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Linear Combinations of Unitaries and Taylor Simulation
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Algebraic Closure, Embeddings, and Separability
- Algebraic Extensions, Extension Degree, and Finite Fields
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Channels, Kraus, Choi, and Stinespring Representations
- Circuit Syntax, Denotational Semantics, and Measurement
- Classical and Quantum Error-Correcting Codes
- Clifford+T Exact and Approximate Synthesis
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Coordinate and Path Transport
- Complex Differentiability and the Cauchy–Riemann Equations
- Complex Norms and Realification
- Complexification, Realification and Real Structures
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- Connectedness
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Continuous-Gate Universality and Exact Synthesis
- Continuous-Time Quantum Walks
- Controlled Gates, Phase, and Entanglement
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Cyclic Groups and Direct Products
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Dimensional Normed Spaces and Riesz Lemma
- Finite-Dimensional Complex Inner-Product Spaces and Matrix Interfaces
- Formal Languages, Encodings, and Decision Problems
- Foundations of the Real Numbers for Analysis
- Free Modules, Exact Sequences, Projective and Injective Modules
- Fundamental Trigonometric Identities
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Hamiltonian Simulation and Product Formulas
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Recurrences and Rational Generating Functions
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Metric Spaces
- Modules, Submodules, Quotient Modules and the Isomorphism Theorems
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Order, Zorn's Lemma, and the Axiom of Choice
- Partitions of Unity and Paracompactness
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- Properties of the Integral and the Working FTC
- Pure and Mixed States, Ensembles, and Schmidt Decomposition
- Qubits, Bloch Sphere, Pauli Algebra, and One-Qubit Gates
- Registers, Tensor Products, and Partial Trace
- Relations, Functions, and Quotients
- Resource Bounds and Machine Invariance
- Reversible Computation, Ancillas, and Coherent Oracles
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Splitting Fields
- State Preparation, Isometry Synthesis, and Limits
- Strongly Continuous Semigroups and Hille Yosida
- Subspaces, Products, and Quotients
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tensor Products of Modules
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Exponential Function
- The Fundamental Theorem of Algebra
- The Fundamental Theorem of Finite Abelian Groups
- The Galois Correspondence
- The Logarithm and General Powers
- The Riemann Integral: Definition and Integrability
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Turing Machines, Configurations, and Computation
- Uniform Circuit Families, Promise Problems, and Complexity
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
An LCU input is a finite ordered decomposition together with complete PREPARE, SELECT, inverse, controlled-access, and cost contracts. Its clean-ancilla projected block is the represented matrix divided by the coefficient sum; the zero branch has an input-dependent postselection weight. One-step oblivious amplification uses the explicit reflection and a tracked global phase. The Taylor construction expands ordered products, adds cancelling identity terms to set the LCU scale, and segments time so robust clean-input error and retained-ancilla leakage accumulate within the tolerance. Query, gate, width, coefficient, table, inverse, control, and classical generation costs remain separate. Continuous-rotation preparation bounds do not provide finite-gate synthesis or coefficient bit-time by themselves.
The certified Taylor scheduler uses interval bounds without exact real-zero tests and chooses its truncation order by rational factorial comparisons. Its term-query bound assumes explicitly supplied coherent indexed term selection; assembly from separate controlled terms costs up to individual calls, with routing and phase costs recorded.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Pure-state trace distance is bounded by vector error
Statement
Let be a finite-dimensional complex inner-product space and let be unit vectors. Write and using the Dirac convention of Dirac Notation Conversion, and define their trace distance by , where is the trace norm of Trace Norm. Then
Facts & Assumptions
Given: A finite-dimensional complex-inner-product space and unit vectors .
Dirac Notation Conversion: sends to , and its coordinate matrix in an orthonormal basis is .
The norm induced by a real or complex inner product: for the root inner product, linear in its first argument.
Cauchy–Schwarz: , with equality exactly for linearly dependent vectors: , with equality exactly when the vectors are linearly dependent.
