Dissipative operator

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In mathematics, a dissipative operator is a linear operator A defined on a linear subspace D(A) of Banach space X, taking values in X such that for all λ > 0 and all x ∈ D(A)

‖(λI−A)x‖≥λ‖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.[1]

The main importance of dissipative operators is their appearance in the Lumer–Phillips theorem which characterizes maximally dissipative operators as the generators of contraction semigroups.

Properties

A dissipative operator has the following properties:[2]

  • From the inequality given above, we see that for any x in the domain of A, if ‖x‖ ≠ 0 then ‖(λI−A)x‖≠0, so the kernel of λI − A is just the zero vector and λI − A is therefore injective and has an inverse for all λ > 0. (If we have the strict inequality ‖(λI−A)x‖>λ‖x‖ for all non-null x in the domain, then, by the triangle inequality, ‖λx‖+‖Ax‖≥‖(λI−A)x‖>λ‖x‖, which implies that A itself has an inverse.) We may then state that
‖(λI−A)−1z‖≤1λ‖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=(λI−A)x. (We could equally well write these as ‖(I−κA)−1z‖≤‖z‖ or ‖(I−κA)x‖≥‖x‖ which must hold for any positive κ.)
  • λI − A is surjective 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 of A).
  • A is a closed operator 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 dual space X' of X, by

J(x):={x′∈X′:‖x′‖X′2=‖x‖X2=⟨x′,x⟩}.

By the Hahn–Banach theorem this set is nonempty.[3] In the Hilbert space case (using the canonical duality between a Hilbert space and its dual) it consists of the single element x.[4] More generally, if X is a Banach space with a strictly convex dual, then J(x) consists of a single element.[5] Using this notation, A is dissipative if and only if[6] for all x ∈ D(A) there exists a x' ∈ J(x) such that

Re⟨Ax,x′⟩≤0.

In the case of Hilbert spaces, this becomes Re⟨Ax,x⟩≤0 for all x in D(A). Since this is non-positive, we have

‖x−Ax‖2=‖x‖2+‖Ax‖2−2Re⟨Ax,x⟩≥‖x‖2+‖Ax‖2+2Re⟨Ax,x⟩=‖x+Ax‖2
∴‖x−Ax‖≥‖x+Ax‖

Since I−A has an inverse, this implies that (I+A)(I−A)−1 is a contraction, and more generally, (λI+A)(λI−A)−1 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 Euclidean space Rn with its usual dot product. If A denotes the negative of the identity operator, defined on all of Rn, then
x⋅Ax=x⋅(−x)=−‖x‖2≤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) 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*A+A*2x. The eigenvalues of this quadratic form 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=(−130−1) 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 λ,λ−A has an inverse and the operator (λ+A)(λ−A)−1 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 = L2([0, 1]; R) with its usual inner product, and let Au = u′ (in this case a weak derivative) with domain D(A) equal to those functions u in the Sobolev space H1([0,1];𝐑) with u(1) = 0. D(A) is dense in L2([0, 1]; R). Moreover, for every u in D(A), using integration by parts,
⟨u,Au⟩=∫01u(x)u′(x)dx=−12u(0)2≤0.
Hence, A is a dissipative operator. Furthermore, since there is a solution (almost everywhere) in D to u−λu′=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 = H02(Ω; R) (see Sobolev space) for an open and connected domain Ω ⊆ Rn and let A = Δ, the Laplace operator, defined on the dense subspace of compactly supported smooth functions on Ω. Then, using integration by parts,
⟨u,Δu⟩=∫Ωu(x)Δu(x)dx=−∫Ω|∇u(x)|2dx=−‖∇u‖L2(Ω;𝐑)2≤0,
so the Laplacian is a dissipative operator.

Notes

  1. ↑ "Dissipative operator". Encyclopedia of Mathematics. http://www.encyclopediaofmath.org/index.php/Dissipative_operator. 
  2. ↑ Engel and Nagel Proposition II.3.14
  3. ↑ The theorem implies that for a given x there exists a continuous linear functional φ with the property that φ(x)=‖x‖, with the norm of φ equal to 1. We identify ‖x‖φ with x'.
  4. ↑ Engel and Nagel Exercise II.3.25i
  5. ↑ Engel and Nagel Example II.3.26
  6. ↑ Engel and Nagel Proposition II.3.23

References

  • Engel, Klaus-Jochen; Nagel, Rainer (2000). One-parameter semigroups for linear evolution equations. Springer. 
  • Renardy, Michael; Rogers, Robert C. (2004). An introduction to partial differential equations. Texts in Applied Mathematics 13 (Second ed.). New York: Springer-Verlag. pp. 356. ISBN 0-387-00444-0.  (Definition 12.25)