Accretive Operator
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In
mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, a dissipative operator is 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 pre ...
''A'' defined on a
linear subspace In mathematics, and more specifically in linear algebra, a linear subspace, also known as a vector subspaceThe term ''linear subspace'' is sometimes used for referring to flats and affine subspaces. In the case of vector spaces over the reals, li ...
''D''(''A'') of
Banach space In mathematics, more specifically in functional analysis, a Banach space (pronounced ) 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 vector ...
''X'', taking values in ''X'' such that for all ''λ'' > 0 and all ''x'' ∈ ''D''(''A'') :\, (\lambda I-A)x\, \geq\lambda\, x\, . A couple of equivalent definitions are given below. A dissipative operator is called maximally dissipative if it is dissipative and for all ''λ'' > 0 the operator ''λI'' − ''A'' is surjective, meaning that the range when applied to the domain ''D'' is the whole of the space ''X''. An operator that obeys a similar condition but with a plus sign instead of a minus sign (that is, the negation of a dissipative operator) is called an accretive operator. The main importance of dissipative operators is their appearance in the
Lumer–Phillips theorem In mathematics, the Lumer–Phillips theorem, named after Günter Lumer and Ralph Phillips, is a result in the theory of strongly continuous semigroups that gives a necessary and sufficient condition for a linear operator in a Banach space to gene ...
which characterizes maximally dissipative operators as the generators of contraction semigroups.


Properties

A dissipative operator has the following properties: * From the inequality given above, we see that for any ''x'' in the domain of ''A'', if ‖''x''‖ ≠ 0 then \, (\lambda I-A)x\, \ne 0, so the
kernel Kernel may refer to: Computing * Kernel (operating system), the central component of most operating systems * Kernel (image processing), a matrix used for image convolution * Compute kernel, in GPGPU programming * Kernel method, in machine learnin ...
of ''λI'' − ''A'' is just the
zero vector In mathematics, a zero element is one of several generalizations of the number zero to other algebraic structures. These alternate meanings may or may not reduce to the same thing, depending on the context. Additive identities An additive identi ...
and ''λI'' − ''A'' is therefore
injective In mathematics, an injective function (also known as injection, or one-to-one function) is a function that maps distinct elements of its domain to distinct elements; that is, implies . (Equivalently, implies in the equivalent contrapositiv ...
and has an inverse for all ''λ'' > 0. (If we have the strict inequality \, (\lambda I-A)x\, >\lambda\, x\, for all non-null ''x'' in the domain, then, by the
triangle inequality In mathematics, the triangle inequality states that for any triangle, the sum of the lengths of any two sides must be greater than or equal to the length of the remaining side. This statement permits the inclusion of degenerate triangles, but ...
, \, \lambda x\, +\, Ax\, \ge\, (\lambda I-A)x\, >\lambda\, x\, , which implies that A itself has an inverse.) We may then state that :::\, (\lambda I-A)^z\, \leq\frac\, z\, ::for all ''z'' in the range of ''λI'' − ''A''. This is the same inequality as that given at the beginning of this article, with z=(\lambda I-A)x. (We could equally well write these as \, (I-\kappa A)^z\, \leq\, z\, \text\, (I-\kappa A)x\, \geq\, x\, which must hold for any positive κ.) * ''λI'' − ''A'' is
surjective In mathematics, a surjective function (also known as surjection, or onto function) is a function that every element can be mapped from element so that . In other words, every element of the function's codomain is the image of one element of i ...
for some ''λ'' > 0 if and only if it is surjective for all ''λ'' > 0. (This is the aforementioned maximally dissipative case.) In that case one has (0, ∞) ⊂ ''ρ''(''A'') (the
resolvent set In linear algebra and operator theory, the resolvent set of a linear operator is a set of complex numbers for which the operator is in some sense "well-behaved". The resolvent set plays an important role in the resolvent formalism. Definitions Le ...
of ''A''). * ''A'' is a
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if and only if the range of ''λI'' - ''A'' is closed for some (equivalently: for all) ''λ'' > 0.


Equivalent characterizations

Define the duality set of ''x'' ∈ ''X'', a subset of the
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''X of ''X'', by :J(x):=\left\. By the
Hahn–Banach theorem The Hahn–Banach theorem is a central tool in functional analysis. It allows the extension of bounded linear functionals defined on a subspace of some vector space to the whole space, and it also shows that there are "enough" continuous linear f ...
this set is nonempty. In the
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case (using the canonical duality between a Hilbert space and its dual) it consists of the single element ''x''. More generally, if ''X'' is a Banach space with a strictly convex dual, then ''J''(''x'') consists of a single element. Using this notation, ''A'' is dissipative if and only ifEngel and Nagel Proposition II.3.23 for all ''x'' ∈ ''D''(''A'') there exists a ''x''' ∈ ''J''(''x'') such that :\langle Ax,x'\rangle\leq0. In the case of Hilbert spaces, this becomes \langle Ax,x\rangle\leq0 for all ''x'' in ''D''(''A''). Since this is non-positive, we have :\, x-Ax\, ^2=\, x\, ^2+\, Ax\, ^2-2\langle Ax,x\rangle\geq\, x\, ^2+\, Ax\, ^2+2\langle Ax,x\rangle=\, x+Ax\, ^2 :\therefore\, x-Ax\, \geq\, x+Ax\, Since ''I−A'' has an inverse, this implies that (I+A)(I-A)^ is a
contraction Contraction may refer to: Linguistics * Contraction (grammar), a shortened word * Poetic contraction, omission of letters for poetic reasons * Elision, omission of sounds ** Syncope (phonology), omission of sounds in a word * Synalepha, merged ...
, and more generally, (\lambda I+A)(\lambda I-A)^ is a contraction for any positive λ. The utility of this formulation is that if this operator is a contraction for some positive λ then ''A'' is dissipative. It is not necessary to show that it is a contraction for all positive λ (though this is true), in contrast to (λI−A)−1 which must be proved to be a contraction for all positive values of λ.


