Alphabeta Math
ExampleConstruction: Literature-sourcedVerification: 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.

Finite hybrid budget for a four-address search space

Example

Take N=4 and T=2. There is a two-query all-zero-oracle circuit whose first pre-query address state is uniform on four addresses and whose second pre-query address state is the fourth basis vector. It has ∑iqt,i=1 at each query time. Its cumulative hybrid estimates give squared-distance sum at most 12, hence average at most 3, while the general aggregate theorem permits at most 4T2=16, hence average at most 4.

Facts & Assumptions

Given: The four-dimensional address register, its query projectors, and the cumulative hybrid estimate.

[F1]

The computational basis is orthonormal: the four computational address vectors are an orthonormal basis.

[F2]

Dirac Notation Conversion: ∣u⟩⟨v∣z=⟨z,v⟩rootu in the root inner-product convention.

[F3]

Query-register projectors and mismatch indicators: the address projectors are orthogonal and their squared norms sum to the squared norm of the full state.

[F4]

Cumulative hybrid distance for a T-query algorithm: each final-state distance is at most 2(q0,i+q1,i) when T=2.

[F5]

A unit-vector outer product is a density operator: for a unit vector u, Pu=∣u⟩⟨u∣ is self-adjoint and idempotent.

Proof

1.1givenF1algebra

Let ∣s⟩=12(∣0⟩+∣1⟩+∣2⟩+∣3⟩) be the first query's address state, with any fixed unit response and work state. By [F1], ∥s∥=1 and each address probability is q0,i=1/4. Hence ∑iq0,i=1.

1.2F1F2F5algebra

Put e3=∣3⟩ and u=s−e3. By [F1], ⟨s,e3⟩root=1/2, so ∥u∥2=1+1−2(1/2)=1. The map Pu=∣u⟩⟨u∣ is an orthogonal projection by [F5], and R=I−2Pu satisfies R∗R=R2=I. By [F2], Pus=⟨s,u⟩rootu=(1/2)u, so Rs=s−u=e3. Use this input-independent reflection between the first and second queries. The all-zero oracle is identity, so the second pre-query address state is ∣3⟩; thus q1,4=1, q1,1=q1,2=q1,3=0, and ∑iq1,i=1.

2.1F3F4step 1.1step 1.2algebra∎

Apply [F4]. For i=1,2,3, ∥ψ2i−ψ20∥≤2(1/2+0)=1; for i=4, ∥ψ24−ψ20∥≤2(1/2+1)=3. Therefore the sum of squared bounds is at most 3⋅12+32=12, and the average squared distance is at most 12/4=3. The general bound 4T2 gives total at most 16 and average at most 4, so the explicit address allocation is consistent with that budget.

Depends on

Used by

Nothing in the library uses this result yet.

Dependency tree · two levels

25 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