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.
Coherent finite sampler and observable value
Definition
Let be a finite nonempty set with probability law , , and let the value register contain an exact finite encoding of a real function , where are finite rationals. A coherent finite sampler for is an explicitly supplied finite-dimensional unitary on ordered sample, value, and work registers such that where the sample labels are distinct computational-basis vectors and each work state has norm one. Zero-probability labels may occur and need no special branch. The registers and their order use Finite registers and their ordered computational bases and Ordered tensor registers, their inner product, and wire permutations; each output is a pure state in the sense of Pure state and ray. The separate item Measurement law of a coherent sampler verifies the induced measurement law.
The access contract lists the actual circuits or oracle interfaces for , , controlled and controlled , value decoding, reversible arithmetic, any coherent predicate and controlled rotation, and the reflections used by the chosen estimator. Their availability is explicit under Controlled Unitary Access and Inverse Unitary Access. A forward unitary alone does not grant an inverse or a controlled call.
The resource record follows Circuit-family and computation cost model: charge state preparation, inverse and controlled access, data loading, value comparison and arithmetic, controlled-rotation synthesis and precision, good-state and initial-state reflections, gates, width, ancillas, and classical postprocessing separately. The state-preparation circuit and its costs are inputs; a state description is not a free QRAM or preparation oracle.
Depends on
Used by
- Amplitude-estimation expectation estimator Algorithm
- Variance-aware quantum Monte Carlo Algorithm
- Sample-only access is not coherent sampler access Counterexample
- Bernoulli mean as a good-state probability Example
- Dyadic positive-mean estimator under an L2 bound Lemma
- Measurement law of a coherent sampler Lemma
- Coherent query-to-circuit cost translation Theorem
- Quantum bounded-expectation guarantee and query cost Theorem
- Variance-aware quantum Monte Carlo guarantee Theorem
Dependency tree · two levels
44 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
- Ashley Montanaro, Quantum speedup of Monte Carlo methods, Sections 2–3 (standard reference, not scraped)
- John Watrous, The Theory of Quantum Information, Chapter 2 (standard reference, not scraped)
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, Section 19.3 (standard reference, not scraped)