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In the mathematical discipline of
functional analysis Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of vector spaces endowed with some kind of limit-related structure (for example, Inner product space#Definition, inner product, Norm (mathematics ...
, the concept of a compact operator on Hilbert space is an extension of the concept of a matrix acting on a finite-dimensional vector space; in
Hilbert space In mathematics, a Hilbert space is a real number, real or complex number, complex inner product space that is also a complete metric space with respect to the metric induced by the inner product. It generalizes the notion of Euclidean space. The ...
,
compact operator In functional analysis, a branch of mathematics, a compact operator is a linear operator T: X \to Y, where X,Y are normed vector spaces, with the property that T maps bounded subsets of X to relatively compact subsets of Y (subsets with compact ...
s are precisely the closure of finite-rank operators (representable by finite-dimensional matrices) in the
topology Topology (from the Greek language, Greek words , and ) is the branch of mathematics concerned with the properties of a Mathematical object, geometric object that are preserved under Continuous function, continuous Deformation theory, deformat ...
induced by the
operator norm In mathematics, the operator norm measures the "size" of certain linear operators by assigning each a real number called its . Formally, it is a norm defined on the space of bounded linear operators between two given normed vector spaces. Inform ...
. As such, results from matrix theory can sometimes be extended to compact operators using similar arguments. By contrast, the study of general operators on infinite-dimensional spaces often requires a genuinely different approach. For example, the spectral theory of compact operators on
Banach space In mathematics, more specifically in functional analysis, a Banach space (, ) is a complete normed vector space. Thus, a Banach space is a vector space with a metric that allows the computation of vector length and distance between vectors and ...
s takes a form that is very similar to the
Jordan canonical form \begin \lambda_1 1\hphantom\hphantom\\ \hphantom\lambda_1 1\hphantom\\ \hphantom\lambda_1\hphantom\\ \hphantom\lambda_2 1\hphantom\hphantom\\ \hphantom\hphantom\lambda_2\hphantom\\ \hphantom\lambda_3\hphantom\\ \hphantom\ddots\hphantom\\ ...
of matrices. In the context of Hilbert spaces, a square matrix is unitarily diagonalizable if and only if it is normal. A corresponding result holds for normal compact operators on Hilbert spaces. More generally, the compactness assumption can be dropped. As stated above, the techniques used to prove results, e.g., the
spectral theorem In linear algebra and functional analysis, a spectral theorem is a result about when a linear operator or matrix can be diagonalized (that is, represented as a diagonal matrix in some basis). This is extremely useful because computations involvin ...
, in the non-compact case are typically different, involving operator-valued measures on the
spectrum A spectrum (: spectra or spectrums) is a set of related ideas, objects, or properties whose features overlap such that they blend to form a continuum. The word ''spectrum'' was first used scientifically in optics to describe the rainbow of co ...
. Some results for compact operators on Hilbert space will be discussed, starting with general properties before considering subclasses of compact operators.


Definition

Let H be a
Hilbert space In mathematics, a Hilbert space is a real number, real or complex number, complex inner product space that is also a complete metric space with respect to the metric induced by the inner product. It generalizes the notion of Euclidean space. The ...
and L(H) be the set of
bounded operator In functional analysis and operator theory, a bounded linear operator is a linear transformation L : X \to Y between topological vector spaces (TVSs) X and Y that maps bounded subsets of X to bounded subsets of Y. If X and Y are normed vector ...
s on ''H''. Then, an operator T\in L(H) is said to be a compact operator if the image of each bounded set under T is relatively compact.


