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In
mathematics Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many ar ...
, more specifically
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 ...
and
operator theory In mathematics, operator theory is the study of linear operators on function spaces, beginning with differential operators and integral operators. The operators may be presented abstractly by their characteristics, such as bounded linear operato ...
, the notion of unbounded operator provides an abstract framework for dealing with differential operators, unbounded
observable In physics, an observable is a physical property or physical quantity that can be measured. In classical mechanics, an observable is a real-valued "function" on the set of all possible system states, e.g., position and momentum. In quantum ...
s in
quantum mechanics Quantum mechanics is the fundamental physical Scientific theory, theory that describes the behavior of matter and of light; its unusual characteristics typically occur at and below the scale of atoms. Reprinted, Addison-Wesley, 1989, It is ...
, and other cases. The term "unbounded operator" can be misleading, since * "unbounded" should sometimes be understood as "not necessarily bounded"; * "operator" should be understood as "
linear operator In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping V \to W between two vector spaces that pr ...
" (as in the case of "bounded operator"); * the domain of the operator is a
linear subspace In mathematics, the term ''linear'' is used in two distinct senses for two different properties: * linearity of a ''function (mathematics), function'' (or ''mapping (mathematics), mapping''); * linearity of a ''polynomial''. An example of a li ...
, not necessarily the whole space; * this linear subspace is not necessarily closed; often (but not always) it is assumed to be dense; * in the special case of a bounded operator, still, the domain is usually assumed to be the whole space. In contrast to bounded operators, unbounded operators on a given space do not form an
algebra Algebra is a branch of mathematics that deals with abstract systems, known as algebraic structures, and the manipulation of expressions within those systems. It is a generalization of arithmetic that introduces variables and algebraic ope ...
, nor even a linear space, because each one is defined on its own domain. The term "operator" often means "bounded linear operator", but in the context of this article it means "unbounded operator", with the reservations made above.


Short history

The theory of unbounded operators developed in the late 1920s and early 1930s as part of developing a rigorous mathematical framework for
quantum mechanics Quantum mechanics is the fundamental physical Scientific theory, theory that describes the behavior of matter and of light; its unusual characteristics typically occur at and below the scale of atoms. Reprinted, Addison-Wesley, 1989, It is ...
. The theory's development is due to
John von Neumann John von Neumann ( ; ; December 28, 1903 – February 8, 1957) was a Hungarian and American mathematician, physicist, computer scientist and engineer. Von Neumann had perhaps the widest coverage of any mathematician of his time, in ...
and Marshall Stone. Von Neumann introduced using graphs to analyze unbounded operators in 1932.


Definitions and basic properties

Let be
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. An unbounded operator (or simply ''operator'') is a
linear map In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping V \to W between two vector spaces that p ...
from a linear subspace —the domain of —to the space . Contrary to the usual convention, may not be defined on the whole space . An operator is said to be closed if its graph is a
closed set In geometry, topology, and related branches of mathematics, a closed set is a Set (mathematics), set whose complement (set theory), complement is an open set. In a topological space, a closed set can be defined as a set which contains all its lim ...
. (Here, the graph is a linear subspace of the
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 ...
, defined as the set of all pairs , where runs over the domain of  .) Explicitly, this means that for every sequence of points from the domain of such that and , it holds that belongs to the domain of and . The closedness can also be formulated in terms of the ''graph norm'': an operator is closed if and only if its domain is a complete space with respect to the norm: : \, x\, _T = \sqrt. An operator is said to be densely defined if its domain is dense in . This also includes operators defined on the entire space , since the whole space is dense in itself. The denseness of the domain is necessary and sufficient for the existence of the adjoint (if and are Hilbert spaces) and the transpose; see the sections below. If is closed, densely defined and continuous on its domain, then its domain is all of .Suppose ''fj'' is a sequence in the domain of that converges to . Since is uniformly continuous on its domain, ''Tfj'' is Cauchy in . Thus, is Cauchy and so converges to some since the graph of is closed. Hence, , and the domain of is closed. A densely defined symmetric operator on 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 ...
is called bounded from below if is a positive operator for some real number . That is, for all in the domain of (or alternatively since is arbitrary). If both and are bounded from below then is bounded.


