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Tensor products of operator matrix units form a basis
Statement
Let be finite-dimensional (have finite bases by Finite-dimensional vector space, and its dimension ; infinite-dimensional means having no finite basis) complex inner-product spaces with ordered orthonormal bases and . For and define and . Then is a basis of . Empty dimensions give the empty basis of the zero endomorphism space. The root pairing is linear in its first argument, so the displayed matrix-unit maps are linear.
Facts & Assumptions
Given: The finite-dimensional spaces, their ordered orthonormal bases, and the matrix-unit maps in the Statement.
Ordered tensor registers, their inner product, and wire permutations: the tensor product has its ordered product basis and product inner product.
The product basis is orthonormal and tensor dimensions multiply: the product basis is orthonormal, spans, and has dimension , including zero factors.
Tensor products of finitely many linear maps: the tensor of linear maps is the unique linear extension of its action on elementary tensors.
Coordinate columns and matrices of linear maps relative to ordered bases and 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: an endomorphism is determined by its coordinate columns on an ordered basis.
Proof
For a product basis vector , [F3] gives when and , and gives otherwise, by orthonormality in [F1]. Thus each tensor matrix unit has a single coordinate and zeros elsewhere in the product basis.
Every endomorphism of has a unique coordinate coefficient for the image of each product basis vector . The finite sum has the same image as on each such basis vector by step 1.1; [F4] therefore makes it equal to . The same coordinate entries show that this expression is unique. If or , the product space is zero by [F2] and both the basis and sum are empty.
Depends on
- Real and complex inner-product spaces and their induced length
- Finite-dimensional vector space, and its dimension $\dim_F V$; infinite-dimensional means having no finite basis
- Linear map between vector spaces over the same field
- Coordinate columns $[v]_{\mathcal B}$ and matrices $[T]_{\mathcal B}^{\mathcal C}$ of linear maps relative to ordered bases
- 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
- Ordered tensor registers, their inner product, and wire permutations
- Tensor products of finitely many linear maps
- The product basis is orthonormal and tensor dimensions multiply
Used by
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Sources
- John Watrous, The Theory of Quantum Information (2018), §2.2.2 (standard reference, not scraped)
- John Preskill, Quantum Computation, Chapter 3, §3.2.1 (standard reference, not scraped)