Some general properties

We list in this section some general properties of compact operators. If ''X'' and ''Y'' are separable Hilbert spaces (in fact, ''X'' Banach and ''Y'' normed will suffice), then ''T'' : ''X'' → ''Y'' is compact if and only if it is
sequentially continuous In topology and related fields of mathematics, a sequential space is a topological space whose topology can be completely characterized by its convergent/divergent sequences. They can be thought of as spaces that satisfy a very weak axiom of count ...
when viewed as a map from ''X'' with the
weak topology In mathematics, weak topology is an alternative term for certain initial topologies, often on topological vector spaces or spaces of linear operators, for instance on a Hilbert space. The term is most commonly used for the initial topology of a ...
to ''Y'' (with the norm topology). (See , and note in this reference that the uniform boundedness will apply in the situation where ''F'' ⊆ ''X'' satisfies (∀φ ∈ Hom(''X'', ''K'')) sup < ∞, where ''K'' is the underlying field. The uniform boundedness principle applies since Hom(''X'', ''K'') with the norm topology will be a Banach space, and the maps ''x**'' : Hom(''X'',''K'') → ''K'' are continuous homomorphisms with respect to this topology.) The family of compact operators is a norm-closed, two-sided, *-ideal in ''L''(''H''). Consequently, a compact operator ''T'' cannot have a bounded inverse if ''H'' is infinite-dimensional. If ''ST'' = ''TS'' = ''I'', then the identity operator would be compact, a contradiction. If sequences of bounded operators ''Bn'' → ''B'', ''Cn'' → ''C'' in the strong operator topology and ''T'' is compact, then B_nTC_n^* converges to BTC^* in norm. For example, consider the Hilbert space \ell^2(\mathbf), with standard basis . Let ''Pm'' be the orthogonal projection on the linear span of . The sequence converges to the identity operator ''I'' strongly but not uniformly. Define ''T'' by Te_n = \tfrac e_n. ''T'' is compact, and, as claimed above, ''PmT'' → ''IT'' = ''T'' in the uniform operator topology: for all ''x'', \left\, P_m T x - T x \right \, \leq \left( \frac\right)^2 \, x \, . Notice each ''Pm'' is a finite-rank operator. Similar reasoning shows that if ''T'' is compact, then ''T'' is the uniform limit of some sequence of finite-rank operators. By the norm-closedness of the ideal of compact operators, the converse is also true. The quotient C*-algebra of ''L''(''H'') modulo the compact operators is called the Calkin algebra, in which one can consider properties of an operator up to compact perturbation.


Compact self-adjoint operator

A bounded operator ''T'' on a Hilbert space ''H'' is said to be
self-adjoint In mathematics, an element of a *-algebra is called self-adjoint if it is the same as its adjoint (i.e. a = a^*). Definition Let \mathcal be a *-algebra. An element a \in \mathcal is called self-adjoint if The set of self-adjoint elements ...
if ''T'' = ''T*'', or equivalently, \langle T x, y \rangle = \langle x, T y \rangle, \quad x, y \in H. It follows that ⟨''Tx'', ''x''⟩ is real for every ''x'' ∈ ''H'', thus eigenvalues of ''T'', when they exist, are real. When a closed linear subspace ''L'' of ''H'' is invariant under ''T'', then the restriction of ''T'' to ''L'' is a self-adjoint operator on ''L'', and furthermore, the
orthogonal complement In the mathematical fields of linear algebra and functional analysis, the orthogonal complement of a subspace W of a vector space V equipped with a bilinear form B is the set W^\perp of all vectors in V that are orthogonal to every vector in W. I ...
''L'' of ''L'' is also invariant under ''T''. For example, the space ''H'' can be decomposed as the orthogonal
direct sum The direct sum is an operation between structures in abstract algebra, a branch of mathematics. It is defined differently but analogously for different kinds of structures. As an example, the direct sum of two abelian groups A and B is anothe ...
of two ''T''–invariant closed linear subspaces: the kernel of ''T'', and the orthogonal complement of the kernel (which is equal to the closure of the range of ''T'', for any bounded self-adjoint operator). These basic facts play an important role in the proof of the spectral theorem below. The classification result for Hermitian matrices is the
spectral theorem In linear algebra and functional analysis, a spectral theorem is a result about when a linear operator or matrix can be diagonalized (that is, represented as a diagonal matrix in some basis). This is extremely useful because computations involvin ...
: If ''M'' = ''M*'', then ''M'' is unitarily diagonalizable, and the diagonalization of ''M'' has real entries. Let ''T'' be a compact self-adjoint operator on a Hilbert space ''H''. We will prove the same statement for ''T'': the operator ''T'' can be diagonalized by an orthonormal set of eigenvectors, each of which corresponds to a real eigenvalue.