Examples

* For a simple finite-dimensional example, consider ''n''-dimensional
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R''n'' with its usual
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. If ''A'' denotes the negative of the
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, defined on all of R''n'', then ::x \cdot A x = x \cdot (-x) = - \, x \, ^ \leq 0, : so ''A'' is a dissipative operator. * So long as the domain of an operator ''A'' (a matrix) is the whole Euclidean space, then it is dissipative if and only if ''A''+''A''* (the sum of A and its
adjoint In mathematics, the term ''adjoint'' applies in several situations. Several of these share a similar formalism: if ''A'' is adjoint to ''B'', then there is typically some formula of the type :(''Ax'', ''y'') = (''x'', ''By''). Specifically, adjoin ...
) does not have any positive eigenvalue, and (consequently) all such operators are maximally dissipative. This criterion follows from the fact that the real part of x^Ax, which must be nonpositive for any ''x'', is x^\frac2x. The eigenvalues of this
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must therefore be nonpositive. (The fact that the real part of x^Ax, must be nonpositive implies that the real parts of the eigenvalues of ''A'' must be nonpositive, but this is not sufficient. For example, if A=\begin-1 & 3 \\0 & -1\end then its eigenvalues are negative, but the eigenvalues of ''A''+''A''* are −5 and 1, so ''A'' is not dissipative.) An equivalent condition is that for some (and hence any) positive \lambda, \lambda-A has an inverse and the operator (\lambda+A)(\lambda-A)^ is a contraction (that is, it either diminishes or leaves unchanged the norm of its operand). If the time derivative of a point ''x'' in the space is given by ''Ax'', then the time evolution is governed by a contraction semigroup that constantly decreases the norm (or at least doesn't allow it to increase). (Note however that if the domain of ''A'' is a proper subspace, then ''A'' cannot be maximally dissipative because the range will not have a high enough dimensionality.) * Consider ''H'' = ''L''2(
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R) with its usual inner product, and let ''Au'' = ''u''′ (in this case a
weak derivative In mathematics, a weak derivative is a generalization of the concept of the derivative of a function (''strong derivative'') for functions not assumed differentiable, but only integrable, i.e., to lie in the L''p'' space L^1( ,b. The method of ...
) with domain ''D''(''A'') equal to those functions ''u'' in the
Sobolev space In mathematics, a Sobolev space is a vector space of functions equipped with a norm that is a combination of ''Lp''-norms of the function together with its derivatives up to a given order. The derivatives are understood in a suitable weak sense t ...
H^1( ,\;1\;\mathbf) with ''u''(1) = 0. ''D''(''A'') is dense in ''L''2(
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R). Moreover, for every ''u'' in ''D''(''A''), using
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, ::\langle u, A u \rangle = \int_^ u(x) u'(x) \, \mathrm x = - \frac1 u(0)^ \leq 0. : Hence, ''A'' is a dissipative operator. Furthermore, since there is a solution (
almost everywhere In measure theory (a branch of mathematical analysis), a property holds almost everywhere if, in a technical sense, the set for which the property holds takes up nearly all possibilities. The notion of "almost everywhere" is a companion notion to ...
) in ''D'' to u-\lambda u'=f for any ''f'' in ''H'', the operator ''A'' is maximally dissipative. Note that in a case of infinite dimensionality like this, the range can be the whole Banach space even though the domain is only a proper subspace thereof. * Consider ''H'' = ''H''02(Ω; R) (see
Sobolev space In mathematics, a Sobolev space is a vector space of functions equipped with a norm that is a combination of ''Lp''-norms of the function together with its derivatives up to a given order. The derivatives are understood in a suitable weak sense t ...
) for an
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and
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domain Ω ⊆ R''n'' and let ''A'' = Δ, the
Laplace operator In mathematics, the Laplace operator or Laplacian is a differential operator given by the divergence of the gradient of a scalar function on Euclidean space. It is usually denoted by the symbols \nabla\cdot\nabla, \nabla^2 (where \nabla is the ...
, defined on the dense subspace of
compactly supported In mathematics, the support of a real-valued function f is the subset of the function domain containing the elements which are not mapped to zero. If the domain of f is a topological space, then the support of f is instead defined as the smalles ...
smooth functions on Ω. Then, using integration by parts, ::\langle u, \Delta u \rangle = \int_\Omega u(x) \Delta u(x) \, \mathrm x = - \int_\Omega \big, \nabla u(x) \big, ^ \, \mathrm x = - \, \nabla u \, ^2_ \leq 0, : so the Laplacian is a dissipative operator.


Notes


References

* * {{cite book , author1=Renardy, Michael , author2=Rogers, Robert C. , title = An introduction to partial differential equations , series = Texts in Applied Mathematics 13 , edition = Second , publisher = Springer-Verlag , location = New York , year = 2004 , pages = 356 , isbn = 0-387-00444-0 (Definition 12.25) Operator theory Linear operators