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Quantum Relative Entropy, Data Processing, and Strong Subadditivity — 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
- Channels, Kraus, Choi, and Stinespring Representations
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Norms and Realification
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- 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
- 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 Complex Inner-Product Spaces and Matrix Interfaces
- 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
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Knill–Laflamme Recovery and Subsystem Codes
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurements, POVMs, and Instruments
- 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
- Order, Zorn's Lemma, and the Axiom of Choice
- 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
- Quantum Information Measures
- Quantum Relative Entropy, Data Processing, and Strong Subadditivity
- Registers, Tensor Products, and Partial Trace
- Relations, Functions, and Quotients
- 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
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Splitting Fields
- 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 Logarithm and General Powers
- The Riemann Integral: Definition and Integrability
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The ZFC Axioms and the Basic Set Constructions
- Topology of ℝ
- Trace Distance, Fidelity, and Information Limits
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Trust region and cubic regularization methods
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
The examples compute an exact strict decrease under qubit dephasing, a strict strong-subadditivity instance for a pure GHZ state, and a nonlinear map on a specified family of diagonal qubit states. The counterexample preserves root fidelity and contracts trace distance on that family while making a finite relative entropy infinite; it is explicitly not a quantum channel.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Qubit dephasing decreases quantum relative entropy
Statement
On the qubit space with computational basis , define the dephasing channel For and , , one has For the orthogonal pure states , the input relative entropy is , whereas both dephased states equal and their relative entropy is .
Facts & Assumptions
Given: The finite qubit register with ordered orthonormal basis and the operators in the Statement.
Finite-dimensional quantum relative entropy: the finite branch is , and support failure gives .
Density operator: a state is nonnegative with trace one.
Finite registers and their ordered computational bases: is an orthonormal basis of the two-dimensional qubit register.
Completely positive maps: complete positivity means every finite ancillary amplification sends positive operators to positive operators.
Finite-dimensional quantum channel: a quantum channel is complex-linear, completely positive, and trace-preserving.
For and , : for compatible finite-dimensional operators, .
The natural logarithm as the inverse of the exponential function and Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: is the natural logarithm on positive numbers, is strictly increasing, and satisfies the product and quotient laws.
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 positive semidefinite operator is diagonalizable with nonnegative eigenvalues; rank-one orthogonal projections have eigenvalues .
Channel data processing for finite quantum relative entropy: a finite quantum channel does not increase quantum relative entropy, including its support-sensitive extended value.
Diagram convention
The one wire is the qubit operator input/output, and the rectangular box denotes the linear map defined above. This is only a map schematic; the channel and entropy claims are proved by the finite matrix calculations below.
\begin{center} \begin{tikzpicture}[>=stealth, every node/.style={font=\small}] \draw[->] (0,0) -- (1.2,0) node[midway,above] {}; \node[draw,rounded corners,minimum width=1.5cm,minimum height=.75cm] (deph) at (2,0) {}; \draw[->] (deph.east) -- (3.3,0) node[midway,above] {}; \end{tikzpicture} \end{center}
Proof
Put for . Then and by [F3]. The map is complex-linear. For any finite ancilla dimension and positive on , its amplification is , a sum of positive operators since each summand has quadratic form . Thus [F4] gives complete positivity. Also [F6] gives . Hence is a channel by [F5].
The state has eigenvalues , while has eigenvalues ; both are density operators by direct trace and positivity. Since is the rank-one projection onto , under , and . Therefore [F1] gives . Dephasing gives and ; the diagonal trace formula gives . Since , strict monotonicity of the logarithm in [F7] proves the strict decrease; this explicit calculation is consistent with [F9] applied to the channel in step 1.1.
The supports of and are distinct one-dimensional subspaces, so the first is not contained in the second and [F1] gives input divergence . Their diagonal entries are both , so ; consequently the output relative entropy is by [F1].
Strong subadditivity for a pure GHZ tripartite state
Statement
For three qubit registers , let Each one-register marginal and each two-register marginal has entropy , while . In particular, for the displayed order, so strong subadditivity is strict.
Facts & Assumptions
Given: The three-qubit computational basis and the normalized vector in the Statement.
Finite-dimensional von Neumann entropy: over the positive eigenvalues.
Density operator: a density operator is positive semidefinite and has trace one.
Partial trace over a finite tensor factor and Partial trace over the first tensor factor: marginals are obtained by summing the diagonal matrix blocks for the traced-out last or first register.
Ordered tensor registers, their inner product, and wire permutations and Finite registers and their ordered computational bases: the three qubit factors are ordered and their computational product basis is the corresponding tensor product basis.
Schmidt decomposition: a bipartite vector has an expansion with positive coefficients and orthonormal factor families, and its squared norm is .
Strong subadditivity of finite-dimensional quantum entropy: every finite tripartite state satisfies .
Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: the natural logarithm is strictly increasing and .
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: an operator diagonal in an orthonormal basis with nonnegative real diagonal entries is non-negative.
Finite wire permutations are unitary basis permutations: permuting tensor wires is a unitary basis permutation, preserving the spectrum under conjugation.
