of the three word rules and density-preserving finite thinning

Statement

Let Q⊆∏i=1dTi, where d>0 and the Ti are finitistic trees. Under the matrix/node interpretation below, formulas are monotone when a coordinate set bound by ∀xi is shrunk. Moreover, if W⊢dW′, then

∀n ∃p Φ(W,n,p)⟹∀n ∃p Φ(W′,n,p).

Thus Rule 3 is sound for this quantified scheme, although it need not preserve a pointwise interpretation with the same density parameter.

Facts & Assumptions

Given: The displayed d,Ti,Q, words W,W′∈Ld, and a derivation W⊢dW′.

[F1]

The preceding definition supplies domination, finite levels, no terminal nodes, and (h,k)-density. Finitistic trees, level products, density, and matrices

[F2]

The only generating steps of ⊢d are the three stated rule classes. The finite word calculus for the Halpern–Läuchli argument

Proof

1.1F1F2givenconstruct

For Bi⊆Ti and ni<ω, put Ci(ni,Bi)={Bi∩{u:t≤Tiu}:t∈Ti(ni)}. Interpret a word from left to right: ∃Ai means “there is Ai⊆Bi that is ni-dense”; ∀xi ranges over Ai; ∀ai ranges over Ci(ni,Bi); and ∃xi ranges over ai. At the empty word assert (x1,…,xd)∈Q. Let W(n,B) be the resulting sentence, and let Φ(W,n,p) say that W(n,B) holds whenever every Bi is p-dense.

2.1step 1.1

If a subformula has Ai only through a quantifier ∀xi∈Ai, replacing Ai by Ai′⊆Ai preserves its truth, because fewer values of xi must be checked. Repeating this argument proves simultaneous monotonicity in every such coordinate.

2.2F2step 1.1

Rule 1 preserves the scheme: like quantifiers commute, and a witness for ∃α ∀β is independent of β and therefore witnesses ∀β ∃α. The side condition that the result lies in Ld ensures that all variable domains in step 1.1 are already defined when used.

2.3F1F2step 1.1choose

Rule 2 is pointwise valid. If ∀ai∈Ci(ni,Bi) there is xi∈ai satisfying the tail, choose one witness from each member of this one finite cone family and collect the witnesses as Ai; it lies in Bi, meets every height-ni cone, hence is ni-dense, and the tail holds for all its members. Conversely, an ni-dense Ai⊆Bi meets every cone in Ci(ni,Bi), so a member of the intersection supplies the matched existential. Finite induction supplies the finitely many witnesses and uses no choice axiom.

2.4F1F2step 1.1assume-hypconstruct

Consider Rule 3 with 1≤r<d, after relabelling its permutation: W=(∀ai)i=1r(∃Ai)i=r+1dV and W′=(∃Ai)i=r+1d(∀ai)i=1rV. Assume ∀k∃p Φ(W,k,p). Because a p′-dense set is p-dense when p′≥p, let F(k) be the least witness exceeding every ki. For fixed n, define G(0)=max⁡i>rni and G(j+1)=F(n1,…,nr,G(j),…,G(j)). This uses least natural witnesses and recursion on ω, not a choice function.

3.1F1step 2.4base

Put m=∏i=1r∣Ti(ni)∣ and pj=G(m−j) for 0≤j≤m. Given p0-dense Bi, enumerate the m tuples of height-ni roots in the first r trees; their associated cone tuples may repeat. Before any tuple is processed, take Ai0=Bi for i>r. These sets are p0-dense and the preservation requirement for the empty list is vacuous.

4.1F1step 2.1step 2.4step 3.1ihchoose

Suppose j<m cone tuples have been processed and Aij⊆Bi is pj-dense for every i>r, with the tail V true for all earlier tuples. Apply Φ(W,(n1,…,nr,pj+1,…,pj+1),pj) to the next cone tuple and to B1,…,Br,Ar+1j,…,Adj. It yields Aij+1⊆Aij that are pj+1-dense and make V true for the new tuple. Step 2.1 preserves all earlier instances. Finite induction gives final sets Aim working for all cone tuples.

5.1F1step 2.4step 4.1discharge-induction

Since pm=G(0)≥ni for i>r, each Aim is ni-dense: extend any height-ni node to height pm and use pm-density. Hence the Aim witness the leading existential block of W′, and the universal block holds because step 4.1 processed every root tuple. Therefore Φ(W′,n,p0) holds. The vector n was arbitrary, proving Rule 3 preserves the quantified scheme.

6.1F2step 2.2step 2.3step 5.1∎

A derivation is finite. Apply steps 2.2, 2.3, or 5.1 successively to its rule steps; transitivity gives the displayed implication for W⊢dW′.

Depends on

Used by

Dependency tree · two levels

4 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