Tensor product of Hilbert spaces
In mathematics, and in particular functional analysis, the tensor product of Hilbert spaces is a way to extend the tensor product construction so that the result of taking a tensor product of two Hilbert spaces is another Hilbert space. Roughly speaking, the tensor product is the metric space completion of the ordinary tensor product. This is an example of a topological tensor product. The tensor product allows Hilbert spaces to be collected into a symmetric monoidal category.
Since Hilbert spaces have inner products, one would like to introduce an inner product, and therefore a topology, on the tensor product that arise naturally from those of the factors. Let H1 and H2 be two Hilbert spaces with inner products and , respectively. Construct the tensor product of H1 and H2 as vector spaces as explained in the article on tensor products. We can turn this vector space tensor product into an inner product space by defining
and extending by linearity. That this inner product is the natural one is justified by the identification of scalar-valued bilinear maps on H1 × H2 and linear functionals on their vector space tensor product. Finally, take the completion under this inner product. The resulting Hilbert space is the tensor product of H1 and H2.
The tensor product can also be defined without appealing to the metric space completion. If H1 and H2 are two Hilbert spaces, one associates to every simple tensor product the rank one operator from to H2 that maps a given as
This extends to a linear identification between and the space of finite rank operators from to H2. The finite rank operators are embedded in the Hilbert space of Hilbert–Schmidt operators from to H2. The scalar product in is given by
where is an arbitrary orthonormal basis of
Under the preceding identification, one can define the Hilbertian tensor product of H1 and H2, that is isometrically and linearly isomorphic to
- There is a weakly Hilbert–Schmidt mapping p : H1 × H2 → H such that, given any weakly Hilbert–Schmidt mapping L : H1 × H2 → K to a Hilbert space K, there is a unique bounded operator T : H → K such that L = Tp.
A weakly Hilbert-Schmidt mapping L : H1 × H2 → K is defined as a bilinear map for which a real number d exists, such that
for all and one (hence all) orthonormal basis e1, e2, ... of H1 and f1, f2, ... of H2.
As with any universal property, this characterizes the tensor product H uniquely, up to isomorphism. The same universal property, with obvious modifications, also applies for the tensor product of any finite number of Hilbert spaces. It is essentially the same universal property shared by all definitions of tensor products, irrespective of the spaces being tensored: this implies that any space with a tensor product is a symmetric monoidal category, and Hilbert spaces are a particular example thereof.
Infinite tensor products
If is a collection of Hilbert spaces and is a collection of unit vectors in these Hilbert spaces then the incomplete tensor product (or Guichardet tensor product) is the completion of the set of all finite linear combinations of simple tensor vectors where all but finitely many of the 's equal the corresponding .
Let be the von Neumann algebra of bounded operators on for Then the von Neumann tensor product of the von Neumann algebras is the strong completion of the set of all finite linear combinations of simple tensor products where for This is exactly equal to the von Neumann algebra of bounded operators of Unlike for Hilbert spaces, one may take infinite tensor products of von Neumann algebras, and for that matter C*-algebras of operators, without defining reference states. This is one advantage of the "algebraic" method in quantum statistical mechanics.
If and have orthonormal bases and respectively, then is an orthonormal basis for In particular, the Hilbert dimension of the tensor product is the product (as cardinal numbers) of the Hilbert dimensions.
Examples and applications
The following examples show how tensor products arise naturally.
Given two measure spaces and , with measures and respectively, one may look at , the space of functions on that are square integrable with respect to the product measure If is a square integrable function on and is a square integrable function on then we can define a function on by The definition of the product measure ensures that all functions of this form are square integrable, so this defines a bilinear mapping Linear combinations of functions of the form are also in . It turns out that the set of linear combinations is in fact dense in if and are separable. This shows that is isomorphic to and it also explains why we need to take the completion in the construction of the Hilbert space tensor product.
Similarly, we can show that , denoting the space of square integrable functions , is isomorphic to if this space is separable. The isomorphism maps to We can combine this with the previous example and conclude that and are both isomorphic to
Tensor products of Hilbert spaces arise often in quantum mechanics. If some particle is described by the Hilbert space and another particle is described by then the system consisting of both particles is described by the tensor product of and For example, the state space of a quantum harmonic oscillator is so the state space of two oscillators is which is isomorphic to . Therefore, the two-particle system is described by wave functions of the form A more intricate example is provided by the Fock spaces, which describe a variable number of particles.
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