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.
Quantum weak-separation query bound
Statement
Let , with rationally encoded radii, precision and failure budgets as in the model, and let be a closed convex body, , and . The completed deterministic coherent oracle and its inverse are supplied, with Under the finite encoding and numerical-error budgets of Quantum membership-to-separation procedure, that procedure implements using membership and inverse queries combined. The promise applies to all encoded query points; in particular it applies throughout the bounded rational localization queries used below. The oracle completion need not be unique in the weak boundary band.
For the optimization composition assume countable choice. Given , , and a unit objective with costed rational approximations, use from Query-only optimization from weak separation by centroid cuts and . Membership access at any precision then returns, with probability at least , a point satisfying , with at most times the preceding per-separation membership-query bound, evaluated at . This is membership queries, where the suppressed factors are logarithmic in . It implies the corresponding weak-optimization guarantee over . Output, QFT/phase gates, rotations, numerical precision, centroid computation, and all classical arithmetic/bit costs are additional. No polynomial-time centroid implementation is asserted.
Facts & Assumptions
Given: The body, radii, weak-membership completion, inverse access, and finite procedure specified in the Statement.
The local height lemma proves convexity, Lipschitz constant , weak-membership value search, clean query implementation, and conversion of an approximate subgradient to an inward separator. (Height geometry and weak-membership binary search)
The local finite-grid lemma proves the full Fourier-tail, mesh, median, approximate-subgradient and value-query bounds. (A finite-grid quantum subgradient from approximate values)
The weak-separation contract uses an outward unit normal and an upper halfspace inequality. (Quantum convex membership and weak-separation model)
The explicit OP7 chooses its finite mesh, power-of-two Fourier grid, encoded output and deterministic error budgets. (Quantum membership-to-separation procedure)
Under countable choice the local centroid reduction proves the stated weak-separation precision, adaptive call count and optimization guarantee with separately charged arithmetic. (Query-only optimization from weak separation by centroid cuts, The Axiom of Countable Choice ())
Proof
If the supplied boundary width is smaller than half its positive admissible upper bound, regard the same oracle as having that larger width. Its two assertions remain valid because outer bands enlarge and inward erosions shrink; the same is true for an exact zero-width oracle. Write for this working allowance, which still satisfies the displayed input bound. First query membership at . IN implies , which is a permitted output. OUT implies , hence since inward erosions decrease with their radius. For , is an interval containing and . A positive OUT point must be at or beyond the positive endpoint minus ; a negative one has the analogous property. Its outward signed normal therefore satisfies the separation contract with slack at most . The point zero necessarily has an IN answer. This proves the scalar case with a single query.
Suppose and OUT occurs. Rotate to and use the height function of [F1]. Set , , and Then since . Moreover , by substituting , , and . Thus the height and grid lemma hypotheses hold.
Substitution of the input bound shows : squaring verifies , while the remaining factor is at most . The deterministic address perturbation in [F4] is at most and its height displacement at most . Thus effective membership uncertainty is less than . The lower height error is less than , and the upper one is at most before the additional value rounding. Hence the implemented clean height-value oracle has uniform error below . Binary search and its inverse use membership/inverse calls by [F1]. This explicit slack also permits the certified rotation/address rounding in [F4]; those are bit costs, not uncounted queries.
Apply [F2] to the transverse dimension , using its finite shift and grid. With failure probability at most , it returns satisfying The parameter substitutions are exact: and . No differentiability of or exact membership at boundary points is used.
The finite shift uses no membership query. There are phase/median runs by [F2], each using a height query and its inverse; step 2.1 supplies their logarithmic membership cost. Since is a fixed constant times a product of powers of , , and , its logarithm is . Initial queries and the scalar branch are absorbed because the displayed logarithms are bounded below by positive constants. This proves the first bound, counting forward and inverse calls separately and then adding them.
The separator conversion [F1] therefore gives, on this event, a unit inward normal with on all of . The input precision implies , so the additional encoded direction/rotation slack in [F4] still leaves error below . Emit in the original coordinates. This gives on , in particular on its inward -erosion, with the OUT assertion already justified in step 1.1. Together with the IN branch this is exactly [F3]. The rational-direction encoding in [F4] specifies an exact unit normal by normalization; its output approximation was charged in the displayed slack.
For optimization, [F5] makes at most adaptive weak-separation calls at precision and per-call failure . Each is implemented by the first part with the stated ; the conditional oracle guarantee is uniform over its input point and completed membership oracle, so the classical adaptive reduction applies. Its failure accounting and output guarantee are exactly those proved in [F5]. Now and , while and have only polynomial dependence on these radius/precision ratios, , and . Multiplying by step 3.2 therefore gives the claimed membership queries. This multiplication charges every call; it imports neither the stronger arithmetic bound from a cited cutting-plane paper nor a free centroid operation.
Depends on
- Quantum membership-to-separation procedure
- Quantum convex membership and weak-separation model
- Height geometry and weak-membership binary search
- A finite-grid quantum subgradient from approximate values
- Query-only optimization from weak separation by centroid cuts
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
29 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
- van Apeldoorn, Gilyen, Gribling, de Wolf, Convex optimization using quantum oracles, Lemmas 14–21 and Theorem 23 (standard reference, not scraped)
- Lee, Sidford, Vempala, Efficient convex optimization with membership oracles, Section 4, Theorem 15 (standard reference, not scraped)