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Quantum-Walk Search and Element Distinctness — Examples
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
- Boolean Circuits and Nonuniform Complexity
- Bounded Linear Operators and Quotient Spaces
- Circuit Syntax, Denotational Semantics, and Measurement
- Clifford+T Exact and Approximate Synthesis
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Norms and Realification
- Complexification, Realification and Real Structures
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Conditional Distributions and Regular Conditional Probability
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- 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
- 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
- Discrete Quantum Walks and Szegedy Theory
- 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 Fourier Analysis and the Fast Fourier Transform
- 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
- Further Trigonometric Identities and Inverse Functions
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- 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
- Markov Kernels and Markov Chains
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measurements, POVMs, and Instruments
- Measures and Their Basic Properties
- 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
- pi: the Equivalent Characterizations
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Pure and Mixed States, Ensembles, and Schmidt Decomposition
- Quantum Fourier-Transform Circuits
- Quantum Phase Estimation
- Quantum-Walk Search and Element Distinctness
- Qubits, Bloch Sphere, Pauli Algebra, and One-Qubit Gates
- Recurrence Transience and Hitting Times for Markov Chains
- 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
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Splitting Fields
- Stationary Markov Chains and Ergodic Limits
- Strongly Continuous Semigroups and Hille Yosida
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tensor Products of Modules
- 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 Lebesgue Integral and the Convergence Theorems
- The Polynomial Hierarchy and Relativization
- The Riemann Integral: Definition and Integrability
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Trigonometric and Oscillatory Examples in One Variable
- Turing Machines, Configurations, and Computation
- Uniform Circuit Families, Promise Problems, and Complexity
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
The examples compute two small lazy Johnson spectra and marked fractions, then specialize the unique-collision probability and balanced setup/update costs. The counterexample separates a one-call coherent value oracle from ordinary two-wire circuit size and spells out how random-access memory changes the charged gate model.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
One oracle query can require many ordinary gates
Statement refuted
For each , let be parity, , and consider its coherent XOR oracle
In the value-oracle query model this is one oracle call. In the ordinary circuit model with bounded-arity two-wire gates, every exact implementation using product clean ancillas requires at least two-wire gate occurrences that connect the address wires to the target component. By contrast, in the declared random-access-memory model of Random-access quantum-memory gate model, one addressed swap reads the precomputed parity bit into a clean scratch location; two such calls with an intermediate copy restore memory and implement the XOR action, with the constant number of RAM calls charged separately. Memory construction and maintenance remain separate costs. Thus a query count alone does not bound ordinary gate count, and unit-cost QRAM access is a distinct model.
Facts & Assumptions
Given: The coherent function-oracle action, the ordinary finite circuit gate-occurrence convention, and the separate random-access memory gate model.
Coherent XOR function oracle: the value oracle maps to and one declared oracle call is one query.
Finite circuit resource accounting: ordinary gate size counts each gate occurrence separately, and a bounded-arity gate acts on only its declared wires.
Random-access quantum-memory gate model: a random-access memory gate swaps the addressed memory bit with a target in one model-defined gate-time unit, with memory construction and updates separately charged.
Proof
The parity oracle is exactly one application of the supplied , so its query count is one by [F1]. In an ordinary circuit, form the interaction graph whose vertices are all circuit wires and whose edges join the two wires acted on by each two-wire gate occurrence. If the target's connected component omitted an address bit, then no gate couples that bit to the target or to any intermediary on its component; the circuit factors across this separation, making the target output independent of the omitted bit. This contradicts parity's dependence on each input bit: fixing the other bits and changing the omitted bit changes the target. Hence the graph contains a connected subgraph joining the target and all address wires. Any connected graph containing these distinct terminals has at least edges, even if it also contains ancilla vertices; each edge comes from a gate occurrence.