Spectral theorem

Theorem For every compact self-adjoint operator ''T'' on a real or complex Hilbert space ''H'', there exists an
orthonormal basis In mathematics, particularly linear algebra, an orthonormal basis for an inner product space V with finite Dimension (linear algebra), dimension is a Basis (linear algebra), basis for V whose vectors are orthonormal, that is, they are all unit vec ...
of ''H'' consisting of eigenvectors of ''T''. More specifically, the orthogonal complement of the kernel of ''T'' admits either a finite orthonormal basis of eigenvectors of ''T'', or a
countably infinite In mathematics, a set is countable if either it is finite or it can be made in one to one correspondence with the set of natural numbers. Equivalently, a set is ''countable'' if there exists an injective function from it into the natural numbe ...
orthonormal basis of eigenvectors of ''T'', with corresponding eigenvalues , such that . In other words, a compact self-adjoint operator can be unitarily diagonalized. This is the spectral theorem. When ''H'' is separable, one can mix the basis with a
countable In mathematics, a Set (mathematics), set is countable if either it is finite set, finite or it can be made in one to one correspondence with the set of natural numbers. Equivalently, a set is ''countable'' if there exists an injective function fro ...
orthonormal basis for the kernel of ''T'', and obtain an orthonormal basis for ''H'', consisting of eigenvectors of ''T'' with real eigenvalues such that . Corollary For every compact self-adjoint operator ''T'' on a real or complex separable infinite-dimensional Hilbert space ''H'', there exists a countably infinite orthonormal basis of ''H'' consisting of eigenvectors of ''T'', with corresponding eigenvalues , such that .


The idea

Let us discuss first the finite-dimensional proof. Proving the spectral theorem for a Hermitian ''n'' × ''n'' matrix ''T'' hinges on showing the existence of one eigenvector ''x''. Once this is done, Hermiticity implies that both the linear span and orthogonal complement of ''x'' (of dimension ''n'' − 1) are invariant subspaces of ''T''. The desired result is then obtained by induction for T_. The existence of an eigenvector can be shown in (at least) two alternative ways: #One can argue algebraically: The characteristic polynomial of ''T'' has a complex root, therefore ''T'' has an eigenvalue with a corresponding eigenvector. #The eigenvalues can be characterized variationally: The largest eigenvalue is the maximum on the closed unit ''sphere'' of the function defined by . Note. In the finite-dimensional case, part of the first approach works in much greater generality; any square matrix, not necessarily Hermitian, has an eigenvector. This is simply not true for general operators on Hilbert spaces. In infinite dimensions, it is also not immediate how to generalize the concept of the characteristic polynomial. The spectral theorem for the compact self-adjoint case can be obtained analogously: one finds an eigenvector by extending the second finite-dimensional argument above, then apply induction. We first sketch the argument for matrices. Since the closed unit sphere ''S'' in R2''n'' is compact, and ''f'' is continuous, ''f''(''S'') is compact on the real line, therefore ''f'' attains a maximum on ''S'', at some unit vector ''y''. By Lagrange's multiplier theorem, ''y'' satisfies \nabla f = \nabla y^* T y = \lambda \cdot \nabla y^* y for some λ. By Hermiticity, . Alternatively, let ''z'' ∈ C''n'' be any vector. Notice that if a unit vector ''y'' maximizes ⟨''Tx'', ''x''⟩ on the unit sphere (or on the unit ball), it also maximizes the
Rayleigh quotient In mathematics, the Rayleigh quotient () for a given complex Hermitian matrix M and nonzero vector ''x'' is defined as:R(M,x) = .For real matrices and vectors, the condition of being Hermitian reduces to that of being symmetric, and the conjugat ...
: g(x) = \frac, \qquad 0 \ne x \in \mathbf^n. Consider the function: \begin h : \mathbf \to \mathbf \\ h(t) = g(y+tz) \end By calculus, , i.e., \begin h'(0) &= \lim_ \frac \\ &= \lim_ \frac \\ &= \lim_ \frac \left (\frac-\frac \right ) \\ &= \lim_ \frac \left (\frac \right ) \\ &= \frac \lim_ \frac \\ &= \frac \left (\frac \frac \right)(0) \\ &= 0. \end Define: m=\frac After some algebra the above expression becomes ( denotes the real part of a complex number) \operatorname(\langle T y - m y, z \rangle) = 0. But ''z'' is arbitrary, therefore . This is the crux of proof for spectral theorem in the matricial case. Note that while the Lagrange multipliers generalize to the infinite-dimensional case, the compactness of the unit sphere is lost. This is where the assumption that the operator ''T'' be compact is useful.


