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 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 [1] 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 (Ryan 2002) in this section. The obvious way to define the tensor product of two Banach spaces and 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 and are Banach spaces the algebraic tensor product of and means the tensor product of and as vector spaces and is denoted by The algebraic tensor product consists of all finite sums
where is a natural number depending on and and for
When and are Banach spaces, a crossnorm (or cross norm) on the algebraic tensor product is a norm satisfying the conditions
Here and are elements of the topological dual spaces of and respectively, and is the dual norm of The term reasonable crossnorm is also used for the definition above.
There is a cross norm called the projective cross norm, given by
where
It turns out that the projective cross norm agrees with the largest cross norm ((Ryan 2002), proposition 2.1).
There is a cross norm called the injective cross norm, given by
where Here and denote the topological duals of and 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 and 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 so the Hilbert space tensor product in the section above would be
A uniform crossnorm is an assignment to each pair of Banach spaces of a reasonable crossnorm on so that if are arbitrary Banach spaces then for all (continuous linear) operators and the operator is continuous and If and are two Banach spaces and is a uniform cross norm then defines a reasonable cross norm on the algebraic tensor product The normed linear space obtained by equipping with that norm is denoted by The completion of which is a Banach space, is denoted by The value of the norm given by on and on the completed tensor product for an element in (or ) is denoted by
A uniform crossnorm is said to be finitely generated if, for every pair of Banach spaces and every
A uniform crossnorm is cofinitely generated if, for every pair of Banach spaces and every
A tensor norm is defined to be a finitely generated uniform crossnorm. The projective cross norm and the injective cross norm defined above are tensor norms and they are called the projective tensor norm and the injective tensor norm, respectively.
If and are arbitrary Banach spaces and is an arbitrary uniform cross norm then
Tensor products of locally convex topological vector spaces
The topologies of locally convex topological vector spaces and are given by families of seminorms. For each choice of seminorm on and on we can define the corresponding family of cross norms on the algebraic tensor product and by choosing one cross norm from each family we get some cross norms on 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 are called the projective and injective tensor products, and denoted by and There is a natural map from to
If or is a nuclear space then the natural map from to is an isomorphism. Roughly speaking, this means that if or is nuclear, then there is only one sensible tensor product of and . This property characterizes nuclear spaces.
See also
- Fréchet space – A locally convex topological vector space that is also a complete metric space
- Fredholm kernel – type of a kernel on a Banach space
- Inductive tensor product – binary operation on topological vector spaces
- Injective tensor product
- Projective tensor product – tensor product defined on two topological vector spaces
- Projective topology – Coarsest topology making certain functions continuous
- Tensor product of Hilbert spaces – Tensor product space endowed with a special inner product
References
- Ryan, R.A. (2002), Introduction to Tensor Products of Banach Spaces, New York: Springer.
- Grothendieck, A. (1955), "Produits tensoriels topologiques et espaces nucléaires", Memoirs of the American Mathematical Society, 16.