Diagram convention
The central node denotes the state-preparation map taking to ; the three outgoing legs are its ordered tensor factors. They describe one joint state, not a product of three states. No proof step relies on this diagram.
\begin{center} \begin{tikzpicture}[>=stealth, every node/.style={font=\small}] \node[draw,rounded corners,minimum width=1.8cm,minimum height=.8cm] (state) at (0,0) {}; \draw[->] (state.north west) -- (-1.1,1) node[above] {}; \draw[->] (state.north) -- (0,1) node[above] {}; \draw[->] (state.north east) -- (1.1,1) node[above] {}; \end{tikzpicture} \end{center}
Proof
By [F4], the vectors , , and the six computational basis vectors other than form an orthonormal basis. Direct multiplication by gives and zero on the other seven basis vectors. Thus its spectrum is ; it is non-negative by [F8] and has trace one, so it is a state by [F2]. Consequently by [F1] and [F7].
Expanding gives the four terms , , , and . For any traced register, the first- or last-factor formula [F3], after the wire permutation [F9] when needed, kills both off-diagonal terms because ; the resulting two-register marginal is . Tracing out two registers similarly gives for each one-register marginal. These diagonal matrices have positive eigenvalues , with two additional zero eigenvalues for each two-register marginal. Across each one-versus-two split, the displayed vector itself is a Schmidt expansion of the form [F5], with coefficients .
For each reduced state in step 1.2, [F1] gives entropy . Hence the left side of the claimed SSA instance is , and the right side is . Since and by strict monotonicity in [F7], the inequality is strict and equals the stated comparison.
Fidelity and trace-distance inequalities do not imply QRE data processing
Statement
Write for a diagonal qubit state. Set and On this family, preserves root fidelity and contracts trace distance for every pair, but it sends the finite input relative entropy to . The map is nonlinear and is not the restriction of a quantum channel. Thus metric inequalities on a family under an arbitrary map do not by themselves prove quantum-relative-entropy data processing for channels.
As a separate support check, and have root fidelity and trace distance both , while .
Facts & Assumptions
Given: The qubit computational basis and the diagonal states and maps in the Statement.
Finite-dimensional quantum relative entropy: is the natural-log spectral expression under support inclusion and equals when support inclusion fails.
Fidelity: root fidelity is .
Trace Distance: the supplier defines trace distance as ; in this item write to distinguish it from relative entropy .
Trace Norm: the trace norm is the sum of the singular values.
Density operator: a density operator is nonnegative and has trace one.
A non-negative operator has a unique non-negative square root: positive diagonal operators have the diagonal positive square roots obtained by taking square roots of their eigenvalues.
The natural logarithm as the inverse of the exponential function and Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm: the natural logarithm is defined on positive reals, is strictly increasing, and obeys the usual logarithm laws.
Signs, monotonicity intervals, and ranges of sine and cosine: sine is strictly increasing on .
The addition formulas for sine and cosine: sine and cosine satisfy their addition formulas, including and .
Parity and the Pythagorean identity for sine and cosine: for every real .
The chain rule, in one line from Carathéodory: if is differentiable at and is differentiable at , then is differentiable at with and Sums, scalar multiples, products and quotients: , , , and when : the chain and product rules permit two differentiations of the displayed trigonometric identity.
A function differentiable at is continuous at : differentiability of cosine implies continuity at the endpoint limit used below.
Pi as twice the smallest positive zero of cosine: is positive, so the intervals and angles in the Statement have the stated order.
Proof
For , is nonnegative and has trace one by [F11], so is a state by [F5]. Since by [F15], [F8] and [F12] make sine positive and strictly increasing on ; squaring preserves strict order there, so the angle parametrization is injective and is well-defined. Its output angle lies in , so its output is also a density operator.
The family is the line segment . If were affine on this segment, interpolation between its endpoint states would make its output's diagonal entry affine in . The same is necessary for the restriction of a quantum channel, by complex-linearity. Thus there would be constants with for every . Differentiating twice on the open interval and using [F10]–[F13] gives . By [F14], cosine is continuous, so taking yields , because and . But by [F15], so [F8]–[F9] give , a contradiction. Hence is not affine on the family, and no quantum channel agrees with it there.
For , the square roots in [F6] are diagonal with entries and . Their product is positive diagonal, so by [F2] and [F4], The cosine addition formula [F10] justifies the last equality. Applying subtracts from both angles, leaving their difference unchanged; root fidelity is therefore preserved for every pair.
For diagonal qubit states, [F3] and [F4] give . Take in . The addition formulas and Pythagorean identity [F10]–[F11] give . Therefore Here , so [F8]–[F12] make the first sine factor in the second line no larger than the corresponding nonnegative factor in the first line; the other factor is the same and nonnegative. Thus the output coordinate difference is at most the input difference, proving trace-distance contraction for every pair.
Take and . By strict increase of sine from to in [F8], [F9], and [F12], every angle strictly between zero and gives ; thus both input diagonal states have full support and their relative entropy is finite by [F1] and [F7], since the positive spectral entries have finite natural logarithms. The outputs are and . Since by [F15], the first output has full support, while the second has one-dimensional support; support inclusion fails and [F1] gives output divergence .
Independently, the root fidelity of and is : the product of their positive square roots is , whose only nonzero singular value is . Their difference is , whose square is , so both singular values are and [F3]–[F4] give trace distance . The first support is not contained in the second, so [F1] gives infinite relative entropy.