Trace Norm: is the sum of the singular values of , counted on its finite-dimensional domain.
Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely: a finite-dimensional normal endomorphism has an orthonormal eigenbasis.
Proof
Given: As in Facts & Assumptions.
Put and . By [F3], . If , equality in Cauchy–Schwarz makes a unit scalar multiple of , so and .
Suppose and set . The Dirac convention makes , and direct expansion gives . In the orthonormal basis of their span, has matrix ; it is zero on the orthogonal complement. This Hermitian matrix has trace and determinant , hence eigenvalues . By [F4]–[F6], , so .
For either case, , while . Thus , including the case from step 1.1.
Clean-ancilla zero-branch postselection
Definition
Let be a finite register with distinguished unit computational-basis vector (unit by The computational basis is orthonormal), let be a finite-dimensional complex-inner-product space, and define the isometry by . The product inner product makes 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. On elementary tensors this is by the convention of Tensor products of finitely many linear maps. For a unit vector , define its zero-branch vector , zero-branch weight , and complementary-branch weight . When , the conditional system vector is ; when , no conditional vector is assigned. This definition fixes only the clean-ancilla two-outcome branch rule used on this page; it makes no physical realization claim.
Partial trace contracts the trace norm on Hermitian operators
Statement
Let be finite-dimensional complex inner-product spaces and let be an endomorphism of . Then The trace norm and partial trace are those of Trace Norm and Partial trace over a finite tensor factor. If either factor is zero-dimensional, both sides are zero.
Facts & Assumptions
Given: Finite-dimensional complex-inner-product spaces and a Hermitian endomorphism of .
Trace Norm: is the sum of the singular values of .
Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely: a finite-dimensional normal endomorphism has an orthonormal eigenbasis.
Partial trace over a finite tensor factor: in ordered orthonormal product bases, .
The partial trace is characterized by the trace pairing and is basis-independent: for every endomorphism of .
Tensor products of finitely many linear maps: on elementary tensors.
Ordered tensor registers, their inner product, and wire permutations: the product inner product and ordered product basis are the finite tensor-product convention.
The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||: on a nonzero domain.
Every finite-dimensional real or complex inner product space has an orthonormal basis: each finite-dimensional inner-product factor has an orthonormal basis.
The adjoint is characterised by and Real and complex inner-product spaces and their induced length: , and the root inner product is conjugate-symmetric.
The basis-independent trace of an endomorphism of a finite-dimensional vector space: trace is the sum of diagonal entries in any ordered basis.
Proof
Given: As in Facts & Assumptions.
If either tensor factor is zero-dimensional, then and the claimed inequality follows from the empty coordinate sum in [F4]; assume both factors are nonzero for the rest of the proof. For any Hermitian on a nonzero finite-dimensional complex-inner-product space, [F3] gives an orthonormal eigenbasis with eigenvalues . The adjoint identity [F11] and conjugate symmetry make , so each is real. For every Hermitian with , [F12] gives . Again [F11] makes each diagonal entry real, and [F8]–[F9] put it in . Thus : in the eigenbasis, has eigenvalues , so [F2] its nonnegative square root has eigenvalues , and [F1], [F2], [F12] give the trace norm sum. Equality is attained by the Hermitian contraction acting by on each (and by when ). Hence .
Formula [F4] shows is Hermitian: transposing and conjugating its entry gives . If and , choose an orthonormal basis of by [F10] and write arbitrary and . The product inner product and tensor-map action [F6]–[F7] give by self-adjointness and [F11], so is Hermitian. Also [F6]–[F8] give , so .
For the remaining nonzero-factor case, apply the variational identity in step 1.1 to . For each allowed , [F5] and step 1.2 give , using step 1.1 for the Hermitian contraction . Taking the supremum proves the claimed inequality.
Clean-ancilla postselection has normalized branch weights
Statement
With the notation of Clean-ancilla zero-branch postselection, every unit vector has and . If , the assigned conditional vector is a unit vector; if , then and no conditional vector exists.
