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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 ...
, specifically in
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 ...
, each
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 ...
A on an
inner product space In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar, ofte ...
defines a Hermitian adjoint (or adjoint) operator A^* on that space according to the rule :\langle Ax,y \rangle = \langle x,A^*y \rangle, where \langle \cdot,\cdot \rangle is the
inner product In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar, ofte ...
on the
vector space In mathematics and physics, a vector space (also called a linear space) is a set (mathematics), set whose elements, often called vector (mathematics and physics), ''vectors'', can be added together and multiplied ("scaled") by numbers called sc ...
. The adjoint may also be called the Hermitian conjugate or simply the Hermitian after Charles Hermite. It is often denoted by in fields like
physics Physics is the scientific study of matter, its Elementary particle, fundamental constituents, its motion and behavior through space and time, and the related entities of energy and force. "Physical science is that department of knowledge whi ...
, especially when used in conjunction with
bra–ket notation Bra–ket notation, also called Dirac notation, is a notation for linear algebra and linear operators on complex vector spaces together with their dual space both in the finite-dimensional and infinite-dimensional case. It is specifically de ...
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 ...
. In finite dimensions where operators can be represented by
matrices Matrix (: matrices or matrixes) or MATRIX may refer to: Science and mathematics * Matrix (mathematics), a rectangular array of numbers, symbols or expressions * Matrix (logic), part of a formula in prenex normal form * Matrix (biology), the ...
, the Hermitian adjoint is given by the
conjugate transpose In mathematics, the conjugate transpose, also known as the Hermitian transpose, of an m \times n complex matrix \mathbf is an n \times m matrix obtained by transposing \mathbf and applying complex conjugation to each entry (the complex conjugate ...
(also known as the Hermitian transpose). The above definition of an adjoint operator extends verbatim to bounded linear operators on
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 ...
s H. The definition has been further extended to include unbounded '' densely defined'' operators, whose domain is topologically dense in, but not necessarily equal to, H.


Informal definition

Consider 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 ...
A: H_1\to H_2 between
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 ...
s. Without taking care of any details, the adjoint operator is the (in most cases uniquely defined) linear operator A^* : H_2 \to H_1 fulfilling :\left\langle A h_1, h_2 \right\rangle_ = \left\langle h_1, A^* h_2 \right\rangle_, where \langle\cdot, \cdot \rangle_ is the
inner product In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar, ofte ...
in the Hilbert space H_i, which is linear in the first coordinate and conjugate linear in the second coordinate. Note the special case where both Hilbert spaces are identical and A is an operator on that Hilbert space. When one trades the inner product for the dual pairing, one can define the adjoint, also called 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 ...
, of an operator A: E \to F, where E, F are
Banach spaces 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 ...
with corresponding norms \, \cdot\, _E, \, \cdot\, _F. Here (again not considering any technicalities), its adjoint operator is defined as A^*: F^* \to E^* with :A^*f = f \circ A : u \mapsto f(Au), i.e., \left(A^*f\right)(u) = f(Au) for f \in F^*, u \in E. The above definition in the Hilbert space setting is really just an application of the Banach space case when one identifies a Hilbert space with its dual (via the
Riesz representation theorem The Riesz representation theorem, sometimes called the Riesz–Fréchet representation theorem after Frigyes Riesz and Maurice René Fréchet, establishes an important connection between a Hilbert space and its continuous dual space. If the un ...
). Then it is only natural that we can also obtain the adjoint of an operator A: H \to E, where H is a Hilbert space and E is a Banach space. The dual is then defined as A^*: E^* \to H with A^*f = h_f such that :\langle h_f, h\rangle_H = f(Ah).


