Hilbert space
In mathematics, a Hilbert space is an inner product space that is complete with respect to the norm defined by the inner product. Hilbert spaces serve to clarify and generalize the concept of Fourier expansion and certain linear transformations such as the Fourier transform, and are of crucial importance in the mathematical formulation of quantum mechanics. They are studied in functional analysis.
Introduction
Every inner product <.,.> on a real or complex vector space H gives rise to a norm ||.|| as follows: : We call H a Hilbert space if it is complete with respect to this norm. Completeness in this context means that any Cauchy sequence of elements of the space converges to an element in the space, in the sense that the norm of differences approaches zero. Every Hilbert space is thus also a Banach space (but not vice versa). All finite-dimensional inner product spaces (such as Euclidean space with the ordinary dot product) are Hilbert spaces. However, the infinite-dimensional examples are much more important in applications. These applications include:- The theory of unitary group representations;
- The theory of square integrable stochastic processes;
- The Hilbert space theory of partial differential equations, in particular formulations of the Dirichlet problem;
- Spectral analysis of functions, including theories of wavelets.
- Mathematical formulations of quantum mechanics.
Examples
In these examples, we will assume the underlying field of scalars is C, although the definitions apply to the case the underlying field of scalars is R.Euclidean spaces
Cn with the inner product definition : where the bar over a complex number denotes its complex conjugation.Sequence spaces
Much more typical are the infinite dimensional Hilbert spaces however. If B is any set, we define little l2 over B, denoted by : This space becomes a Hilbert space with the inner product : for all x and y in l2(''B''). B does not have to be a countable set in this definition, although if B is not countable, the resulting Hilbert space is not separable. In a sense made more precise below, every Hilbert space is isomorphic to one the form l2(''B'') for a suitable set B. If B='''N''', we write simply l2.Lebesgue spaces
These are function spaces associated to measure spaces (''X'', M, μ), where M is a σ-algebra of subsets of X and μ is a countably additive measure on M. Let L2μ(''X'') be the space of complex-valued square-integrable measurable functions on X, modulo the subspace of those functions whose square integral is zero, or equivalently that are equal to zero almost everywhere. Square integrable means the integral of the square of its absolute value is finite. Modulo equality almost everywhere means functions are identified if and only if they are equal outside of a set of measure 0. The inner product of functions f and g is here given by : One needs to show:- That this integral indeed makes sense;
- The resulting space is complete.
Sobolev spaces
Sobolev spaces, denoted by are another example of Hilbert spaces, which are used very often in the field of Partial differential equations.Operations on Hilbert spaces
Given two (or more) Hilbert spaces, we can combine them into a big Hilbert space by taking their direct sum or their tensor product.Bases
An important concept is that of an orthonormal basis of a Hilbert space H: this is a family {''e''k}k ∈ B of H satisfying: # Elements are normalized: Every element of the family has norm 1: ||''e''k|| = 1 for all k in B # Elements are orthogonal: Every two different elements of B are orthogonal: <''e''k, ej> = 0 for all k, j in B with k ≠ j. # Dense span: The linear span of B is dense in H. We also use the expressions orthonormal sequence and orthonormal set. Examples of orthonormal bases include:- the set {(1,0,0),(0,1,0),(0,0,1)} forms an orthonormal basis of R3
- the sequence {''f''n : n ∈ Z} with fn(''x'') = exp(2π''inx'') forms an orthonormal basis of the complex space L2([0,1])
- the family {''e''b : b ∈ B} with eb(''c'') = 1 if b=''c'' and 0 otherwise forms an orthonormal basis of l2(''B'').
Orthogonal complements and projections
If S is a subset of the Hilbert space H, we define the set of vectors orthogonal to S : Sperp is a closed subspace of H and so forms itself a Hilbert space. If V is a closed subspace of H, then Vperp is called the orthogonal complement of V. In fact, every x in H can then be written uniquely as x = v + w, with v in V and w in Vperp. Therefore, H is the internal Hilbert direct sum of V and Vperp. The linear operator PV : H → H which maps x to v is called the orthogonal projection onto V. Theorem. The orthogonal projection PV is a self-adjoint linear operator on H of norm ≤ 1 with the property PV2 = PV. Moreover, any self-adjoint linear operator E such that E2 = E is of the form PV, where V is the range of E. For every x in H, PV(''x'') is the unique element v of V which minimizes the distance ||''x'' - v||. This provides the geometrical interpretation of PV(''x''): it is the best approximation to x by elements of V.Reflexivity
An important property of any Hilbert space is its reflexivity. In fact, more is true: one has a complete and convenient description of its dual space (the space of all continuous linear functions from the space H into the base field), which is itself a Hilbert space. Indeed, the Riesz representation theorem states that to every element φ of the dual H' there exists one and only one u in H such that : for all x in H and the association φ ↔ u provides an antilinear isomorphism between H and H'. This correspondence is exploited by the bra-ket notation popular in physics but frowned upon by mathematicians.Bounded operators
For a Hilbert space H, the continuous linear operators A : H → H are of particular interest. Such a continuous operator is bounded in the sense that it maps bounded sets to bounded sets. This allows to define its norm as : The sum and the composition of two continuous linear operators is again continuous and linear. For y in H, the map that sends x to <''y'', Ax> is linear and continuous, and according to the Riesz representation theorem can therefore be represented in the form : This defines another continuous linear operator AUnbounded operators
In quantum mechanics, one also considers linear operators which need not be continuous and which need not be defined on the whole space H. One requires only that they are defined on a dense subspace of H. It is possible to define self-adjoint unbounded operators, and these play the role of the observables in the mathematical formulation of quantum mechanics. Examples of self-adjoint unbounded operator on the Hilbert space L2('''R''') are:- A suitable extension of the differential operator
- The multiplication by x operator:
See also
- Topologies on the set of operators on a Hilbert space
- Operator algebra
- Reproducing kernel Hilbert space
References
- Paul Halmos, Measure Theory, D. van Nostrand Co, 1950.
- Jean Dieudonné, Foundations of Modern Analysis, Academic Press, 1960.
- Hermann Weyl, The Theory of Groups and Quantum Mechanics, Dover Press, 1950. This book was originally published in German in 1931.
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