Facts & Assumptions
Given: Finite registers , the injection , the projector , and a unit vector .
Clean-ancilla zero-branch postselection: , , and .
Ordered tensor registers, their inner product, and wire permutations: the tensor-product inner product is the product inner product on elementary tensors.
Dirac Notation Conversion, Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces, and Finite-dimensional linear isometries satisfy the adjoint identity: the bra is the adjoint functional for the root-linear-first pairing, and a norm-preserving linear map satisfies .
The norm induced by a real or complex inner product: the squared norm is the self-pairing.
The computational basis is orthonormal: the distinguished computational-basis vector has norm .
Proof
Given: As in Facts & Assumptions.
From the product inner product [F2] and unit norm [F5], for every , so is an isometry by its definition in [F3]. Therefore by [F3]. It follows that is self-adjoint and idempotent, , and .
The two summands are orthogonal because and . Expanding their squared norm by [F4] gives . Both summands are nonnegative, so each lies in .
If , then . If , definiteness of the inner-product norm gives , so normalization is undefined and the definition correctly assigns no conditional vector.
LCU decomposition and access model
Definition
Let be a finite-dimensional complex-inner-product system space and let where , each is unitary, and The finite ordered list is an LCU representation of ; it is part of the input, and a matrix description alone does not supply circuits for any .
Set and let be the -qubit index register, with the one-dimensional case allowed. Its computational indices are . For put when and when . Define the complete SELECT unitary by This basis rule fixes every valid and padded index; it extends linearly to all superpositions and acts as identity on any separately declared work register.
A PREPARE access is a fully specified unitary on the index register and all its declared work registers, with for some phase . The same full unitary, including its action on every nonzero input, determines ; neither an inverse nor a controlled call is implied unless explicitly supplied. The allowed global phase cancels between and in the LCU block. PREPARE work wires are included among the ancillas projected to zero.
For an amplitude-table implementation with entries, the dense fixed-width input length, table reading, arithmetic, and coefficient precision are separate costs. If the continuous-rotation QC24 procedure QC24 State Preparation is used, its source theorem QC24 State Preparation Rotation Level Upper Bound gives bounded-arity gates and serial depth, with at most reusable clean work bits; the table and exact arithmetic costs remain separate. This bound is for continuous rotations. Finite-alphabet synthesis and finite-precision bit-time require separate guarantees. A supplied PREPARE circuit is instead charged by its declared full description, gates, wires, and generation cost.
The LCU block circuit is the complete unitary on all coefficient/work ancillas and the system. The access record separately lists PREPARE, PREPARE, SELECT, SELECT, and every controlled form used, together with their query, gate, wire, coefficient-bit, and classical-description costs under Hamiltonian simulation error and resources and Circuit-family and computation cost model. Unspecified access, inverse access, controlled access, and table loading have no free cost. The zero LCU representation is outside this access model because does not define a normalized coefficient state.
LCU block encoding
Definition
Input: An LCU representation and complete PREPARE and SELECT access from LCU decomposition and access model, including their stated work-register and padded-index behavior. The access record must explicitly supply PREPARE and its cost; an input without that inverse access is inadmissible.
Procedure: On the coefficient/work ancillas and system, apply PREPARE, then SELECT, then the supplied PREPARE. Return the complete unitary . Charge the three calls at their declared costs. No measurement or deterministic state-output guarantee is part of this procedure.
Oblivious ancilla reflection
Definition
Let be the full coefficient and PREPARE-work ancilla register in LCU decomposition and access model, let be the system, and let be the clean injection of Clean-ancilla zero-branch postselection. Set ; An isometric quantum encoding gives an orthogonal code projector makes this the orthogonal projection onto the image of . Its basis formula is , where is unit by The computational basis is orthonormal and the tensor action is that of Tensor products of finitely many linear maps. Define Thus acts as on the clean-ancilla subspace and as on its orthogonal complement; it acts identically on the unknown system state. In the convention of Orthogonal-Projector Reflection and Access Contract, , while that item writes . These signs are distinct inside controlled blocks: if only the controlled is supplied, implement controlled with the exact control- correction of Projector Reflections Are Hermitian Unitary Involutions and charge that gate. A projector-reflection call and its controlled form are explicit access operations, not free consequences of a state vector.
