Tensor product of Hilbert spaces

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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. [1]

Contents

Definition

Since Hilbert spaces have inner products, one would like to introduce an inner product, and thereby a topology, on the tensor product that arises naturally from the inner products on the factors. Let and be two Hilbert spaces with inner products and respectively. Construct the tensor product of and 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 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 and

Explicit construction

The tensor product can also be defined without appealing to the metric space completion. If and are two Hilbert spaces, one associates to every simple tensor product the rank one operator from to that maps a given as

This extends to a linear identification between and the space of finite rank operators from to The finite rank operators are embedded in the Hilbert space of Hilbert–Schmidt operators from to 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 and that is isometrically and linearly isomorphic to

Universal property

The Hilbert tensor product is characterized by the following universal property ( Kadison & Ringrose 1997 , Theorem 2.6.4):

Theorem   There is a weakly Hilbert–Schmidt mapping such that, given any weakly Hilbert–Schmidt mapping to a Hilbert space there is a unique bounded operator such that

A weakly Hilbert-Schmidt mapping is defined as a bilinear map for which a real number exists, such that

for all and one (hence all) orthonormal bases of and of

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

Two different definitions have historically been proposed for the tensor product of an arbitrary-sized collection of Hilbert spaces. Von Neumann's traditional definition simply takes the "obvious" tensor product: to compute , first collect all simple tensors of the form such that . The latter describes a pre-inner product through the polarization identity, so take the closed span of such simple tensors modulo that inner product's isotropy subspaces. This definition is almost never separable, in part because, in physical applications, "most" of the space describes impossible states. Modern authors typically use instead a definition due to Guichardet: to compute , first select a unit vector in each Hilbert space, and then collect all simple tensors of the form , in which only finitely-many are not . Then take the completion of these simple tensors. [2] [3]

Operator algebras

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. [3] This is one advantage of the "algebraic" method in quantum statistical mechanics.

Properties

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. [4] 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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<span class="mw-page-title-main">Wave function</span> Mathematical description of the quantum state of a system

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In mathematics, a Hilbert–Schmidt operator, named after David Hilbert and Erhard Schmidt, is a bounded operator that acts on a Hilbert space and has finite Hilbert–Schmidt norm

In quantum information theory, a quantum channel is a communication channel which can transmit quantum information, as well as classical information. An example of quantum information is the state of a qubit. An example of classical information is a text document transmitted over the Internet.

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In quantum mechanics, separable states are multipartite quantum states that can be written as a convex combination of product states. Product states are multipartite quantum states that can be written as a tensor product of states in each space. The physical intuition behind these definitions is that product states have no correlation between the different degrees of freedom, while separable states might have correlations, but all such correlations can be explained as due to a classical random variable, as opposed as being due to entanglement.

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<span class="mw-page-title-main">Hilbert space</span> Type of topological vector space

In mathematics, Hilbert spaces allow the methods of linear algebra and calculus to be generalized from (finite-dimensional) Euclidean vector spaces to spaces that may be infinite-dimensional. Hilbert spaces arise naturally and frequently in mathematics and physics, typically as function spaces. Formally, a Hilbert space is a vector space equipped with an inner product that induces a distance function for which the space is a complete metric space.

Given a Hilbert space with a tensor product structure a product numerical range is defined as a numerical range with respect to the subset of product vectors. In some situations, especially in the context of quantum mechanics product numerical range is known as local numerical range

This is a glossary for the terminology in a mathematical field of functional analysis.

References

  1. B. Coecke and E. O. Paquette, Categories for the practising physicist, in: New Structures for Physics, B. Coecke (ed.), Springer Lecture Notes in Physics, 2009. arXiv:0905.3010
  2. Nik Weaver (8 March 2020). Answer to Result of continuum tensor product of Hilbert spaces. MathOverflow . StackExchange.
  3. 1 2 Bratteli, O. and Robinson, D: Operator Algebras and Quantum Statistical Mechanics v.1, 2nd ed., page 144. Springer-Verlag, 2002.
  4. Kolmogorov, A. N.; Fomin, S. V. (1961) [1960]. Elements of the theory of functions and functional analysis. Vol. 2: Measure, the Lebesgue integral, and Hilbert space. Translated by Kamel, Hyman; Komm, Horace. Albany, NY: Graylock. p. 100, ex. 3. LCCN   57-4134.

Bibliography