Details

Claim  If ''T'' is a compact self-adjoint operator on a non-zero Hilbert space ''H'' and m(T) := \sup \bigl\, then ''m''(''T'') or −''m''(''T'') is an eigenvalue of ''T''. If , then ''T'' = 0 by the
polarization identity In linear algebra, a branch of mathematics, the polarization identity is any one of a family of formulas that express the inner product of two vectors in terms of the norm of a normed vector space. If a norm arises from an inner product t ...
, and this case is clear. Consider the function \begin f : H \to \mathbf \\ f(x) = \langle T x, x \rangle \end Replacing ''T'' by −''T'' if necessary, one may assume that the supremum of ''f'' on the closed unit ball ''B'' ⊂ ''H'' is equal to . If ''f'' attains its maximum ''m''(''T'') on ''B'' at some unit vector ''y'', then, by the same argument used for matrices, ''y'' is an eigenvector of ''T'', with corresponding eigenvalue = . By the Banach–Alaoglu theorem and the reflexivity of ''H'', the closed unit ball ''B'' is weakly compact. Also, the compactness of ''T'' means (see above) that ''T'' : ''X'' with the weak topology → ''X'' with the norm topology is continuous . These two facts imply that ''f'' is continuous on ''B'' equipped with the weak topology, and ''f'' attains therefore its maximum ''m'' on ''B'' at some . By maximality, \, y\, =1, which in turn implies that ''y'' also maximizes the Rayleigh quotient ''g''(''x'') (see above). This shows that ''y'' is an eigenvector of ''T'', and ends the proof of the claim. Note. The compactness of ''T'' is crucial. In general, ''f'' need not be continuous for the weak topology on the unit ball ''B''. For example, let ''T'' be the identity operator, which is not compact when ''H'' is infinite-dimensional. Take any orthonormal sequence . Then ''yn'' converges to 0 weakly, but lim ''f''(''yn'') = 1 ≠ 0 = ''f''(0). Let ''T'' be a compact operator on a Hilbert space ''H''. A finite (possibly empty) or countably infinite orthonormal sequence of eigenvectors of ''T'', with corresponding non-zero eigenvalues, is constructed by induction as follows. Let ''H''0 = ''H'' and ''T''0 = ''T''. If ''m''(''T''0) = 0, then ''T'' = 0 and the construction stops without producing any eigenvector ''en''. Suppose that orthonormal eigenvectors of ''T'' have been found. Then is invariant under ''T'', and by self-adjointness, the orthogonal complement ''Hn'' of ''E''''n'' is an invariant subspace of ''T''. Let ''Tn'' denote the restriction of ''T'' to ''Hn''. If ''m''(''Tn'') = 0, then ''Tn'' = 0, and the construction stops. Otherwise, by the ''claim'' applied to ''Tn'', there is a norm one eigenvector ''en'' of ''T'' in ''Hn'', with corresponding non-zero eigenvalue λ''n'' = . Let ''F'' = (span), where is the finite or infinite sequence constructed by the inductive process; by self-adjointness, ''F'' is invariant under ''T''. Let ''S'' denote the restriction of ''T'' to ''F''. If the process was stopped after finitely many steps, with the last vector ''e''''m''−1, then ''F''= ''Hm'' and ''S'' = ''Tm'' = 0 by construction. In the infinite case, compactness of ''T'' and the weak-convergence of ''en'' to 0 imply that , therefore . Since ''F'' is contained in ''Hn'' for every ''n'', it follows that ''m''(''S'') ≤ ''m''() = , ''λn'', for every ''n'', hence ''m''(''S'') = 0. This implies again that . The fact that ''S'' = 0 means that ''F'' is contained in the kernel of ''T''. Conversely, if ''x'' ∈ ker(''T'') then by self-adjointness, ''x'' is orthogonal to every eigenvector with non-zero eigenvalue. It follows that , and that is an orthonormal basis for the orthogonal complement of the kernel of ''T''. One can complete the diagonalization of ''T'' by selecting an orthonormal basis of the kernel. This proves the spectral theorem. A shorter but more abstract proof goes as follows: by
Zorn's lemma Zorn's lemma, also known as the Kuratowski–Zorn lemma, is a proposition of set theory. It states that a partially ordered set containing upper bounds for every chain (that is, every totally ordered subset) necessarily contains at least on ...
, select ''U'' to be a maximal subset of ''H'' with the following three properties: all elements of ''U'' are eigenvectors of ''T'', they have norm one, and any two distinct elements of ''U'' are orthogonal. Let ''F'' be the orthogonal complement of the linear span of ''U''. If ''F'' ≠ , it is a non-trivial invariant subspace of ''T'', and by the initial claim, there must exist a norm one eigenvector ''y'' of ''T'' in ''F''. But then ''U'' ∪ contradicts the maximality of ''U''. It follows that ''F'' = , hence span(''U'') is dense in ''H''. This shows that ''U'' is an orthonormal basis of ''H'' consisting of eigenvectors of ''T''.


