# nLab tensor product of Banach spaces

Tensor products of Banach spaces

## Topics in Functional Analysis

#### Monoidal categories

monoidal categories

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With duals for objects

With duals for morphisms

With traces

Closed structure

Special sorts of products

Semisimplicity

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In higher category theory

# Tensor products of Banach spaces

## Idea

There are various norms that may be placed on the tensor product of the underlying vector spaces of two Banach spaces; the result is not usually complete, but of course we may take its completion. One of these, the projective tensor product, makes Ban (the category of Banach spaces and short linear maps) into a closed symmetric monoidal category, but there are others that still put useful structures on $Ban$. If we start with Hilbert spaces, then there is a choice of norm that will make the result into a Hilbert space; then Hilb also becomes a symmetric monoidal category.

## Definitions

Let $V$ and $W$ be Banach spaces, and let $V \otimes W$ be their tensor product as vector spaces. To define a tensor product of $V$ and $W$ as Banach spaces, we will place a norm on $V \otimes W$, making a normed vector space; the only difference in the following definitions is which norm to use. Then we take the completion $V {\displaystyle\hat{\otimes}} W$, which is a Banach space.

###### Definition (projective tensor product)

Every element of $V \otimes W$ may be written (in many different ways) as a formal linear combination of formal tensor products of elements of $V$ and $W$ (suppressing the symbol $\otimes$):

$\sum_i \alpha_i v_i w_i .$

Let the projective cross norm ${\|x\|_\pi}$ of an element $x$ of $V \otimes W$ be

${\|x\|_\pi} \coloneqq \inf \{ \sum_i {|\alpha_i|} {\|v_i\|_V} {\|w_i\|_W} \;|\; x = \sum_i \alpha_i v_i w_i \} .$

Then the projective tensor product $V {\displaystyle\hat{\otimes}_\pi} W$ of $V$ and $W$ is the completion of $V \otimes W$ under the projective cross norm.

###### Definition (injective tensor product)

If $\lambda$ and $\mu$ are linear functionals on $V$ and $W$ (respectively), then $\lambda \otimes \mu$ is a linear functional on $V \otimes W$. Let the injective cross norm ${\|x\|_\epsilon}$ of an element $x$ of $V \otimes W$ be

${\|x\|_\epsilon} \coloneqq \sup \{ {|(\lambda \otimes \mu)x|} \;|\; {\|\lambda\|_{V^*}}, {\|\mu\|_{W^*}} \leq 1 \} .$

Then the injective tensor product $V {\displaystyle\hat{\otimes}_\epsilon} W$ of $V$ and $W$ is the completion of $V \otimes W$ under the injective cross norm.

###### Definition (tensor product of Hilbert spaces)

If $V$ and $W$ are Hilbert spaces, then their norms determine and are determined by their inner products, so let us discuss inner products. The elements of $V \otimes W$ are generated by elements of the form $v w$, so set

$\langle{v_1 w_1, v_2 w_2}\rangle \coloneqq \langle{v_1, v_2}\rangle \langle{w_1, w_2}\rangle$

and extend by linearity. We write the norm of an element $x$ of the inner product space $V \otimes W$ as ${\|x\|_\sigma}$. Then the tensor product $V {\displaystyle\hat{\otimes}_\sigma} W$ of the Hilbert spaces $V$ and $W$ is the completion of $V \otimes W$ under this norm (or inner product).

## Cross norms

Besides the specific norms defined above, we can define axioms of a reasonable norm on $V \otimes W$.

###### Definition (cross norm)

A cross norm on $V$ and $W$ is any norm $\chi$ on $V \otimes W$ such that:

• ${\|v \otimes w\|_\chi} = {\|v\|_V} {\|w\|_W}$ for any elements $v$ and $w$ of $V$ and $W$ (respectively);
• ${\|\lambda \otimes \mu\|_{\chi^*}} = {\|\lambda\|_{V^*}} {\|\mu\|_{W^*}}$ for any bounded linear functionals $\lambda$ and $\mu$ on $V$ and $W$ (respectively).
###### Definition (uniform cross norm)

A uniform cross norm is an operation that takes two Banach spaces and returns a norm on their algebraic tensor product, naturally in the two spaces. Equivalently, it's a functor $\chi\colon Ban \times Ban \to NVect$ that makes the following diagram commute (or fills it with a natural isomorphism):

$\array { Ban \times Ban & \overset{\chi}\rightarrow & NVect \\ \downarrow & & \downarrow \\ Vect \times Vect & \underset{\otimes}\rightarrow & Vect }$

A uniform cross norm is obviously desirable from the nPOV, but does it meet the analysts' needs for a cross norm? Yes:

###### Proposition

A uniform cross norm assigns a cross norm to any two Banach spaces.

