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Robust one-step OAA including ancilla leakage
Statement
Let be a nonzero finite-dimensional system space, let be the complete clean-ancilla register, let , and put , . Suppose is unitary, , is unitary, and . For one has the clean-input isometry bound The estimate includes residual ancilla leakage; it does not assert exact cleanup for nonzero .
Facts & Assumptions
Given: The finite system and ancilla spaces, the stated block condition, unitaries , and .
One-step oblivious amplitude amplification fixes the chronological circuit .
Oblivious ancilla reflection: for the projector onto the entire clean coefficient/work ancilla, tensored with identity on the system.
Projector Reflections Are Hermitian Unitary Involutions: is a unitary involution.
Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces: a unitary preserves every vector norm.
The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||: the operator norm is the maximum norm on unit vectors.
The inner-product norm is definite, homogeneous, and satisfies the triangle inequality and Cauchy–Schwarz: , with equality exactly for linearly dependent vectors: the vector norm is homogeneous, satisfies the triangle inequality, and obeys Cauchy–Schwarz.
Ordered tensor registers, their inner product, and wire permutations and Tensor products of finitely many linear maps: product registers have the product inner product and acts factorwise.
Every finite-dimensional real or complex inner product space has an orthonormal basis: every finite-dimensional inner-product space has an orthonormal basis.
Finite registers and their ordered computational bases and The computational basis is orthonormal: the distinguished clean register vector is a unit vector. Together with [F8], the clean injection is an isometry; Finite-dimensional linear isometries satisfy the adjoint identity gives , and An isometric quantum encoding gives an orthogonal code projector makes the orthogonal projection onto its image.
Proof
Given: As in Facts & Assumptions.
By [F10], and is an orthogonal projection. By the circuit order in [L1], the factors in are unitary by [F2]–[F4], so is an isometry. Put . By [F1] and the minus sign in , . Write . For every unit vector , , so by [F5]. For each endomorphism of the nonzero space , Cauchy–Schwarz gives (with immediate), hence . The adjoint identity interchanges the unit vectors, so ; in particular and .
Since , . For every unit vector, apply the vector triangle inequality [F6] and [F7] to these three terms; using and from [F4] gives . Maximizing over unit vectors by [F5], for .
Let . Since and by [F10], and . Hence both cross terms vanish in , and because and are isometries. Thus and by [F7].
Set by step 2.1. For every unit vector , , so . Since , ; the vector triangle inequality [F6] and [F7] therefore give for unit . Maximizing by [F5], . Thus .
From , for every unit the vector triangle inequality [F6] and the isometry of in [F10] give . Maximizing by [F5] and using yields .
For any finite reference space , choose an orthonormal basis by [F9] and write . By [F8], . Thus the same clean-input isometry bound holds with any finite reference, including entangled inputs.
Depends on
- One-step oblivious amplitude amplification
- Oblivious-amplification block identity
- Oblivious ancilla reflection
- Projector Reflections Are Hermitian Unitary Involutions
- The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||
- The operator norm is submultiplicative and satisfies ||T^*T|| = ||T||^2
- The inner-product norm is definite, homogeneous, and satisfies the triangle inequality
- Cauchy–Schwarz: $|\langle u,v\rangle|\leq\lVert u\rVert\lVert v\rVert$, with equality exactly for linearly dependent vectors
- Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces
- Ordered tensor registers, their inner product, and wire permutations
- Tensor products of finitely many linear maps
- Every finite-dimensional real or complex inner product space has an orthonormal basis
- Finite registers and their ordered computational bases
- The computational basis is orthonormal
- Finite-dimensional linear isometries satisfy the adjoint identity
- An isometric quantum encoding gives an orthogonal code projector
Used by
- Qubitized Hamiltonian simulator Algorithm
- Segmented Taylor LCU simulator Algorithm
- Qubitized simulation correctness Theorem
- Segmented Taylor error and resources Theorem
Dependency tree · two levels
56 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, Chapter 28 §28.3 (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes, §9.3 and Exercise 9 (standard reference, not scraped)