Functional calculus

If ''T'' is compact on an infinite-dimensional Hilbert space ''H'', then ''T'' is not invertible, hence σ(''T''), the spectrum of ''T'', always contains 0. The spectral theorem shows that σ(''T'') consists of the eigenvalues of ''T'' and of 0 (if 0 is not already an eigenvalue). The set σ(''T'') is a compact subset of the complex numbers, and the eigenvalues are dense in σ(''T''). Any spectral theorem can be reformulated in terms of a
functional calculus In mathematics, a functional calculus is a theory allowing one to apply mathematical functions to mathematical operators. It is now a branch (more accurately, several related areas) of the field of functional analysis, connected with spectral theo ...
. In the present context, we have: Theorem. Let ''C''(σ(''T'')) denote the
C*-algebra In mathematics, specifically in functional analysis, a C∗-algebra (pronounced "C-star") is a Banach algebra together with an involution satisfying the properties of the adjoint. A particular case is that of a complex algebra ''A'' of contin ...
of continuous functions on σ(''T''). There exists a unique isometric homomorphism such that Φ(1) = ''I'' and, if ''f'' is the identity function , then . Now we may define g(T):=\Phi(g) (clearly this would hold when g is polynomial). Then it also holds, that . The functional calculus map Φ is defined in a natural way: let be an orthonormal basis of eigenvectors for ''H'', with corresponding eigenvalues ; for , the operator Φ(''f''), diagonal with respect to the orthonormal basis , is defined by setting \Phi(f)(e_n) = f(\lambda_n) e_n for every ''n''. Since Φ(''f'') is diagonal with respect to an orthonormal basis, its norm is equal to the supremum of the modulus of diagonal coefficients, \, \Phi(f)\, = \sup_ , f(\lambda_n), = \, f\, _. The other properties of Φ can be readily verified. Conversely, any homomorphism Ψ satisfying the requirements of the theorem must coincide with Φ when ''f'' is a polynomial. By the
Weierstrass approximation theorem Karl Theodor Wilhelm Weierstrass (; ; 31 October 1815 – 19 February 1897) was a German mathematician often cited as the " father of modern analysis". Despite leaving university without a degree, he studied mathematics and trained as a school t ...
, polynomial functions are dense in ''C''(σ(''T'')), and it follows that . This shows that Φ is unique. The more general
continuous functional calculus In mathematics, particularly in operator theory and C*-algebra theory, the continuous functional calculus is a functional calculus which allows the application of a continuous function to normal elements of a C*-algebra. In advanced theory, the ap ...
can be defined for any self-adjoint (or even normal, in the complex case) bounded linear operator on a Hilbert space. The compact case described here is a particularly simple instance of this functional calculus.


Simultaneous diagonalization

Consider an Hilbert space ''H'' (e.g. the finite-dimensional C''n''), and a commuting set \mathcal\subseteq\operatorname(H,H) of self-adjoint operators. Then under suitable conditions, it can be simultaneously (unitarily) diagonalized. ''Viz.'', there exists an orthonormal basis ''Q'' consisting of common eigenvectors for the operators — i.e., (\forall)(\exists)(T-\sigma)q=0 Notice we did not have to directly use the machinery of matrices at all in this proof. There are other versions which do. We can strengthen the above to the case where all the operators merely commute with their adjoint; in this case we remove the term "orthogonal" from the diagonalisation. There are weaker results for operators arising from representations due to Weyl–Peter. Let ''G'' be a fixed locally compact hausdorff group, and H=L^2(G) (the space of square integrable measurable functions with respect to the unique-up-to-scale Haar measure on ''G''). Consider the continuous shift action: \begin G\times H\to H \\ (gf)(x)=f(g^x) \end Then if ''G'' were compact then there is a unique decomposition of ''H'' into a countable direct sum of finite-dimensional, irreducible, invariant subspaces (this is essentially diagonalisation of the family of operators G\subseteq U(H)). If ''G'' were not compact, but were abelian, then diagonalisation is not achieved, but we get a unique ''continuous'' decomposition of ''H'' into 1-dimensional invariant subspaces.


