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.
HHL state-preparation and simulation access model
Definition
For a Hermitian on a finite-dimensional register, with operator norm as in The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||, the HHL access instance supplies: (i) a unitary with for a fixed normalized work state (which may be ) and declared costs for and any controlled forms used; (ii) for every requested real and tolerance , a controlled simulation circuit with operator-norm error at most from , and separately declared inverse/negative-time costs; and (iii) separate actual resource functions , , for each forward or inverse sine-table preparation, for its one-time classical table generation/data bits, , , , , and , and costs for reversible arithmetic, registers and finite-precision gate synthesis. Here is the negative-sign Fourier circuit and its positive-sign inverse, is the per-attempt reversible decode/filter arithmetic cost, and are the per-call reflection and well-verification costs. These functions count the stated circuit implementation in the chosen gate/access model; they assert no polylogarithmic bound on table generation or rotation synthesis. The positive exponential sign is the OP5 convention. An implementation of from matrix entries or a sparse oracle is additional data and must include its own proof and cost. A bare matrix, sparsity promise, or list of amplitudes is not a circuit. A rational scale may be supplied; after replacing by , the supported gap gives .
Clean-workspace simulation mode. The original full-operator-norm access mode remains admissible. Alternatively, supply a unitary dilation with a fixed clean-work embedding and , including arbitrary timing/control/reference registers. The ideal operation leaves this simulator workspace in zero; other ideal HHL operations do not touch it. Actual output work may be dirty. Supply actual circuit inverses and controls and charge their full workspace and query costs. Unitary hybrids on a preserved clean-work subspace proves the same clean-input error for the actual adjoint, coherent controls and arbitrary references, and proves accumulation along the ideal all-clean trajectory. The inverse used in HHL uncomputation/amplification is the literal reverse physical circuit, not a separately approximated negative-time routine. Include simulator work in the joint output comparison and the ideal all-zero algorithm registers. A full-space error on arbitrary dirty inputs is neither required nor inferred in this alternative mode.
Depends on
- Quantum linear-systems state-output task
- The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||
- Controlled Unitary Access
- Inverse Unitary Access
- Circuit-family and computation cost model
- Hamiltonian simulation error and resources
- Unitary hybrids on a preserved clean-work subspace
Used by
Dependency tree · two levels
33 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)