Finite Taylor LCU polynomial
Definition
Let on a finite-dimensional complex-inner-product space, with , real and Hermitian unitaries , and put . For real and integer , define Its ordered product-term LCU list has one empty tuple for , with coefficient and unitary , and for each and ordered tuple has coefficient and unitary . Distinct tuples remain distinct entries even if their product unitaries coincide. The absolute coefficient sum of this listed representation is
Whenever , append two distinct identity entries with coefficients and , where . They leave the represented matrix unchanged and raise the listed absolute coefficient sum to exactly . If , the zero-weight entries may be retained with zero preparation amplitude or omitted. The polynomial, coefficient phases, ordered tuple index, and any numerical precision used to generate them are part of the finite input/access record; no term product, coefficient table, PREPARE circuit, or SELECT circuit is free.
LCU projected-block and postselection correctness
Statement
Let be a finite LCU representation with , let be the unitary from LCU block encoding, and let include every coefficient and PREPARE-work ancilla. Then For every unit input vector , the clean-ancilla zero-branch vector is and its postselection weight, under Clean-ancilla zero-branch postselection, is . If this weight is positive, the conditional system vector is ; if it is zero, the conditional vector is undefined.
Facts & Assumptions
Given: The finite LCU representation, complete PREPARE and SELECT access, explicitly supplied PREPARE access with its declared cost, and a unit system vector .
LCU block encoding: , where PREPARE sends the all-zero ancilla to the coefficient-amplitude state, up to one global phase, and SELECT applies each coefficient phase with its unitary term.
Dirac Notation Conversion: the bra is the adjoint functional, and acts by .
Finite registers and their ordered computational bases: the index register has the declared ordered computational basis, including its one-dimensional zero-qubit case.
Clean-ancilla zero-branch postselection: the zero-branch vector of is and its weight is the squared norm of that vector.
Clean-ancilla postselection has normalized branch weights: the zero and complementary branch weights of a unit vector are in and sum to one; a normalized conditional vector exists only when the corresponding weight is positive.
The computational basis is orthonormal: the computational index basis, including the zero-qubit register's basis, is orthonormal.
Proof
Given: As in Facts & Assumptions.
Write and for (take when ). PREPARE gives from the all-zero ancilla. After SELECT, the th component is . The all-zero matrix element of PREPARE on is by [F1], so the global phase cancels and . Padded invalid indices have zero prepared amplitude. Since this holds for every , it proves the block identity; orthonormality [F5] validates these basis matrix elements.
Apply [F3] to : its zero-branch vector is . Its branch weight is therefore , and [F4] makes this a valid probability in .
If , division of the branch vector by its norm gives . If , the weight is zero and [F4] forbids assigning a normalized conditional vector to that branch.
One-step oblivious amplitude amplification
Definition
Input: A unitary on coefficient/work ancillas and system, explicit inverse access to , the reflection of Oblivious ancilla reflection, and an operator satisfying for the clean injection .
Procedure: Chronologically apply , then , then , then , then . The resulting unitary is The scalar is an explicit phase correction; it is not omitted when this procedure is controlled. The circuit uses two calls, one call, and two reflection calls. A controlled invocation requires the declared controlled forward, inverse, reflection, and phase-correction gates. This procedure makes no measurement and asserts no exact ancilla cleanup for a nonunitary or approximate ; the robust clean-input guarantee is proved separately.
Taylor simulation tail bound
Statement
Let be a finite-dimensional self-adjoint Hamiltonian on a nonzero complex-inner-product space, with , written with real and Hermitian unitaries , and set . For real , integer , and , The Taylor coefficient sum satisfies when . If and , there is a for which the right-hand side is at most .