Compact normal operator

The family of Hermitian matrices is a proper subset of matrices that are unitarily diagonalizable. A matrix ''M'' is unitarily diagonalizable if and only if it is normal, i.e., ''M*M'' = ''MM*''. Similar statements hold for compact normal operators. Let ''T'' be compact and ''T*T'' = ''TT*''. Apply the ''Cartesian decomposition'' to ''T'': define R = \frac, \quad J = \frac. The self-adjoint compact operators ''R'' and ''J'' are called the real and imaginary parts of ''T,'' respectively. That ''T'' is compact implies that ''T*'' and, consequently, ''R'' and ''J'' are compact. Furthermore, the normality of ''T'' implies that ''R'' and ''J'' commute. Therefore they can be simultaneously diagonalized, from which follows the claim. A hyponormal compact operator (in particular, a subnormal operator) is normal.


Unitary operator

The spectrum of a
unitary operator In functional analysis, a unitary operator is a surjective bounded operator on a Hilbert space that preserves the inner product. Non-trivial examples include rotations, reflections, and the Fourier operator. Unitary operators generalize unitar ...
''U'' lies on the unit circle in the complex plane; it could be the entire unit circle. However, if ''U'' is identity plus a compact perturbation, ''U'' has only a countable spectrum, containing 1 and possibly, a finite set or a sequence tending to 1 on the unit circle. More precisely, suppose where ''C'' is compact. The equations and show that ''C'' is normal. The spectrum of ''C'' contains 0, and possibly, a finite set or a sequence tending to 0. Since , the spectrum of ''U'' is obtained by shifting the spectrum of ''C'' by 1.


Examples

* Let ''H'' = ''L''2( , 1. The multiplication operator ''M'' defined by (M f)(x) = x f(x), \quad f \in H, \, \, x \in
, 1 The comma is a punctuation mark that appears in several variants in different languages. Some typefaces render it as a small line, slightly curved or straight, but inclined from the vertical; others give it the appearance of a miniature fille ...
/math> is a bounded self-adjoint operator on ''H'' that has no eigenvector and hence, by the spectral theorem, cannot be compact. * An example of a compact operator on a Hilbert space that is not self-adjoint is the Volterra operator, defined for a function f\in L^2( ,1 and a value t \in ,1/math> as V(f)(t) = \int_^ f(s)\, ds. It is the operator corresponding to the Volterra integral equations. * Define a Hilbert-Schmidt kernel K: \Omega \times \Omega \to \mathbb on \Omega = ,1/math> and its associated Hilbert-Schmidt integral operator T_K : L^(\Omega)\to L^2(\Omega) as (T_K f)(x) = \int_0^1 K(x, y) f(y) \, \mathrm y. Then T_K is a compact operator; it is a
Hilbert–Schmidt operator In mathematics, a Hilbert–Schmidt operator, named after David Hilbert and Erhard Schmidt, is a bounded operator A \colon H \to H that acts on a Hilbert space H and has finite Hilbert–Schmidt norm \, A\, ^2_ \ \stackrel\ \sum_ \, Ae_i\, ^ ...
with Hilbert-Schmidt norm \, T_k\, _=\, K\, _. * T_K is a compact self-adjoint operator if and only if K(x,y) is a hermitian kernel which, according to
Mercer's theorem In mathematics, specifically functional analysis, Mercer's theorem is a representation of a symmetric positive-definite function on a square as a sum of a convergent sequence of product functions. This theorem, presented in , is one of the most ...
, can be represented as K(x, y) = \sum \lambda_n \varphi_n(x) \overline, where \ is an orthonormal basis of eigenvectors of T_K, with eigenvalues \ and the sum converges absolutely and uniformly on ,1/math>.


See also

* * * − If the compactness assumption is removed, operators need not have countable spectrum in general. * * − The notion of singular values can be extended from matrices to compact operators. * *


References

*J. Blank, P. Exner, and M. Havlicek, ''Hilbert Space Operators in Quantum Physics'', American Institute of Physics, 1994. *M. Reed and B. Simon, ''Methods of Modern Mathematical Physics I: Functional Analysis'', Academic Press, 1972. * {{Hilbert space Hilbert spaces Articles containing proofs Operator theory Linear operators