For the explicit upper-bound constructions, choose an ordinary gate alphabet containing CNOT, with basis action ; this is an additional model choice, not a consequence of [F2]. Applying the CNOT gates from each address bit to the target computes parity into that target and gives an exact -gate implementation. In QRAM, store and use one addressed swap to move to a clean scratch bit, copy it by CNOT into the oracle target, and use a second addressed swap to restore the memory and clear the scratch. This is a constant number of RAM calls by [F3], but it still requires the table to have been constructed and maintained. The online gate models therefore count one oracle call versus at least ordinary two-wire gates for this function, with RAM construction cost recorded separately.
Small Johnson-walk spectra and marked fractions
Example
For and , compute the lazy Johnson spectrum, its gap, and the marked fraction from one fixed colliding pair. Also compute the marked fraction for two disjoint colliding pairs in the case. In the one-pair cases assume that the named pair is the only collision pair; in the two-pair case assume that the named disjoint pairs are the only collision pairs, so their common values are distinct and all remaining values are distinct from each other and from those common values.
Facts & Assumptions
Given: The lazy Johnson transition and formulas in Element-distinctness Johnson walk and value access and Spectrum of the lazy Johnson walk.
Spectrum of the lazy Johnson walk: with multiplicity , for .
Element-distinctness O(N^{2/3}) query bound: one fixed collision pair marks a fraction at least of all -subsets.
Element-distinctness Johnson walk and value access: the state space consists of all -subsets and marked states contain at least one collision pair.
Proof
For , the denominator in [F1] is . At , the eigenvalues are , , and . Their multiplicities are , , and , totaling . Thus the nonconstant top eigenvalue is and the gap is . An independent finite check enumerates the ten -subsets lexicographically and forms the integer matrix : its diagonal is , and its off-diagonal entry is exactly when . Exact determinant expansion gives , confirming the scaled spectrum. A fixed colliding pair lies in of the subsets, so its marked fraction is .
For , the denominator is . Formula [F1] gives eigenvalues for . Their multiplicities are , totaling . The independent exact check enumerates the triples and forms with diagonal and off-diagonal exactly when ; fraction-free determinant expansion gives , confirming those eigenvalues and multiplicities. The gap is . A fixed pair belongs to of the subsets, hence has marked fraction .
Under the stated assumption that the only collision pairs are the two named disjoint pairs, each pair is contained in four -subsets, and no -subset contains both pairs because their union has four elements. The two marked families are therefore disjoint and their union has subsets, a fraction . The value exceeds the one-pair lower bound , as required by the “at least” in [F2]. Without the exclusivity assumptions, the counted families still give lower bounds for the marked fraction, but extra collisions can increase it.
Unique-collision element-distinctness parameters
Example
Suppose exactly one pair of distinct indices has equal values. Compute its marked fraction for , and verify the balanced setup/update expression for of order .
Facts & Assumptions
Given: The Johnson-walk state and cost conventions of Element-distinctness Johnson walk and value access and the query bound of Element-distinctness O(N^{2/3}) query bound.
Element-distinctness Johnson walk and value access: a state is an -subset, and its marked condition is the presence of a colliding pair; setup and update query costs are and .
Element-distinctness O(N^{2/3}) query bound: a fixed pair is included with probability , and the one-outer-trial query bound is .
Proof
For , the state space has subsets. Exactly contain the unique colliding pair, so , equal to . The stationary mass is positive, and [F1] gives four setup value queries, two value queries per update, and no extra value query for the stored-value check.
More generally, for with , [F2] charges at most two fresh setups, with leading term and update/search term . Thus both terms are of the same asymptotic order and the theorem's total is . For , the clamp in the theorem selects ; its expression is , consistent with this scaling.
Sources
- Andris Ambainis, Quantum walk algorithm for element distinctness, §6
- Andris Ambainis, Quantum walk algorithm for element distinctness, §§3–4
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, Chapter 20, §20.2
- Andris Ambainis, Quantum walk algorithm for element distinctness, Theorems 4–5 and §§3–4
- Andrew M. Childs, Lecture Notes on Quantum Algorithms, Chapter 20, §§20.1–20.3