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.
Classical bit-operation cost
Definition
For a classical query algorithm Classical query algorithm, bit-operation cost is the number of transitions of a declared multitape Turing machine over a fixed finite alphabet; the -tape transition reads and writes one symbol on each of its tapes and moves each head once per transition (Multitape and nondeterministic Turing machine variants). It includes random-bit generation, any encoding work actually performed by that machine on declared public data or received replies, address formation, reading and writing every bit of an oracle reply, comparison/postprocessing, and writing the classical output. The abstract instance encoding in Input encoding and size for algorithmic tasks fixes the size parameter; it supplies neither a readable hidden input nor an encoding procedure to execute. The fair-bit machine convention is supplied by Probabilistic polynomial time machine interface. The oracle invocation itself is one separately counted query action; its returned bits are not free to process.
For a query with an -bit address and a -bit reply, the machine's charged work includes forming the address and processing the reply symbols. A claimed time bound also specifies whether it is worst-case over promised inputs and random tapes, as in Probabilistic polynomial time machine interface. Query, nonoracle quantum gate, measurement, and classical bit costs remain distinct.
Depends on
Used by
- Budgeted Simon recovery with explicit failure branch Algorithm
- Known-count search by randomized Grover iteration Algorithm
- Median confidence amplification for amplitude estimation Algorithm
- QFT-based amplitude estimation Algorithm
- Quantum counting by uniform-state amplitude estimation Algorithm
- Rational-interval rounding of a counting output Algorithm
- Relative approximate counting with unknown marked count Algorithm
- Relative estimation of a promised coherent success probability Algorithm
- Anyon compiler resource ledger Definition
- Shor factoring cost-accounting branches Definition
- Promise, query and cost-model examples Example
- Finite exact comparison of real cyclotomic values Lemma
- Terminating certified rounding for a counting estimate Lemma
- Bit cost of exact known-count iteration selection Proposition
- Classical bit cost of randomized known-count search Proposition
- Amplitude-estimation additive error and success probability Theorem
- Bit cost of phase-sample rational reconstruction Theorem
- Explicit median confidence guarantee for amplitude estimation Theorem
- F2 row reduction returns the unique Simon mask Theorem
- Gate and bit cost of modular multiplication and powering Theorem
- Promise-preserving reduction composes with a query solver Theorem
- Quantum counting error and boundary cases Theorem
- Quantum counting query complexity Theorem
- Rejection sampling is uniform, almost surely terminating, and has expected linear bit cost Theorem
- Relative approximate counting success guarantee Theorem
- Relative probability estimation with a charged finite cap Theorem
- Separate order-finding query, gate, and bit costs Theorem
- Separate Shor factoring bit, gate, and query costs Theorem
- Simon recovery succeeds with probability at least 1-delta Theorem
Dependency tree · two levels
10 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)