Facts & Assumptions
Given: A nonzero finite-dimensional complex-inner-product space, the stated self-adjoint decomposition, real , and .
Finite Taylor LCU polynomial: , and .
Finite Hermitian matrix dynamics: is defined by the finite spectral functional calculus on the eigenvalues of .
Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely: a finite-dimensional self-adjoint endomorphism has an orthonormal eigenbasis.
Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces: every unitary term preserves vector norms.
The inner-product norm is definite, homogeneous, and satisfies the triangle inequality: the induced inner-product norm is homogeneous and satisfies the triangle inequality.
The operator norm is zero on the zero domain and otherwise is max_{||v||=1} ||Tv||: the operator norm is the maximum over unit vectors.
The complex exponential by its power series and The complex exponential series converges absolutely for every complex argument: with absolute convergence.
, , and : for real , .
Proof
Given: As in Facts & Assumptions.
By [F1], choose an orthonormal eigenbasis of with eigenvalues . For a unit eigenvector , by [F2]–[F4]. On this basis, [L1] and [L2] make the difference diagonal with scalar entries .
Since , the finite Taylor coefficient sum obeys by [L1] and [F5]. If , [F7] gives .
Put . The absolute scalar-series tail at eigenvalue is at most . Writing and using bounds this by by [F5]–[F6]. If the diagonal error has entries in the eigenbasis and , then its squared output norm is ; an eigenbasis vector attaining the finite maximum gives equality in the operator norm [F4]. Hence the operator norm is . Since , the monotonicity of and on nonnegative reals gives . Taking the maximum proves the stated tail bound.
Assume , so by [F7]. Let . The exponential series gives : its first two terms sum to , while for , with strict inequality for , so the remaining sum is less than . Thus by [F5], and the strict increase and inverse relation in [F7] give . If , gives . If , take . For , has derivative , so it decreases up to and increases thereafter. Since , , hence by [F7]; thus . Also . Therefore so . Hence , using , , and . For the factorial estimate, monotonicity of gives , so . Since , this choice gives a tail at most . In both cases . Since , this is also , the displayed order after changing logarithm bases. Hence has the stated order.
Oblivious-amplification block identity
Statement
Let be the clean-ancilla isometry , let be the orthogonal projection onto its image, and set . Let be unitary and assume . For the chronological circuit , If is unitary, this projected block is . The identity alone gives no bound on leakage outside the clean-ancilla subspace for a nonunitary .
Facts & Assumptions
Given: A finite-dimensional system, a unitary , the clean-ancilla isometry , and .
One-step oblivious amplitude amplification: the chronological operation is , , , , , and .
Oblivious ancilla reflection: projects only the full clean coefficient/work ancilla to zero and is identity on the system.
Projector Reflections Are Hermitian Unitary Involutions: for an orthogonal projection , is a unitary involution; the opposite sign is distinct under control.
Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces and Finite-dimensional linear isometries satisfy the adjoint identity: a unitary is a surjective linear isometry, so ; an isometry satisfies .
An isometric quantum encoding gives an orthogonal code projector: is the orthogonal projection onto the image of an isometry .
Finite registers and their ordered computational bases, The computational basis is orthonormal, and Ordered tensor registers, their inner product, and wire permutations: the clean basis vector is unit and the product inner product makes a linear isometry.
Proof
Given: As in Facts & Assumptions.
Let . By [F3]–[F5], and is the stated orthogonal projection; hence and . By [L1]–[F2], the three-use circuit is the stated unitary circuit with two reflections.
Expand twice inside . Since is unitary, [F3] gives , and [F4] gives . The four terms compress to : respectively, use , , , and . Substituting gives .
If is unitary, then , so the block is . For arbitrary , step 2.1 proves only the compression identity; it contains no estimate for .
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.