Definition for unbounded operators between Banach spaces

Let \left(E, \, \cdot\, _E\right), \left(F, \, \cdot\, _F\right) 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. Suppose A: D(A) \to F and D(A) \subset E, and suppose that A is a (possibly unbounded) linear operator which is densely defined (i.e., D(A) is dense in E). Then its adjoint operator A^* is defined as follows. The domain is :D\left(A^*\right) := \left\. Now for arbitrary but fixed g \in D(A^*) we set f: D(A) \to \R with f(u) = g(Au). By choice of g and definition of D(A^*), f is (uniformly) continuous on D(A) as , f(u), = , g(Au), \leq c\cdot \, u\, _E. Then by 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 ...
, or alternatively through extension by continuity, this yields an extension of f, called \hat, defined on all of E. This technicality is necessary to later obtain A^* as an operator D\left(A^*\right) \to E^* instead of D\left(A^*\right) \to (D(A))^*. Remark also that this does not mean that A can be extended on all of E but the extension only worked for specific elements g \in D\left(A^*\right). Now, we can define the adjoint of A as :\begin A^*: F^* \supset D(A^*) &\to E^* \\ g &\mapsto A^*g = \hat f. \end The fundamental defining identity is thus :g(Au) = \left(A^* g\right)(u) for u \in D(A).


Definition for bounded operators between Hilbert spaces

Suppose is a complex
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 ...
, with
inner product In mathematics, an inner product space (or, rarely, a Hausdorff pre-Hilbert space) is a real vector space or a complex vector space with an operation called an inner product. The inner product of two vectors in the space is a scalar, ofte ...
\langle\cdot,\cdot\rangle. Consider a continuous
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 ...
(for linear operators, continuity is equivalent to being a
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 ...
). Then the adjoint of is the continuous linear operator satisfying : \langle Ax , y \rangle = \left\langle x , A^* y\right\rangle \quad \mbox x, y \in H. Existence and uniqueness of this operator follows from the
Riesz representation theorem The Riesz representation theorem, sometimes called the Riesz–Fréchet representation theorem after Frigyes Riesz and Maurice René Fréchet, establishes an important connection between a Hilbert space and its continuous dual space. If the un ...
.; This can be seen as a generalization of the ''adjoint'' matrix of a square matrix which has a similar property involving the standard complex inner product.


Properties

The following properties of the Hermitian adjoint 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 are immediate: # Involutivity: # If is invertible, then so is , with \left(A^*\right)^ = \left(A^\right)^* # Conjugate linearity: #* #* , where denotes the
complex conjugate In mathematics, the complex conjugate of a complex number is the number with an equal real part and an imaginary part equal in magnitude but opposite in sign. That is, if a and b are real numbers, then the complex conjugate of a + bi is a - ...
of the
complex number In mathematics, a complex number is an element of a number system that extends the real numbers with a specific element denoted , called the imaginary unit and satisfying the equation i^= -1; every complex number can be expressed in the for ...
# " Anti-distributivity": If we define 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 ...
of by :\, A \, _\text := \sup \left\ then :\left\, A^* \right\, _\text = \, A\, _\text. Moreover, :\left\, A^* A \right\, _\text = \, A\, _\text^2. One says that a norm that satisfies this condition behaves like a "largest value", extrapolating from the case of self-adjoint operators. The set of bounded linear operators on a complex Hilbert space together with the adjoint operation and the operator norm form the prototype of a
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 ...
.


Adjoint of densely defined unbounded operators between Hilbert spaces


Definition

Let the inner product \langle \cdot, \cdot \rangle be linear in the ''first'' argument. A densely defined operator from a complex Hilbert space to itself is a linear operator whose domain is a dense
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 ...
of and whose values lie in . By definition, the domain of its adjoint is the set of all for which there is a satisfying : \langle Ax , y \rangle = \langle x , z \rangle \quad \mbox x \in D(A). Owing to the density of D(A) and
Riesz representation theorem The Riesz representation theorem, sometimes called the Riesz–Fréchet representation theorem after Frigyes Riesz and Maurice René Fréchet, establishes an important connection between a Hilbert space and its continuous dual space. If the un ...
, z is uniquely defined, and, by definition, A^*y=z. Properties 1.–5. hold with appropriate clauses about domains and
codomain In mathematics, a codomain, counter-domain, or set of destination of a function is a set into which all of the output of the function is constrained to fall. It is the set in the notation . The term '' range'' is sometimes ambiguously used to ...
s. For instance, the last property now states that is an extension of if , and are densely defined operators.


ker A=(im A)

For every y \in \ker A^*, the linear functional x \mapsto \langle Ax,y \rangle = \langle x,A^*y\rangle is identically zero, and hence y \in (\operatorname A)^\perp. Conversely, the assumption that y \in (\operatorname A)^\perp causes the functional x \mapsto \langle Ax,y \rangle to be identically zero. Since the functional is obviously bounded, the definition of A^* assures that y \in D(A^*). The fact that, for every x \in D(A), \langle Ax,y \rangle = \langle x,A^*y\rangle = 0 shows that A^* y \in D(A)^\perp =\overline^\perp = \, given that D(A) is dense. This property shows that \operatornameA^* is a topologically closed subspace even when D(A^*) is not.


