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.
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.
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.
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 ), pp. 15-16).
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
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
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In mathematics, the tensor product of two vector spaces V and W is a vector space to which is associated a bilinear map that maps a pair to an element of denoted .
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In mathematics, specifically functional analysis, a trace-class operator is a linear operator for which a trace may be defined, such that the trace is a finite number independent of the choice of basis used to compute the trace. This trace of trace-class operators generalizes the trace of matrices studied in linear algebra. All trace-class operators are compact operators.
In the area of mathematics known as functional analysis, a reflexive space is a locally convex topological vector space for which the canonical evaluation map from into its bidual is a homeomorphism. A normed space is reflexive if and only if this canonical evaluation map is surjective, in which case this evaluation map is an isometric isomorphism and the normed space is a Banach space. Those spaces for which the canonical evaluation map is surjective are called semi-reflexive spaces.
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In functional analysis and related areas of mathematics, a sequence space is a vector space whose elements are infinite sequences of real or complex numbers. Equivalently, it is a function space whose elements are functions from the natural numbers to the field K of real or complex numbers. The set of all such functions is naturally identified with the set of all possible infinite sequences with elements in K, and can be turned into a vector space under the operations of pointwise addition of functions and pointwise scalar multiplication. All sequence spaces are linear subspaces of this space. Sequence spaces are typically equipped with a norm, or at least the structure of a topological vector space.
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In mathematics, a Schauder basis or countable basis is similar to the usual (Hamel) basis of a vector space; the difference is that Hamel bases use linear combinations that are finite sums, while for Schauder bases they may be infinite sums. This makes Schauder bases more suitable for the analysis of infinite-dimensional topological vector spaces including Banach spaces.
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In mathematics, the injective tensor product of two topological vector spaces (TVSs) was introduced by Alexander Grothendieck and was used by him to define nuclear spaces. An injective tensor product is in general not necessarily complete, so its completion is called the completed injective tensor products. Injective tensor products have applications outside of nuclear spaces. In particular, as described below, up to TVS-isomorphism, many TVSs that are defined for real or complex valued functions, for instance, the Schwartz space or the space of continuously differentiable functions, can be immediately extended to functions valued in a Hausdorff locally convex TVS without any need to extend definitions from real/complex-valued functions to -valued functions.
In mathematics, nuclear operators are an important class of linear operators introduced by Alexander Grothendieck in his doctoral dissertation. Nuclear operators are intimately tied to the projective tensor product of two topological vector spaces (TVSs).
In the mathematical discipline of functional analysis, a differentiable vector-valued function from Euclidean space is a differentiable function valued in a topological vector space (TVS) whose domains is a subset of some finite-dimensional Euclidean space. It is possible to generalize the notion of derivative to functions whose domain and codomain are subsets of arbitrary topological vector spaces (TVSs) in multiple ways. But when the domain of a TVS-valued function is a subset of a finite-dimensional Euclidean space then many of these notions become logically equivalent resulting in a much more limited number of generalizations of the derivative and additionally, differentiability is also more well-behaved compared to the general case. This article presents the theory of -times continuously differentiable functions on an open subset of Euclidean space , which is an important special case of differentiation between arbitrary TVSs. This importance stems partially from the fact that every finite-dimensional vector subspace of a Hausdorff topological vector space is TVS isomorphic to Euclidean space so that, for example, this special case can be applied to any function whose domain is an arbitrary Hausdorff TVS by restricting it to finite-dimensional vector subspaces.
This is a glossary for the terminology in a mathematical field of functional analysis.