Segmented Taylor LCU simulator
Definition
Inputs: A finite list on a nonzero finite-dimensional complex system space, where , and each is a supplied Hermitian unitary; real time and a tolerance , each with a finite exact description. The description of supplies arbitrarily tight rational interval enclosures. Also supply the complete PREPARE/SELECT, inverse, and cost interfaces from LCU decomposition and access model for the Taylor list selected below. For the certified procedure the real descriptions supply arbitrarily tight rational interval enclosures for and , where . Exact coefficient phases and the required unitary/circuit access for the selected list are separate supplied data; interval names alone do not provide them. Arithmetic, refinement, description and generation costs are charged separately. No efficient classical compiler is asserted.
For the indexed term-query implementation, additionally supply the complete unitary for , acting as identity at padded term indices, together with every controlled or inverse form actually used and its separate costs. A call to this coherent multiplexer is one indexed term query. Individual accesses to the separate do not grant this operation: when it is assembled from individual controlled , each multiplexed call uses equality-controlled individual calls, and all label tests, routing, phase gates and work are charged. With an independently supplied Taylor SELECT, only its declared internal resource record applies.
Procedure:
- Refine an enclosure of until and . Refine an enclosure of , intersecting with the known nonnegative half-line, until its width is less than . If , return the exact identity circuit with no oracle calls and the certificate . Otherwise proceed to the segmented branch; no positive lower bound on is needed. These refinements terminate because and the supplied descriptions give arbitrarily tight rational enclosures. No exact equality test on interval-described reals is used; every or input takes the identity branch.
- In the remaining branch put . In the ideal exact-arithmetic variant set . In the certified variant refine an enclosure until its width is less than , then set . Either choice has , , and . Set and . All refinement and segment-count costs are recorded.
- Set , a positive rational lower bound for . Set and successively double until the exact rational comparison holds; compute the factorial by finite integer multiplication and set . This finite scheduler has no real-equality test or unbounded refinement at a fixed failed order. Since , the tail in Taylor simulation tail bound is at most . Its factorial estimate gives the stated logarithmic-over-double-logarithmic order, including the factor of at most two from doubling. Charge the factorial and coefficient arithmetic.
- Expand into the ordered product-term LCU list of Finite Taylor LCU polynomial. The certificate and Taylor simulation tail bound prove analytically. Add two distinct identity terms with , retaining zero-weight padding labels if needed; the matrix is unchanged and the listed norm is exactly . Under the indexed term-query implementation, implement each Taylor SELECT using at most controlled indexed term queries: process tuple positions from down to , condition each call on a valid tuple having that position, and use its term label. Compute/uncompute those labels in charged work registers. This reverse execution order yields the displayed product . Apply the coefficient phase separately and act as identity on padding and unused labels. The adjoint SELECT reverses this sequence and uses the declared inverse calls.
- For each of the segments, allocate a fresh clean register containing the expanded-term index and every PREPARE work wire. Build using the exact coefficient phases and the padded invalid-index behavior. Apply the phase-corrected chronological circuit , with on the complete clean coefficient/work register. Thus the segment unitary is , with two reflection calls, two forward calls, and one inverse call.
- Compose the segment circuits in time order. Retain every segment's coefficient/work register in the output dilation; do not measure or claim exact cleanup. The output is the finite unitary/access-circuit description together with the chosen , coefficient table or generator, and resource record.
The default procedure is uncontrolled. A controlled variant is defined only when controlled access to every component is supplied; the known minus sign is applied as a phase on the outer control, not discarded. If a compiled implementation is used, the per-call operator-norm error bounds must satisfy the certified sum . The exact-access variant has . Every PREPARE, SELECT, inverse, reflection, control, coefficient, table, precision, wire, and gate cost remains explicit.