The specific cross norms from the previous section qualify as much as possible:

###### Proposition

The projective and injective cross norms are uniform cross norms (and hence are in fact cross norms). The norm on the algebraic tensor product of two Hilbert spaces is also a cross norm.

As far as I can tell, the Hilbert-space cross norm $\sigma$ doesn't apply to arbitrary Banach spaces, so it doesn't define a uniform cross norm as defined above; however, it does define a functor on $Hilb \times Hilb$, so it's as uniform as could be expected.

Looking only at the general theory of cross norms, the projective and injective cross norms appear naturally:

###### Proposition (Ryan 2002, Prop. 6.1)

Let $V$ and $W$ be Banach spaces and $\chi$ be any norm on $V \otimes W$. Then $\chi$ is a cross norm if and only if

${\|x\|_\epsilon} \leq {\|x\|_\chi} \leq {\|x\|_\pi},$

for every $x \in V \otimes W$.

That is, we have a poset of cross norms, and the projective and injective cross norms are (respectively) the top and bottom of this poset.

We therefore obtain the following relationship between $\epsilon$, $\sigma$, and $\pi$:

###### Corollary

If $V$ and $W$ are Hilbert spaces and $x$ is an element of $V \otimes W$, then

${\|x\|_\epsilon} \leq {\|x\|_\sigma} \leq {\|x\|_\pi} .$

Of course, any cross norm $\chi$ on $V$ and $W$ allows us to form the Banach space $V {\displaystyle\hat{\otimes}_\chi} W$, which may reasonably be called a tensor product of $V$ and $W$; that's why we care.

## Schmidt decomposition

The Schmidt decomposition is a way of expressing a pure state in the tensor product of two Hilbert spaces in terms of states of the two components:

###### Theorem (Nielsen and Chuang Theorem 2.7)

Let $A$ and $B$ be finite-dimensional Hilbert spaces. Let $|\psi\rangle$ be a pure state of $A \otimes B$. Then there exist orthonormal families? $\{ |i_A \rangle \}_i$ in $A$ and $\{ |i_B \rangle \}_i$ in $B$, and non-negative real numbers $\lambda_i$, such that

$|\psi\rangle = \sum_i \lambda_i |i_A \rangle \otimes |i_B\rangle$

and $\sum_i \lambda_i^2 = 1$.

The numbers $\lambda_i$ are called the Schmidt co-efficients of $|\psi\rangle$, and the families $\{ |i_A\rangle \}$ and $\{ |i_B\rangle \}$ the Schmidt bases for $A$ and $B$.

###### Definition

The Schmidt number of $|\psi\rangle$ is the number of non-zero Schmidt coefficients of $|\psi\rangle$.

###### Remark

Although most often stated for finite dimensional Hilbert spaces, the Schmidt decomposition theorem stated as above works for $A$ and $B$ Hilbert spaces of arbitrary dimension (even uncountable). A proof follows through a straightforward application of the polar decomposition and spectral theorems to the positive trace-class operator given by the partial trace of the projection operator onto $\psi$ (see MO: Schmidt Decomposition on infinite-dimensional Hilbert spaces.)

## Foundational issues

We need the Hahn–Banach theorem for $\epsilon$ to be a cross norm; but $\sigma$ and $\pi$ work regardless. Possibly some of the other propositions rely on some other form of the axiom of choice; I haven't seen their proofs.

## References

• M. Nielsen and I. Chuang. Quantum Computation and Quantum Information. Cambridge University Press. 2000.

• Raymond A. Ryan, Introduction to Tensor Products of Banach Spaces. Springer Monographs in Mathematics. Springer-Verlag London. 2002. (doi:10.1007/978-1-4471-3903-4, toc pdf)

• J. M. Egger, Notes on Banach spaces and Hilbert spaces (pdf)