Example

Let denote the space of continuous functions on the unit interval, and let denote the space of continuously differentiable functions. We equip C( ,1 with the supremum norm, \, \cdot\, _, making it a Banach space. Define the classical differentiation operator by the usual formula: : \left (\fracf \right )(x) = \lim_ \frac, \qquad \forall 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 ...
Every differentiable function is continuous, so . We claim that is a well-defined unbounded operator, with domain . For this, we need to show that \frac is linear and then, for example, exhibit some \_n \subset C^1( ,1 such that \, f_n\, _\infty=1 and \sup_n \, \frac f_n\, _\infty=+\infty. This is a linear operator, since a linear combination of two continuously differentiable functions is also continuously differentiable, and :\left (\tfrac \right )(af+bg)= a \left (\tfrac f \right ) + b \left (\tfrac g \right ). The operator is not bounded. For example, :\begin f_n :
, 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 ...
\to
1, 1 Onekama ( ) is a village in Manistee County in the U.S. state of Michigan. The population was 399 at the 2020 census. The village is located on the northeast shore of Portage Lake and is surrounded by Onekama Township. The town's name is deri ...
\\ f_n(x) = \sin (2\pi n x) \end satisfy : \left \, f_n \right \, _ = 1, but : \left \, \left (\tfrac f_n \right ) \right \, _ = 2\pi n \to \infty as n\to\infty. The operator is densely defined (which can be shown by the Weierstrass approximation theorem, since the set of polynomial functions on ,1is contained in , while also being dense in ) and closed. The same operator can be treated as an operator for many choices of Banach space and not be bounded between any of them. At the same time, it can be bounded as an operator for other pairs of Banach spaces , and also as operator for some topological vector spaces . As an example let be an open interval and consider :\frac : \left (C^1 (I), \, \cdot \, _ \right ) \to \left ( C (I), \, \cdot \, _ \right), where: :\, f \, _ = \, f \, _ + \, f' \, _.


