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 linear-systems state-output task
Definition
Let be a finite-dimensional linear map, , and let , where is the image defined in Kernel and image of a linear map. The quantum linear-systems state-output task (QLSP) is to prepare the normalized domain-register state where is the Moore–Penrose pseudoinverse. By Every linear map between finite-dimensional real or complex inner product spaces admits a singular value decomposition, write in left singular vectors; the promised support gap is a supplied rational or exactly represented such that every with has singular value . The input includes a costed unitary mapping its designated all-zero input to in the codomain register, tensored with a fixed work state. Its inverse, controlled access, and resource coordinates are specified in the separate HHL access model. If is multiplied by , the normalized representative is multiplied by , so its pure-state ray is unchanged. The task returns a quantum state (and may return a success flag); it does not promise a classical list of coordinates.
Depends on
- The Moore--Penrose pseudoinverse $A^+$ as the solution of the four Penrose equations
- Every finite real or complex matrix has a unique Moore--Penrose pseudoinverse
- Every linear map between finite-dimensional real or complex inner product spaces admits a singular value decomposition
- Kernel and image of a linear map
- Finite registers and their ordered computational bases
- Pure state and ray
- Dirac Notation Conversion
Used by
- HHL finite sine-window phase-estimation algorithm Algorithm
- State preparation does not print all coordinates Counterexample
- Block-encoded QLSP input and singular-gap promise Definition
- Childs–Kothari–Somma sparse QLSP oracle model Definition
- HHL state-preparation and simulation access model Definition
- Ideal inverse amplitude and HHL postselection probability Lemma
- Normalization and nonzero success weight of the supported pseudoinverse target Lemma
- Normalization is stable under a small flagged-vector error Lemma
- The QLSP target is nonzero Lemma
Dependency tree · two levels
26 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
- Aram W. Harrow, Avinatan Hassidim, and Seth Lloyd, Quantum algorithm for linear systems of equations (standard reference, not scraped)
- Andrew M. Childs, Robin Kothari, and Rolando D. Somma, Quantum algorithm for systems of linear equations with exponentially improved dependence on precision (standard reference, not scraped)
- Andrew M. Childs, Lecture Notes on Quantum Algorithms (standard reference, not scraped)