Segmented Taylor error and resources
Statement
Let be the finite Hermitian-unitary decomposition on a nonzero finite-dimensional complex-inner-product space in Segmented Taylor LCU simulator, let , let , and let . For the segmented branch, let be the segment count selected by that algorithm. It satisfies and ; put . Choose by the factorial-doubling rule in that algorithm. Let be its complete circuit or access-circuit unitary, including all work registers, and suppose the sum of its per-call operator-norm error bounds is at most . Let append all initial work registers in zero, and let append the same work registers in zero to an ideal output. Then For every finite reference space and every input density operator on system plus reference, tracing out the work registers gives output states satisfying The certified small-time branch returns identity with error at most ; it is exact when or . No operator-norm bound on arbitrary nonzero initial work registers or exact cleanup of the output registers is claimed.
On the segmented branch the segment count is , and the truncation order obeys . With the explicitly supplied controlled indexed term multiplexer of the algorithm, the construction uses at most indexed term queries. If each such multiplexed call is instead assembled from the individually supplied controlled , the corresponding bound is individual term calls; equality tests, routing, coefficient phases and their inverse/control operations remain separately charged. Independently supplied Taylor SELECT access has only its declared internal query/gate cost, with no inferred -call implementation. It uses exactly PREPARE calls, PREPARE calls, SELECT calls, SELECT calls, and reflection calls. If the expanded Taylor list has ordered terms and each segment keeps a fresh index register, the index width is qubits and the retained registers' total index width is . All PREPARE table, internal work, term gates, coefficient bits, circuit description, control, inverse, and classical generation costs are charged separately under Hamiltonian simulation error and resources.
Facts & Assumptions
Given: The exact finite term list and access model, the specified , and a compiled unitary whose summed operator-norm error is at most .
Segmented Taylor LCU simulator: its interval procedure obtains a rational lower bound with ; the identity branch certifies , and the other branch chooses and factorial doubling chooses using , where . In the segmented branch, each segment uses fresh clean coefficient/work registers, pads the Taylor LCU to norm , applies , retains all work registers, and has certified sum of per-call errors .
Finite Taylor LCU polynomial: the Taylor expansion has listed coefficient norm and the two padding coefficients cancel in the represented operator.
Taylor simulation tail bound: , , and . Its proof supplies the scalar exponential series, the factorial estimate , and the factorial-order choice argument.
LCU projected-block and postselection correctness: PREPARE/SELECT/PREPARE has clean-ancilla block for its listed LCU.
Oblivious-amplification block identity: the projected block of is when the input block is .
Robust one-step OAA including ancilla leakage: if for a unitary , the phase-corrected circuit on clean input has isometry error at most , including leakage.
Hamiltonian simulation error and resources: operator-norm simulation error and query, gate, controlled/inverse, width, coefficient-bit, description, and classical-generation costs are distinct coordinates.
Density operator: a density operator is a nonnegative trace-one endomorphism of a nonzero finite-dimensional complex-inner-product space.
A non-negative operator is equivalently self-adjoint with nonnegative eigenvalues, a positive semidefinite matrix in an orthonormal basis, or an operator of the form S^*S: a nonnegative endomorphism has an orthonormal eigenbasis with nonnegative eigenvalues.
Partial trace over a finite tensor factor: the partial trace is the finite coordinate contraction over the discarded factor.
Ordered tensor registers, their inner product, and wire permutations: tensor factors have the declared product inner product and ordered product basis.
Pure-state trace distance is bounded by vector error: for unit vectors , .
Partial trace contracts the trace norm on Hermitian operators: partial trace does not increase the trace norm of a Hermitian difference.
The basis-independent trace of an endomorphism of a finite-dimensional vector space: trace is the sum of diagonal entries in any ordered basis.
Every finite-dimensional real or complex inner product space has an orthonormal basis: a finite-dimensional inner-product reference space has an orthonormal basis.
Proof
Given: As in Facts & Assumptions.
On the identity branch let . In an orthonormal eigenbasis as in [F2], each Hamiltonian eigenvalue satisfies . Its scalar-series error obeys . The diagonal norm calculation in [F2] proves , and the error is zero if or . Otherwise step 2 chooses a finite with ; no lower bound on is needed. Hence , and cancelling padding makes the norm exactly without changing .