Adjoint

The adjoint of an unbounded operator can be defined in two equivalent ways. Let T : D(T) \subseteq H_1 \to H_2 be an unbounded operator between Hilbert spaces. First, it can be defined in a way analogous to how one defines the adjoint of a bounded operator. Namely, the adjoint T^* : D\left(T^*\right) \subseteq H_2 \to H_1 of is defined as an operator with the property: \langle Tx \mid y \rangle_2 = \left \langle x \mid T^*y \right \rangle_1, \qquad x \in D(T). More precisely, T^* y is defined in the following way. If y \in H_2 is such that x \mapsto \langle Tx \mid y \rangle is a continuous linear functional on the domain of , then y is declared to be an element of D\left(T^*\right), and after extending the linear functional to the whole space via the
Hahn–Banach theorem In functional analysis, the Hahn–Banach theorem is a central result that allows the extension of bounded linear functionals defined on a vector subspace of some vector space to the whole space. The theorem also shows that there are sufficient ...
, it is possible to find some z in H_1 such that \langle Tx \mid y \rangle_2 = \langle x \mid z \rangle_1, \qquad x \in D(T), since Riesz representation theorem allows the continuous dual of the Hilbert space H_1 to be identified with the set of linear functionals given by the inner product. This vector z is uniquely determined by y if and only if the linear functional x \mapsto \langle Tx \mid y \rangle is densely defined; or equivalently, if is densely defined. Finally, letting T^* y = z completes the construction of T^*, which is necessarily a linear map. The adjoint T^* y exists if and only if is densely defined. By definition, the domain of T^* consists of elements y in H_2 such that x \mapsto \langle Tx \mid y \rangle is continuous on the domain of . Consequently, the domain of T^* could be anything; it could be trivial (that is, contains only zero). It may happen that the domain of T^* is a closed
hyperplane In geometry, a hyperplane is a generalization of a two-dimensional plane in three-dimensional space to mathematical spaces of arbitrary dimension. Like a plane in space, a hyperplane is a flat hypersurface, a subspace whose dimension is ...
and T^* vanishes everywhere on the domain. Thus, boundedness of T^* on its domain does not imply boundedness of . On the other hand, if T^* is defined on the whole space then is bounded on its domain and therefore can be extended by continuity to a bounded operator on the whole space.Proof: being closed, the everywhere defined T^* is bounded, which implies boundedness of T^, the latter being the closure of . See also for the case of everywhere defined . If the domain of T^* is dense, then it has its adjoint T^. A closed densely defined operator is bounded if and only if T^* is bounded.Proof: T^ = T. So if T^* is bounded then its adjoint is bounded. The other equivalent definition of the adjoint can be obtained by noticing a general fact. Define a linear operator J as follows: \begin J: H_1 \oplus H_2 \to H_2 \oplus H_1 \\ J(x \oplus y) = -y \oplus x \end Since J is an isometric surjection, it is unitary. Hence: J(\Gamma(T))^ is the graph of some operator S if and only if is densely defined. A simple calculation shows that this "some" S satisfies: \langle Tx \mid y \rangle_2 = \langle x \mid Sy \rangle_1, for every in the domain of . Thus S is the adjoint of . It follows immediately from the above definition that the adjoint T^* is closed. In particular, a self-adjoint operator (meaning T = T^*) is closed. An operator is closed and densely defined if and only if T^ = T.Proof: If is closed densely defined then T^* exists and is densely defined. Thus T^ exists. The graph of is dense in the graph of T^; hence T = T^. Conversely, since the existence of T^ implies that that of T^*, which in turn implies is densely defined. Since T^ is closed, is densely defined and closed. Some well-known properties for bounded operators generalize to closed densely defined operators. The kernel of a closed operator is closed. Moreover, the kernel of a closed densely defined operator T : H_1 \to H_2 coincides with the orthogonal complement of the range of the adjoint. That is, \operatorname(T) = \operatorname(T^*)^\bot. von Neumann's theorem states that T^* T and T T^* are self-adjoint, and that I + T^* T and I + T T^* both have bounded inverses. If T^* has trivial kernel, has dense range (by the above identity.) Moreover: : is surjective if and only if there is a K > 0 such that \, f\, _2 \leq K \left\, T^* f\right\, _1 for all f in D\left(T^*\right).If T is surjective then T : (\ker T)^ \to H_2 has bounded inverse, denoted by S. The estimate then follows since \, f\, _2^2 = \left , \langle TSf \mid f \rangle_2 \right , \leq \, S\, \, f\, _2 \left \, T^*f \right \, _1 Conversely, suppose the estimate holds. Since T^* has closed range, it is the case that \operatorname(T) = \operatorname\left(T T^*\right). Since \operatorname(T) is dense, it suffices to show that T T^* has closed range. If T T^* f_j is convergent then f_j is convergent by the estimate since \, T^*f_j\, _1^2 = , \langle T^*f_j \mid T^*f_j \rangle_1, \leq \, TT^*f_j\, _2 \, f_j\, _2. Say, f_j \to g. Since T T^* is self-adjoint; thus, closed, (von Neumann's theorem), T T^* f_j \to T T^* g. QED (This is essentially a variant of the so-called closed range theorem.) In particular, has closed range if and only if T^* has closed range. In contrast to the bounded case, it is not necessary that (T S)^* = S^* T^*, since, for example, it is even possible that (T S)^* does not exist. This is, however, the case if, for example, is bounded. A densely defined, closed operator is called '' normal'' if it satisfies the following equivalent conditions: * T^* T = T T^*; * the domain of is equal to the domain of T^*, and \, T x\, = \left\, T^* x\right\, for every in this domain; * there exist self-adjoint operators A, B such that T = A + i B,T^* = A - i B, and \, T x\, ^2 = \, A x\, ^2 + \, B x\, ^2 for every in the domain of . Every self-adjoint operator is normal.


Transpose

Let T : B_1 \to B_2 be an operator between Banach spaces. Then the ''
transpose In linear algebra, the transpose of a Matrix (mathematics), matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix by producing another matrix, often denoted by (among other ...
'' (or ''dual'') ^t T: ^* \to ^* of T is the linear operator satisfying: \langle T x, y' \rangle = \langle x, \left(^t T\right) y' \rangle for all x \in B_1 and y \in B_2^*. Here, we used the notation: \langle x, x' \rangle = x'(x). The necessary and sufficient condition for the transpose of T to exist is that T is densely defined (for essentially the same reason as to adjoints, as discussed above.) For any Hilbert space H, there is the anti-linear isomorphism: J: H^* \to H given by J f = y where f(x) = \langle x \mid y \rangle_H, (x \in H). Through this isomorphism, the transpose ^t T relates to the adjoint T^* in the following way: T^* = J_1 \left(^t T\right) J_2^, where J_j: H_j^* \to H_j. (For the finite-dimensional case, this corresponds to the fact that the adjoint of a matrix is its conjugate transpose.) Note that this gives the definition of adjoint in terms of a transpose.


