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Operator error for the finite sine-prefix rotation table
Statement
Let , and let and be as in Finite sine-window phase state. In the binary prefix tree, order the register bits from root to leaf. At level , each interval node has midpoint and split . Apply to the next bit, controlled on the preceding prefix that names , encoding bit as the left child and bit as the right child. Starting from , this ideal prefix circuit prepares . If a finite state-preparation circuit contains controlled rotations and each implemented rotation differs from its ideal rotation by operator norm at most , the product unitary differs from the ideal product by operator norm at most . In the OP5 table variant let , and , so the preparation error is less than ; using the same bound for its inverse gives the stated unpreparation cost.
Facts & Assumptions
Given: A finite list of controlled rotations and a per-rotation operator-error bound.
Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces: unitary operators preserve vector norm.
The inner-product norm is definite, homogeneous, and satisfies the triangle inequality: the norm of a finite sum is at most the sum of the norms.
Sine chord and linear bounds: for , and for .
Parity and the Pythagorean identity for sine and cosine: sine is odd and .
The addition formulas for sine and cosine: the sine and cosine addition formulas hold; substituting them into the displayed rotation matrices gives the corresponding angle-addition rule.
Finite sine-window phase state: the leaf weights are and the target amplitudes are .
Sine-window normalization and positive prefix weights: , and every nonempty interval has positive mass.
Proof
The real -rotation matrix is . For any unit vector , [F5] and [F4] give Taking the supremum over unit and using [F3] and [F4] yields . A controlled rotation is block diagonal with identity and this rotation on its control subspaces, so its operator error obeys the same bound.
For each leaf , put . If , [F3] gives ; if , [F8] reduces positivity to and the same bound. Thus each leaf weight is positive, and [F7] makes every split ratio lie in . The rotation sends to , so its branch amplitudes are exactly the square roots of the right- and left-child mass fractions. Induction from the root shows that leaf has amplitude , by [F6] and [F7]. With left encoded by , interval leaf has computational label . Its amplitude equals that of label because and [F8] gives . Hence the ideal circuit prepares .
For products and , insert and subtract one factor at a time. This writes their difference as a sum of terms, each containing one between unitary products. By [F1] the outer products preserve norm, and [F2] bounds the sum by . For , and this is less than . Applying the same estimate to the inverse rotation list, whose ideal angles are negated and whose synthesis uses the same per-angle tolerance, gives the same bound for inverse preparation.
Depends on
- Controlled Unitary Access
- Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces
- The inner-product norm is definite, homogeneous, and satisfies the triangle inequality
- Sine chord and linear bounds
- Parity and the Pythagorean identity for sine and cosine
- The addition formulas for sine and cosine
- Finite sine-window phase state
- Sine-window normalization and positive prefix weights
- Cofunction, supplementary, quarter-turn, and reflection identities for the six trigonometric functions
Used by
Dependency tree · two levels
39 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
- Andrew M. Childs, Lecture Notes on Quantum Algorithms (standard reference, not scraped)