Topological tensor product

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.

Tensor products of Hilbert spaces

Main article: Tensor product 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 a_i and b_j run through orthonormal bases of A and B, then the vectors a_i⊗b_j 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 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 $A\otimes B$ . The algebraic tensor product $A\otimes B$ consists of all finite sums

x=\sum _{{i=1}}^{n}a_{i}\otimes b_{i}

where $n$ is a natural number depending on $x$ and $a_{i}\in A$ and $b_{i}\in B$ for $i=1,\ldots ,n$ .

When A and B are Banach spaces, a cross norm p on the algebraic tensor product $A\otimes B$ is a norm satisfying the conditions

p(a\otimes b)=\|a\|\|b\|

p'(a'\otimes b')=\|a'\|\|b'\|.

Here a′ and b′ are in the topological dual spaces of A and B, respectively, and p′ is the dual norm of p. The term reasonable crossnorm is also used for the definition above.

There is a largest cross norm $\pi$ called the projective cross norm, given by

\pi (x)=\inf \left\{\sum _{{i=1}}^{n}\|a_{i}\|\|b_{i}\|:x=\sum _{{i}}a_{i}\otimes b_{i}\right\}

where $x\in A\otimes B$ .

There is a smallest cross norm $\varepsilon$ called the injective cross norm, given by

\varepsilon (x)=\sup\{|(a'\otimes b')(x)|:a'\in A',b'\in B',\|a'\|=\|b'\|=1\}

where $x\in A\otimes B$ . Here A′ and B′ mean the topological duals of A and B, respectively.

The completions of the algebraic tensor product in these two norms are called the projective and injective tensor products, and are denoted by $A{\hat {\otimes }}_{\pi }B$ and $A{\hat {\otimes }}_{\varepsilon }B$ .

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 σ, so the Hilbert space tensor product in the section above would be $A{\hat {\otimes }}_{\sigma }B$ .

A uniform crossnorm α is an assignment to each pair $(X,Y)$ of Banach spaces of a reasonable crossnorm on $X\otimes Y$ 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 $S\otimes T:X\otimes _{\alpha }Y\to W\otimes _{\alpha }Z$ is continuous and $\|S\otimes T\|\leq \|S\|\|T\|$ . If A and B are two Banach spaces and α is a uniform cross norm then α defines a reasonable cross norm on the algebraic tensor product $A\otimes B$ . The normed linear space obtained by equipping $A\otimes B$ with that norm is denoted by $A\otimes _{\alpha }B$ . The completion of $A\otimes _{\alpha }B$ , which is a Banach space, is denoted by $A{\hat {\otimes }}_{\alpha }B$ . The value of the norm given by α on $A\otimes B$ and on the completed tensor product $A{\hat {\otimes }}_{\alpha }B$ for an element x in $A{\hat {\otimes }}_{\alpha }B$ (or $A\otimes _{\alpha }B$ ) is denoted by $\alpha _{{A,B}}(x)$ or $\alpha (x)$ .

A uniform crossnorm $\alpha$ is said to be finitely generated if, for every pair $(X,Y)$ of Banach spaces and every $u\in X\otimes Y$ ,

\alpha (u;X\otimes Y)=\inf\{\alpha (u;M\otimes N):\dim M,\dim N<\infty \}.

A uniform crossnorm $\alpha$ is cofinitely generated if, for every pair $(X,Y)$ of Banach spaces and every $u\in X\otimes Y$ ,

\alpha (u)=\sup\{\alpha ((Q_{E}\otimes Q_{F})u;(X/E)\otimes (Y/F)):\dim X/E,\dim Y/F<\infty \}.

A tensor norm 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 α is an arbitrary uniform cross norm then

\varepsilon _{{A,B}}(x)\leq \alpha _{{A,B}}(x)\leq \pi _{{A,B}}(x).

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⊗B, and by choosing one cross norm from each family we get some cross norms on A⊗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⊗B are called the projective and injective tensor products, and denoted by A⊗_γB and A⊗_λB. There is a natural map from A⊗_γB to A⊗_λB.

If A or B is a nuclear space then the natural map from A⊗_γB to A⊗_λB 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.

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 .

Functional analysis

Set / subset types	Absolutely convex Absorbing Balanced Bounded Convex Radial Star-shaped Symmetric Linear cone (subset) Convex cone (subset)

TVS types	Banach Barrelled Bornological Brauner F-space Finite-dimensional Fréchet (tame) Hilbert LF-space Locally convex Mackey Montel Nuclear Normed (norm) Quasinormed Reflexive Riesz Smith Stereotype Webbed Topological tensor product (of Hilbert spaces)

Mapping topologies	Dual Dual space Operator Ultraweak Weak (operator) Mackey Strong (polar operator) Ultrastrong Uniform convergence

Linear operators	Adjoint Bilinear (form) Bounded / Unbounded Closed Continuous / Discontinuous Compact Fredholm Hilbert–Schmidt Functionals (positive) Normal Nuclear Self-adjoint Strictly singular Trace class Transpose Unitary

Set operations	Algebraic interior (core) Interior Minkowski addition Polar

Operator theory	Banach algebras C-algebras Spectrum (C-algebra radius) Spectral theory (of ODEs Spectral theorem) Polar decomposition Singular value decomposition

Theorems	Banach–Alaoglu Banach–Saks Banach–Mazur Bessel's inequality Cauchy–Schwarz inequality Closed range Closed graph Eberlein–Šmulian Freudenthal spectral Gelfand–Mazur Goldstine Hahn–Banach (hyperplane separation) Kakutani fixed-point Lomonosov's invariant subspace Mackey–Arens Mazur's lemma M. Riesz extension Open mapping Parseval's identity Schauder fixed-point

Analysis	Bochner space Differentiation in Fréchet spaces Derivatives (Fréchet Gâteaux functional holomorphic) Integrals (Bochner Dunford Gelfand–Pettis regulated weak) Functional calculus (Borel continuous holomorphic) Inverse function theorem (Nash–Moser theorem) Vector measure Weakly measurable function

This article is issued from Wikipedia - version of the 4/13/2015. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.

Topological tensor product

Tensor products of Hilbert spaces

Cross norms and tensor products of Banach spaces

Tensor products of locally convex topological vector spaces

See also

References