Closed linear operators

Closed linear operators are a class of
linear operator In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping V \to W between two vector spaces that pr ...
s 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. They are more general than bounded operators, and therefore not necessarily continuous, but they still retain nice enough properties that one can define 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 ...
and (with certain assumptions) functional calculus for such operators. Many important linear operators which fail to be bounded turn out to be closed, such as the
derivative In mathematics, the derivative is a fundamental tool that quantifies the sensitivity to change of a function's output with respect to its input. The derivative of a function of a single variable at a chosen input value, when it exists, is t ...
and a large class of differential operators. Let be two
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. A
linear operator In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping V \to W between two vector spaces that pr ...
is closed if for every
sequence In mathematics, a sequence is an enumerated collection of objects in which repetitions are allowed and order matters. Like a set, it contains members (also called ''elements'', or ''terms''). The number of elements (possibly infinite) is cal ...
in converging to in such that as one has and . Equivalently, is closed if its graph is closed in the
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 ...
. Given a linear operator , not necessarily closed, if the closure of its graph in happens to be the graph of some operator, that operator is called the closure of , and we say that is closable. Denote the closure of by . It follows that is the restriction of to . A core (or essential domain) of a closable operator is a
subset In mathematics, a Set (mathematics), set ''A'' is a subset of a set ''B'' if all Element (mathematics), elements of ''A'' are also elements of ''B''; ''B'' is then a superset of ''A''. It is possible for ''A'' and ''B'' to be equal; if they a ...
of such that the closure of the restriction of to is .


Example

Consider the
derivative In mathematics, the derivative is a fundamental tool that quantifies the sensitivity to change of a function's output with respect to its input. The derivative of a function of a single variable at a chosen input value, when it exists, is t ...
operator where is the Banach space of all
continuous function In mathematics, a continuous function is a function such that a small variation of the argument induces a small variation of the value of the function. This implies there are no abrupt changes in value, known as '' discontinuities''. More preci ...
s on an interval . If one takes its domain to be , then is a closed operator which is not bounded. On the other hand if , then will no longer be closed, but it will be closable, with the closure being its extension defined on .


Symmetric operators and self-adjoint operators

An operator ''T'' on a Hilbert space is ''symmetric'' if and only if for each ''x'' and ''y'' in the domain of we have \langle Tx \mid y \rangle = \lang x \mid Ty \rang. A densely defined operator is symmetric if and only if it agrees with its adjoint ''T'' restricted to the domain of ''T'', in other words when ''T'' is an extension of . In general, if ''T'' is densely defined and symmetric, the domain of the adjoint ''T'' need not equal the domain of ''T''. If ''T'' is symmetric and the domain of ''T'' and the domain of the adjoint coincide, then we say that ''T'' is ''self-adjoint''. Note that, when ''T'' is self-adjoint, the existence of the adjoint implies that ''T'' is densely defined and since ''T'' is necessarily closed, ''T'' is closed. A densely defined operator ''T'' is ''symmetric'', if the subspace (defined in a previous section) is orthogonal to its image under ''J'' (where ''J''(''x'',''y''):=(''y'',-''x'')).Follows from and the definition via adjoint operators. Equivalently, an operator ''T'' is ''self-adjoint'' if it is densely defined, closed, symmetric, and satisfies the fourth condition: both operators , are surjective, that is, map the domain of ''T'' onto the whole space ''H''. In other words: for every ''x'' in ''H'' there exist ''y'' and ''z'' in the domain of ''T'' such that and . An operator ''T'' is ''self-adjoint'', if the two subspaces , are orthogonal and their sum is the whole space H \oplus H . This approach does not cover non-densely defined closed operators. Non-densely defined symmetric operators can be defined directly or via graphs, but not via adjoint operators. A symmetric operator is often studied via its
Cayley transform In mathematics, the Cayley transform, named after Arthur Cayley, is any of a cluster of related things. As originally described by , the Cayley transform is a mapping between skew-symmetric matrices and special orthogonal matrices. The transform ...
. An operator ''T'' on a complex Hilbert space is symmetric if and only if the number \langle Tx \mid x \rangle is real for all ''x'' in the domain of ''T''. A densely defined closed symmetric operator ''T'' is self-adjoint if and only if ''T'' is symmetric. It may happen that it is not. A densely defined operator ''T'' is called ''positive'' (or ''nonnegative'') if its quadratic form is nonnegative, that is, \langle Tx \mid x \rangle \ge 0 for all ''x'' in the domain of ''T''. Such operator is necessarily symmetric. The operator ''T''''T'' is self-adjoint and positive for every densely defined, closed ''T''. 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 ...
applies to self-adjoint operators and moreover, to normal operators, but not to densely defined, closed operators in general, since in this case the spectrum can be empty. A symmetric operator defined everywhere is closed, therefore bounded, which is the Hellinger–Toeplitz theorem.