Geometric interpretation

If H_1 and H_2 are Hilbert spaces, then H_1 \oplus H_2 is a Hilbert space with the inner product :\bigl \langle (a,b),(c,d) \bigr \rangle_ \stackrel \langle a,c \rangle_ + \langle b,d \rangle_, where a,c \in H_1 and b,d \in H_2. Let J\colon H\oplus H \to H \oplus H be the symplectic mapping, i.e. J(\xi, \eta) = (-\eta, \xi). Then the graph :G(A^*) =\ \subseteq H \oplus H of A^* is 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 ...
of JG(A): :G(A^*) = (JG(A))^\perp = \. The assertion follows from the equivalences : \bigl \langle (x, y) , (-A\xi, \xi) \bigr \rangle = 0 \quad \Leftrightarrow \quad \langle A\xi, x \rangle = \langle \xi, y \rangle, and :\Bigl \forall \xi \in D(A)\ \ \langle A\xi, x \rangle = \langle \xi, y \rangle \Bigr \quad \Leftrightarrow \quad x \in D(A^*)\ \&\ y = A^*x.


Corollaries


=A is closed

= An operator A is ''closed'' if the graph G(A) is topologically closed in H \oplus H. The graph G(A^*) of the adjoint operator A^* is the orthogonal complement of a subspace, and therefore is closed.


=A is densely defined ⇔ A is closable

= An operator A is ''closable'' if the topological closure G^\text(A) \subseteq H \oplus H of the graph G(A) is the graph of a function. Since G^\text(A) is a (closed) linear subspace, the word "function" may be replaced with "linear operator". For the same reason, A is closable if and only if (0,v) \notin G^\text(A) unless v=0. The adjoint A^* is densely defined if and only if A is closable. This follows from the fact that, for every v \in H, :v \in D(A^*)^\perp\ \Leftrightarrow\ (0,v) \in G^\text(A), which, in turn, is proven through the following chain of equivalencies: : \begin v \in D(A^*)^\perp &\Longleftrightarrow (v,0) \in G(A^*)^\perp \Longleftrightarrow (v,0) \in (JG(A))^\text = JG^\text(A) \\ &\Longleftrightarrow (0,-v) = J^(v,0) \in G^\text(A) \\ &\Longleftrightarrow (0,v) \in G^\text(A). \end


=A = A

= The ''closure'' A^\text of an operator A is the operator whose graph is G^\text(A) if this graph represents a function. As above, the word "function" may be replaced with "operator". Furthermore, A^ = A^, meaning that G(A^) = G^(A). To prove this, observe that J^* = -J, i.e. \langle Jx,y\rangle_ = -\langle x,Jy\rangle_, for every x,y \in H \oplus H. Indeed, : \begin \langle J(x_1,x_2),(y_1,y_2)\rangle_ &= \langle (-x_2,x_1),(y_1,y_2)\rangle_ = \langle -x_2,y_1\rangle_H + \langle x_1,y_2 \rangle_H \\ &= \langle x_1,y_2 \rangle_H + \langle x_2,-y_1 \rangle_H = \langle (x_1,x_2),-J(y_1,y_2)\rangle_. \end In particular, for every y \in H \oplus H and every subspace V \subseteq H \oplus H, y \in (JV)^\perp if and only if Jy \in V^\perp. Thus, J JV)^\perp= V^\perp and [(JV)^\perp^\perp = V^\text. Substituting V = G(A), obtain G^\text(A) = G(A^).