By [F3], the padded circuit has block . The uncorrected amplified block is by [F4], so the explicit phase correction in [L1] gives the corresponding opposite-sign block; [F5] supplies the needed full isometry estimate including leakage. The Taylor-tail rule gives , and . Apply [F5] with to obtain a clean-input isometry error at most for each segment, including any finite reference and all earlier retained registers.
By [L1], the scheduler uses the positive rational , where . The loop terminates because tends to infinity. Since and , ; hence . For , the inequalities and give , hence . Therefore . Monotonicity of gives , so . The least power of two at least is less than and already meets the factorial comparison, so the scheduler stops at some . Thus . Since and , this is . The rule uses only a finite integer loop, and its cost is a separate classical coordinate. For the error estimates, because .
The ideal segment maps each input to the same system evolution and a fresh zero register. Telescoping the compositions, every intervening exact segment is an isometry and has norm , so the total access-circuit isometry error is at most . The ideal system factor is by [F6].
Replacing the exact access calls by their compiled unitaries changes the full circuit in operator norm by at most the sum of their per-call errors: expand the product difference as a telescoping sum and use norm for each unitary factor. The declared sum is at most by [L1]. The triangle inequality therefore gives .
First take a pure unit input, including any finite reference. The segmented isometry bound in step 3.1, or the identity-branch bound in step 1.1 tensored with that reference, gives vector error at most . For the identity branch, write a system-reference vector as in an orthonormal reference basis [F15]; [F11] makes its squared error the sum , justifying that extension explicitly. Then [F12] bounds the joint pure-state trace distance by . The difference of the two joint density operators is Hermitian, so applying partial-trace contractivity [F13] over all work registers preserves this bound.
For a general input density operator, [F8]–[F9] give an orthonormal eigenbasis with nonnegative eigenvalues ; [F14] and trace one imply . Take an auxiliary reference space with orthonormal basis , which exists by [F15], and set . By the product inner product [F11], . In the product basis, its projector has entries . The coordinate rule [F10] gives , which is if and otherwise, exactly the matrix of . Thus purifies . Apply step 4.1 with the original reference and this purifying reference, then trace out the work registers and the purifying register; [F13] again preserves the bound. Therefore the reduced outputs for differ in trace distance by at most .
In each segment the chronological OAA circuit has two forward factors, one factor, and two reflections [L1]. Expanding each gives three PREPARE and three PREPARE calls, two SELECT and one SELECT call per segment. In the indexed term-query implementation [L1], a length- tuple acts by processing its labels in reverse order, so its conditionally active positions implement exactly . The phase and invalid-label rules are separately specified. Thus each SELECT or its adjoint uses at most controlled indexed term calls and the total is at most . If only individual controlled are used to assemble a multiplexer, apply the th unitary conditioned on label equality, for every : exactly one block is active on each valid label, so this implements the same direct sum with at most individual calls per indexed call. This gives individual calls with the declared label/routing/phase costs; no such decomposition bound is inferred for an arbitrary supplied SELECT. The expanded coefficient list has ordered terms and two retained padding labels, giving the stated widths. Internal work and all other resource coordinates are charged as in [F7]. The identity branch has no queries or retained segment registers.
5 · Examples, counterexamples and false statements
None yet.
Sources
- John Watrous, The Theory of Quantum Information, §1.1.3, Eqs. (1.181)–(1.184)
- Ronald de Wolf, Quantum Computing: Lecture Notes, Appendix A.5
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, Chapter 28 §28.3
- Ronald de Wolf, Quantum Computing: Lecture Notes, §9.3
- John Watrous, The Theory of Quantum Information, §1.1.3, Eq. (1.183)
- Ronald de Wolf, Quantum Computing: Lecture Notes, §9.3.1
- Ronald de Wolf, Quantum Computing: Lecture Notes, §9.3 and Exercise 9
- John Watrous, The Theory of Quantum Information, §1.1.3, Eqs. (1.181)–(1.183)