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Purifications exist and are unitarily equivalent after padding
Statement
Every density operator on a nonzero finite-dimensional complex-inner-product space has a purification on some finite-dimensional auxiliary space. More precisely, if , it has one on an auxiliary space of dimension . If () are any two purifications of the same , then for every integer and every pair of linear isometric embeddings , where has its standard complex inner product, there is a unitary on such that
Facts & Assumptions
Given: A density operator on nonzero finite-dimensional , and when proving equivalence, two finite-dimensional purifications of , an integer , and linear isometric embeddings with the standard inner product on .
Density operators have an orthogonal spectral ensemble: with , orthonormal , and .
Ensemble and purification: a purification is a unit vector whose auxiliary partial trace is .
Schmidt decomposition: a finite bipartite vector has a Schmidt decomposition with positive coefficients and orthonormal factor families.
Ordered tensor registers, their inner product, and wire permutations, Tensor products of finitely many linear maps and Dirac Notation Conversion: tensor factors are ordered with product pairings, tensor maps apply each linear map to its factor, and acts by .
Partial trace over a finite tensor factor: in ordered orthonormal product bases, partial trace sums entries with equal auxiliary indices.
Linear combination of a finite list, and the span as the smallest linear subspace containing , The orthogonal complement , For a subspace of a finite-dimensional inner product space, , If and is a linear subspace of , then is finite-dimensional, , and if and only if and Every finite-dimensional real or complex inner product space has an orthonormal basis: the span of a finite family is a subspace; its orthogonal complement is finite-dimensional and has an orthonormal basis; adjoining that basis to an orthonormal basis of gives an orthonormal basis of the ambient space.
The partial trace is characterized by the trace pairing and is basis-independent: the partial-trace formula is independent of the chosen ordered orthonormal basis of the auxiliary space.
If with every finite-dimensional, then is finite-dimensional and ; in particular : if a finite-dimensional space is a direct sum of two finite-dimensional subspaces, its dimension is the sum of their dimensions.
The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension and The standard formulas on and on are inner products: the standard basis of has elements and is orthonormal for its standard pairing.
A finite list is an ordered basis if and only if every equals for exactly one ; those scalars are the coordinates of in that ordered basis: prescribing images on an ordered basis determines a unique linear map.
Rank and nullity of a linear map with finite-dimensional domain: the rank of is the dimension of its image.
The product basis is orthonormal and tensor dimensions multiply: elementary tensors of ordered factor bases form a basis of the tensor product, and if the factor bases are orthonormal then so is this product basis.
Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces: a norm-preserving linear map is a linear isometry, and a bijective linear isometry on a finite-dimensional complex inner-product space is unitary.
Proof
Use [F1] and let with the standard ordered basis relabelled , orthonormal by [F9]. Define . The product pairing [F4] gives , and [F5] gives . Thus is a purification on an auxiliary space of dimension by [F12].
For each , choose an orthonormal basis of by [F6], and put . Since is linear and norm-preserving by [F11], each has norm one. For , the four vectors and have squared norm , so their images do too. With the root inner product convention, for the differences and both vanish. Thus and , so ; the image vectors are orthonormal. Let . By [F6], and is finite-dimensional; choose an orthonormal basis of by [F6] and append it to to obtain an ordered orthonormal basis of . Choose an ordered orthonormal basis of by [F6]. The product basis result [F13] shows that sends the orthonormal product basis of to an orthonormal family, so the padded vector is still a unit vector. Write in this product basis. In the extended basis of , has zero coefficients on every complement basis vector, so the partial-trace coordinate sum [F5] over the extended basis equals the original partial trace over , namely . By [F3] write each in Schmidt form ; [F5]–[F7] give its marginal . Therefore the vectors with form an orthonormal basis of each positive -eigenspace of .
Fix an eigenvalue . By step 1.2, its two lists of Schmidt vectors are orthonormal bases of the same eigenspace. Write . Orthonormality gives ; conjugating this identity gives , so the square matrix is unitary. Prescribe . For indices , the inner product of the two images is ; distinct eigenvalue blocks remain orthogonal. Thus this basis map extends linearly by [F10] to an onto isometry between the Schmidt-support subspaces.
