In mathematics, there are usually many different ways to construct a topological tensor product of two topological vector spaces. For Hilbert spaces or nuclear spaces there is a simple well-behaved theory of tensor products (see Tensor product of Hilbert spaces), but for general Banach spaces or locally convex topological vector spaces the theory is notoriously subtle.

Motivation

One of the original motivations for topological tensor products is the fact that tensor products of the spaces of smooth real-valued functions on \R^n do not behave as expected. There is an injection but this is not an isomorphism. For example, the function cannot be expressed as a finite linear combination of smooth functions in We only get an isomorphism after constructing the topological tensor product; i.e., This article first details the construction in the Banach space case. The space is not a Banach space and further cases are discussed at the end.

Tensor products of Hilbert spaces

The algebraic tensor product of two Hilbert spaces A and B has a natural positive definite sesquilinear form (scalar product) induced by the sesquilinear forms of A and B. So in particular it has a natural positive definite quadratic form, and the corresponding completion is a Hilbert space A ⊗ B, called the (Hilbert space) tensor product of A and B. If the vectors ai and bj run through orthonormal bases of A and B, then the vectors ai⊗bj form an orthonormal basis of A ⊗ B.

Cross norms and tensor products of Banach spaces

We shall use the notation from in this section. The obvious way to define the tensor product of two Banach spaces A and B is to copy the method for Hilbert spaces: define a norm on the algebraic tensor product, then take the completion in this norm. The problem is that there is more than one natural way to define a norm on the tensor product. If A and B are Banach spaces the algebraic tensor product of A and B means the tensor product of A and B as vector spaces and is denoted by The algebraic tensor product A \otimes B consists of all finite sums where n is a natural number depending on x and a_i \in A and b_i \in B for When A and B are Banach spaces, a ' (or ') p on the algebraic tensor product A \otimes B is a norm satisfying the conditions Here a^{*p**ri**me**}*** and b^{*p**ri**me**}*** are elements**** of**** the topological dual**** spaces**** of**** A and B,**** respectively****,**** and p^{*p**ri**me**}*** is**** the dual**** norm**** of**** p.**** The term**** **** is**** also**** used**** for the definition**** above.**** There is a cross norm \pi called the projective cross norm, given by where It turns out that the projective cross norm agrees with the largest cross norm (, pp. 15-16). There is a cross norm \varepsilon called the injective cross norm, given by where Here A^{\prime} and B^{\prime} denote the topological duals of A and B, respectively. Note hereby that the injective cross norm is only in some reasonable sense the "smallest". The completions of the algebraic tensor product in these two norms are called the projective and injective tensor products, and are denoted by and When A and B are Hilbert spaces, the norm used for their Hilbert space tensor product is not equal to either of these norms in general. Some authors denote it by \sigma, so the Hilbert space tensor product in the section above would be A **** *alp**ha** is*** an**** assignment**** to**** each**** pair**** (X, Y)**** of**** Banach**** spaces**** of**** a reasonable**** crossnorm on**** X *oti**me**s*** Y so**** that**** if**** X,**** W,**** Y,**** Z are arbitrary Banach**** spaces**** then**** for all (continuous linear****)**** operators S : X *to*** W and T : Y *to*** Z the operator**** is**** continuous**** and **** If**** A and B are two Banach**** spaces**** and *alp**ha** is*** a uniform cross norm**** then**** *alp**ha** def**in**es** a rea**so**na**bl**e*** cross norm**** on**** the algebraic tensor**** product **** The normed**** linear**** space obtained**** by**** equipping A *oti**me**s*** B with**** that**** norm**** is**** denoted by**** **** The completion**** of**** **** which is**** a Banach**** space,**** is**** denoted by**** **** The value of**** the norm**** given by**** *alp**ha** on*** A *oti**me**s*** B and on**** the completed tensor**** product **** for an**** element x in**** **** (or ) is**** denoted by**** A uniform crossnorm *alp**ha** is*** said**** to**** be**** **** if****,**** for every pair**** (X, Y)**** of**** Banach**** spaces**** and every A uniform crossnorm *alp**ha** is*** **** if****,**** for every pair**** (X, Y)**** of**** Banach**** spaces**** and every A **** is**** defined to**** be**** a finitely**** generated uniform crossnorm.**** The projective cross norm \pi and the injective cross norm \varepsilon defined above are tensor norms and they are called the projective tensor norm and the injective tensor norm, respectively. If A and B are arbitrary Banach spaces and \alpha is an arbitrary uniform cross norm then

Tensor products of locally convex topological vector spaces

The topologies of locally convex topological vector spaces A and B are given by families of seminorms. For each choice of seminorm on A and on B we can define the corresponding family of cross norms on the algebraic tensor product A\otimes B, and by choosing one cross norm from each family we get some cross norms on A\otimes B, defining a topology. There are in general an enormous number of ways to do this. The two most important ways are to take all the projective cross norms, or all the injective cross norms. The completions of the resulting topologies on A\otimes B are called the projective and injective tensor products, and denoted by and There is a natural map from to If A or B is a nuclear space then the natural map from to is an isomorphism. Roughly speaking, this means that if A or B is nuclear, then there is only one sensible tensor product of A and B. This property characterizes nuclear spaces.