Extension-related

By definition, an operator ''T'' is an ''extension'' of an operator ''S'' if . An equivalent direct definition: for every ''x'' in the domain of ''S'', ''x'' belongs to the domain of ''T'' and . Note that an everywhere defined extension exists for every operator, which is a purely algebraic fact explained at and based on the
axiom of choice In mathematics, the axiom of choice, abbreviated AC or AoC, is an axiom of set theory. Informally put, the axiom of choice says that given any collection of non-empty sets, it is possible to construct a new set by choosing one element from e ...
. If the given operator is not bounded then the extension is a discontinuous linear map. It is of little use since it cannot preserve important properties of the given operator (see below), and usually is highly non-unique. An operator ''T'' is called ''closable'' if it satisfies the following equivalent conditions: * ''T'' has a closed extension; * the closure of the graph of ''T'' is the graph of some operator; * for every sequence (''xn'') of points from the domain of ''T'' such that ''xn'' → 0 and also ''Txn'' → ''y'' it holds that . Not all operators are closable. A closable operator ''T'' has the least closed extension \overline T called the ''closure'' of ''T''. The closure of the graph of ''T'' is equal to the graph of \overline T. Other, non-minimal closed extensions may exist. A densely defined operator ''T'' is closable if and only if ''T'' is densely defined. In this case \overline T = T^ and (\overline T)^* = T^*. If ''S'' is densely defined and ''T'' is an extension of ''S'' then ''S'' is an extension of ''T''. Every symmetric operator is closable. A symmetric operator is called ''maximal symmetric'' if it has no symmetric extensions, except for itself. Every self-adjoint operator is maximal symmetric. The converse is wrong. An operator is called ''essentially self-adjoint'' if its closure is self-adjoint. An operator is essentially self-adjoint if and only if it has one and only one self-adjoint extension. A symmetric operator may have more than one self-adjoint extension, and even a continuum of them. A densely defined, symmetric operator ''T'' is essentially self-adjoint if and only if both operators , have dense range. Let ''T'' be a densely defined operator. Denoting the relation "''T'' is an extension of ''S''" by ''S'' ⊂ ''T'' (a conventional abbreviation for Γ(''S'') ⊆ Γ(''T'')) one has the following. * If ''T'' is symmetric then ''T'' ⊂ ''T''∗∗ ⊂ ''T''. * If ''T'' is closed and symmetric then ''T'' = ''T''∗∗ ⊂ ''T''. * If ''T'' is self-adjoint then ''T'' = ''T''∗∗ = ''T''. * If ''T'' is essentially self-adjoint then ''T'' ⊂ ''T''∗∗ = ''T''.


Importance of self-adjoint operators

The class of self-adjoint operators is especially important in mathematical physics. Every self-adjoint operator is densely defined, closed and symmetric. The converse holds for bounded operators but fails in general. Self-adjointness is substantially more restricting than these three properties. The famous
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 ...
holds for self-adjoint operators. In combination with Stone's theorem on one-parameter unitary groups it shows that self-adjoint operators are precisely the infinitesimal generators of strongly continuous one-parameter unitary groups, see . Such unitary groups are especially important for describing time evolution in classical and quantum mechanics.


See also

* * Stone–von Neumann theorem * Bounded operator


Notes


References


Citations


Bibliography

* (see Chapter 12 "General theory of unbounded operators in Hilbert spaces"). * * * * * * (see Chapter 5 "Unbounded operators"). * (see Chapter 8 "Unbounded operators"). * * * * * {{DEFAULTSORT:Unbounded Operator Linear operators Operator theory de:Linearer Operator#Unbeschränkte lineare Operatoren