=A = (A)

= For a closable operator A, A^* = \left(A^\text\right)^*, meaning that G(A^*) = G\left(\left(A^\text\right)^*\right). Indeed, : G\left(\left(A^\text\right)^*\right) = \left(JG^\text(A)\right)^\perp = \left(\left(JG(A)\right)^\text\right)^\perp = (JG(A))^\perp = G(A^*).


Counterexample where the adjoint is not densely defined

Let H=L^2(\mathbb,l), where l is the linear measure. Select a measurable, bounded, non-identically zero function f \notin L^2, and pick \varphi_0 \in L^2 \setminus \. Define :A \varphi = \langle f,\varphi\rangle \varphi_0. It follows that D(A) = \. The subspace D(A) contains all the L^2 functions with compact support. Since \mathbf_ \cdot \varphi\ \stackrel\ \varphi, A is densely defined. For every \varphi \in D(A) and \psi \in D(A^*), :\langle \varphi, A^*\psi \rangle = \langle A\varphi, \psi \rangle = \langle \langle f,\varphi \rangle\varphi_0, \psi \rangle = \langle f,\varphi \rangle\cdot \langle \varphi_0, \psi \rangle = \langle \varphi, \langle \varphi_0, \psi \rangle f\rangle. Thus, A^* \psi = \langle \varphi_0, \psi \rangle f. The definition of adjoint operator requires that \mathopA^* \subseteq H=L^2. Since f \notin L^2, this is only possible if \langle \varphi_0, \psi \rangle= 0. For this reason, D(A^*) = \^\perp. Hence, A^* is not densely defined and is identically zero on D(A^*). As a result, A is not closable and has no second adjoint A^.


Hermitian operators

A
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 ...
is called Hermitian or Self-adjoint operator">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 :A = A^* which is equivalent to :\langle Ax , y \rangle = \langle x , A y \rangle \mbox x, y \in H.; In some sense, these operators play the role of the real numbers (being equal to their own "complex conjugate") and form a real
vector space In mathematics and physics, a vector space (also called a linear space) is a set (mathematics), set whose elements, often called vector (mathematics and physics), ''vectors'', can be added together and multiplied ("scaled") by numbers called sc ...
. They serve as the model of real-valued
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 ...
. See the article on
self-adjoint operator In mathematics, a self-adjoint operator on a complex vector space ''V'' with inner product \langle\cdot,\cdot\rangle is a linear map ''A'' (from ''V'' to itself) that is its own adjoint. That is, \langle Ax,y \rangle = \langle x,Ay \rangle for al ...
s for a full treatment.


Adjoints of conjugate-linear operators

For a conjugate-linear operator the definition of adjoint needs to be adjusted in order to compensate for the complex conjugation. An adjoint operator of the conjugate-linear operator on a complex Hilbert space is an conjugate-linear operator with the property: : \langle Ax , y \rangle = \overline \quad \text x, y \in H.


Other adjoints

The equation : \langle Ax , y \rangle = \left\langle x, A^* y \right\rangle is formally similar to the defining properties of pairs of adjoint functors in
category theory Category theory is a general theory of mathematical structures and their relations. It was introduced by Samuel Eilenberg and Saunders Mac Lane in the middle of the 20th century in their foundational work on algebraic topology. Category theory ...
, and this is where adjoint functors got their name.


See also

* Mathematical concepts **
Conjugate transpose In mathematics, the conjugate transpose, also known as the Hermitian transpose, of an m \times n complex matrix \mathbf is an n \times m matrix obtained by transposing \mathbf and applying complex conjugation to each entry (the complex conjugate ...
**
Hermitian operator In mathematics, a self-adjoint operator on a complex vector space ''V'' with inner product \langle\cdot,\cdot\rangle is a linear map ''A'' (from ''V'' to itself) that is its own adjoint. That is, \langle Ax,y \rangle = \langle x,Ay \rangle for al ...
** ** Transpose of linear maps * Physical applications **
Operator (physics) An operator is a function over a space of physical states onto another space of states. The simplest example of the utility of operators is the study of symmetry (which makes the concept of a group useful in this context). Because of this, they a ...
** †-algebra


References

* . * . * {{DEFAULTSORT:Hermitian Adjoint Operator theory