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.
Promise, query and cost-model examples
Example
Decision reduction. Let the source decision task have and , and let the target task have and . Define the total map by concatenating with itself. Inputs outside either one-bit source promise have no correctness obligation.
Search reduction. Let the source search domain be with relation iff and . Let the target domain be with relation iff and . Define the total instance map and the total witness map .
A total two-bit-output query instance. Write every four-bit instance as , where . Define
This is a total function on both addresses for every . Give it the decision promise and . Instances with or are off-promise.
Use the exact one-query procedure that starts with address and target , calls once, measures the two-bit target in the computational basis, and answers yes exactly when the result is . Compare it with the same procedure preceded by two Hadamard gates on the first target bit. Resource counts for these circuits use the declared QC gate, query, measurement, and classical-readout coordinates.
| Procedure | Oracle queries | Nonoracle quantum gates | Extra clean ancillas | Measurement/readout | Classical bit work |
|---|---|---|---|---|---|
| Decision reduction | 0 | not applicable | not applicable | not applicable | $O( |
| One-query circuit | 1 | 0 | 0 | One computational-basis measurement of the two-bit target; two bits read out | transitions to compare the measured value with and write one output bit |
| Same query with then on target bit 0 | 1 | 2 | 0 | One computational-basis measurement of the two-bit target; two bits read out | transitions to compare the measured value with and write one output bit |
The two query circuits both perform one oracle call even though the reply has two bits. Their gate counts differ while their query count and output law agree.
Facts & Assumptions
Given: The two decision/search task pairs, the maps , and the four-bit query family defined in the Example.
QA task and promise domain: decision tasks require the stated yes/no output only on the disjoint promise pair; search tasks require a witness in the stated relation only on their domain.
Promise query instance and oracle family: each promised instance selects a total function on every address, and one call to its coherent XOR oracle is one query, independent of output width.
Quantum query algorithm: a query circuit applies the specified XOR-oracle calls to its address and target registers.
Exact correctness for promise tasks: exact correctness means the required decision or witness event has probability one on each promised input.
Quantum query complexity: query cost counts designated oracle calls over promised inputs and branches.
Nonoracle quantum gate cost: nonoracle elementary gates are counted separately from black-box oracle calls.
Classical bit-operation cost: address/reply processing and output writing count as Turing transitions, separate from the oracle invocation.
Promise preserving reduction: a total polynomial-time map is a decision promise reduction when it maps source yes-instances to target yes-instances and source no-instances to target no-instances.
Clifford+T gate library and exact matrices: the exact Hadamard matrix is .
Normalized output law for finite quantum query branches: terminal computational-basis weights are finite sums of density-operator diagonal weights over unobserved wires, and the finite branch law is normalized.
Rectangular matrix multiplication and the identity matrix , including zero-sized shapes: matrix products are computed by finite row-by-column sums and the identity matrix acts as the multiplicative identity.
Finite registers and their ordered computational bases and The computational basis is orthonormal give the orthonormal computational basis of each factor. Equip their ordered tensor product with the product inner product of Ordered tensor registers, their inner product, and wire permutations; then The product basis is orthonormal and tensor dimensions multiply makes the bit-string product basis orthonormal.
Dirac Notation Conversion: for the root pairing, linear in its first argument, .
A unit-vector outer product is a density operator: the rank-one projector of a unit vector is a density operator.
Verification
A multitape machine computes by copying twice, using transitions under [F7], so is total and polynomial time. Moreover, and , giving and . Thus is a promise-preserving reduction by [F8]. No image condition is needed for source strings outside .
For the search reduction, the only promised source input is , and . Every valid target witness is , so is either or and satisfies . Both maps are total as defined on all binary strings, even though witness validity is required only on the promise.
For every four-bit , the table assigns one two-bit value to address 0 and one to address 1, so is total on its two-address domain. Starting at target , the oracle call at address 0 returns ; it is one invocation and therefore one query by [F2]–[F3].
The full output state after the oracle call is the basis vector , which is a unit vector by orthonormality [F12]. Its rank-one projector is a density operator by [F14]. For output word and remaining address bit , the product basis is orthonormal by [F12], so exactly when and is zero otherwise. The projector formula [F13] gives ; root first-linearity and conjugate symmetry therefore give . Summing over the unmeasured address bit as in [F10] gives output weight one at and zero elsewhere. If the rule answers yes; if it answers no, so the solver is exact on the promise by [F4]. For off-promise the same rule outputs no, but the decision task imposes no condition there; the two total completions assigning either answer on these inputs agree on .
The matrix in [F9] satisfies by finite row-by-column multiplication [F11]. Therefore the two extra gates in the second circuit return the first target bit to its initial value before the same oracle call. The target entering is again , so both query circuits have the same output law and one query; their nonoracle gate counts are 0 and 2 by [F5]–[F6].
Step 1.1 gives the reduction's linear transition bound in the table. In either query circuit, the fixed two-bit reply and one-bit output rule take transitions. These transition counts are separate from the one oracle query and from the quantum gate counts by [F7].
Depends on
- QA task and promise domain
- Promise query instance and oracle family
- Quantum query algorithm
- Exact correctness for promise tasks
- Quantum query complexity
- Normalized output law for finite quantum query branches
- Nonoracle quantum gate cost
- Classical bit-operation cost
- Promise preserving reduction
- Clifford+T gate library and exact matrices
- Finite registers and their ordered computational bases
- The computational basis is orthonormal
- Ordered tensor registers, their inner product, and wire permutations
- The product basis is orthonormal and tensor dimensions multiply
- Dirac Notation Conversion
- A unit-vector outer product is a density operator
- Rectangular matrix multiplication and the identity matrix $I_n$, including zero-sized shapes
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
72 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
- Ronald de Wolf, Quantum Computing: Lecture Notes (standard reference, not scraped)
- Andrew M. Childs, Lecture Notes on Quantum Algorithms (standard reference, not scraped)
- John Preskill, Quantum Information, Chapter 6: Quantum Algorithms (standard reference, not scraped)