By [F6], each padded auxiliary space is the orthogonal direct sum of its Schmidt-support subspace and its orthogonal complement. Step 1.2 shows that each support has dimension , so [F8] gives dimension for both complements. Choose orthonormal bases for them by [F6] and prescribe a bijection between those bases. The complement map and the support isometry from step 2.1 together send an orthonormal basis of to an orthonormal basis of ; [F10] extends this map uniquely and linearly, and the basis map is surjective and preserves norms. Hence [F11] makes it a unitary . In each eigenvalue block, , and therefore Summing these equalities over the positive eigenvalues gives the displayed equivalence after padding.
Remarks
The proof uses finite-dimensional spectral families, orthonormal complements and finite basis extensions; it makes no arbitrary-index choice.
Depends on
- Ensemble and purification
- Dirac Notation Conversion
- Ordered tensor registers, their inner product, and wire permutations
- Tensor products of finitely many linear maps
- Linear isometries, and orthogonal or unitary operators on finite-dimensional inner product spaces
- Density operators have an orthogonal spectral ensemble
- Partial trace over a finite tensor factor
- The partial trace is characterized by the trace pairing and is basis-independent
- Schmidt decomposition
- Finite-dimensional vector space, and its dimension $\dim_F V$; infinite-dimensional means having no finite basis
- Linear combination of a finite list, and the span $\operatorname{span}(S)$ as the smallest linear subspace containing $S$
- The orthogonal complement $W^\perp=\{v:\langle v,w\rangle=0\text{ for all }w\in W\}$
- For a subspace $W$ of a finite-dimensional inner product space, $V=W\oplus W^\perp$
- If $\dim_F V = n$ and $U$ is a linear subspace of $V$, then $U$ is finite-dimensional, $\dim_F U \le n$, and $\dim_F U = n$ if and only if $U = V$
- Every finite-dimensional real or complex inner product space has an orthonormal basis
- If $V = \bigoplus_{i<n} U_i$ with every $U_i$ finite-dimensional, then $V$ is finite-dimensional and $\dim_F V = \sum_{i<n} \dim_F U_i$; in particular $\dim_F(U \oplus W) = \dim_F U + \dim_F W$
- The standard list $e : n \to F^{n}$ with $e_i(i) = 1_F$ and $e_i(j) = 0_F$ for $j \ne i$ is an ordered basis of $F^{n}$; hence $\dim_F F^{n} = n$, and $F^{0}$ is the zero space with basis $\varnothing$ and dimension $0$
- The standard formulas $\langle x,y\rangle=\sum_{k<n}x_k y_k$ on $\mathbb R^n$ and $\sum_{k<n}x_k\overline{y_k}$ on $\mathbb C^n$ are inner products
- A finite list $v : n \to V$ is an ordered basis if and only if every $x \in V$ equals $\sum_{i<n} \lambda_i v_i$ for exactly one $\lambda : n \to F$; those scalars are the coordinates of $x$ in that ordered basis
- Rank and nullity of a linear map with finite-dimensional domain
- The product basis is orthonormal and tensor dimensions multiply
Used by
- Complementary channels and coherent information Definition
- Finite IID quantum source and compression code Definition
- Operational quantum, private, and entanglement-assisted capacities Definition
- Coherent information equals output entropy minus environment entropy Lemma
- Every finite extension is obtained from a purification by a channel Lemma
- Flat-input coherent information is achievable by subspace codes Lemma
- Gentle measurement bound in finite dimensions Lemma
- Regularized coherent-information formula for quantum capacity Theorem
- The least purification environment dimension is the density rank Theorem
Cited to discharge well-definedness by Ensemble and purification.
Dependency tree · two levels
91 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
- John Watrous, The Theory of Quantum Information, §§2.1.2–2.1.3, Thms. 2.10–2.12 (standard reference, not scraped)
- John Preskill, Quantum Computation, Chapter 2: Foundations I: States and Ensembles, §§2.4–2.5 (standard reference, not scraped)
- Ronald de Wolf, Quantum Computing: Lecture Notes, §18.3 (standard reference, not scraped)