Absorbing set
In functional analysis and related areas of mathematics an absorbing set in a vector space is a set which can be "inflated" or "scaled up" to eventually always include any given point of the vector space. Alternative terms are radial or absorbent set. Every neighborhood of the origin in every topological vector space is an absorbing subset.
Definition
Suppose that is a vector space over the field of real numbers or complex numbers
Notation
Products of scalars and vectors
For any vector and subset let denote the open ball (respectively, the closed ball) of radius in centered at and let
Similarly, if and is a scalar then let and
One set absorbing another
If and are subsets of then is said to absorb if it satisfies any of the following equivalent conditions:
- Definition: There exists a real such that for every scalar satisfying
- If the scalar field is then intuitively, " absorbs " means that if is perpetually "scaled up" or "inflated" (referring to as ) then eventually (for all positive sufficiently large), all will contain and similarly, must also eventually contain for all negative sufficiently large in magnitude.
- This definition depends on the underlying scalar field's canonical norm (that is, on the absolute value ), which thus ties this definition to the usual Euclidean topology on the scalar field. Consequently, the definition of an absorbing set (given below) is also tied to this topology.
- There exists a real such that for every scalar satisfying
- If it is known that then the restriction may be removed, giving the characterization: There exists a real such that for every scalar satisfying
- There exists a real such that
- The closed ball (with the origin removed) can be used in place of the open ball giving the next characterization.
- There exists a real such that
If is a balanced set then to this list can be appended:
- There exists a scalar such that
- There exists a scalar such that
A set absorbing a point
A set is said to absorb a point if it absorbs the singleton set A set absorbs the origin if and only if it contains the origin; that is, if and only if
Examples
Every set absorbs the empty set but the empty set does not absorbs any non-empty set. The singleton set containing the origin is the one and only singleton subset that absorbs itself.
Suppose that is equal to either or If is the unit circle (centered at the origin ) together with the origin, then is the one and only non-empty set that absorbs. Moreover, there does not exist any non-empty subset of that is absorbed by the unit circle In contrast, every neighborhood of the origin absorbs every bounded subset of (and so in particular, absorbs every singleton subset/point).
Absorbing set
A subset of a vector space over a field is called an absorbing (or absorbent) subset of and is said to be absorbing in if it satisfies any of the following equivalent conditions (here ordered so that each condition is an easy consequence of the previous one, starting with the definition):
- Definition: absorbs every point of that is, for every absorbs
- So in particular, can not be absorbing if
- absorbs every finite subset of
- For every there exists a real such that for any scalar satisfying
- For every there exists a real such that for any scalar satisfying
- For every there exists a real such that
- Here is the open ball of radius in the scalar field centered at the origin and
- The closed ball can be used in place of the open ball.
- For every there exists a real such that where
- Proof: This follows from the previous condition since so that if and only if
- Connection to topology: If is given its usual Hausdorff Euclidean topology then the set is a neighborhood of the origin in thus, there exists a real such that if and only if is a neighborhood of the origin in
- Every 1-dimensional vector subspace of is of the form for some non-zero and if this 1-dimensional space is endowed with the unique Hausdorff vector topology, then the map defined by is necessarily a TVS-isomorphism (where as usual, has the normed Euclidean topology).
- contains the origin and for every 1-dimensional vector subspace of is a neighborhood of the origin in when is given its unique Hausdorff vector topology.
- The Hausdorff vector topology on a 1-dimensional vector space is necessarily TVS-isomorphic to with its usual normed Euclidean topology.
- Intuition: This condition shows that it is only natural that any neighborhood of 0 in any topological vector space (TVS) be absorbing: if is a neighborhood of the origin in then it would be pathological if there existed any 1-dimensional vector subspace in which was not a neighborhood of the origin in at least some TVS topology on The only TVS topologies on are the Hausdorff Euclidean topology and the trivial topology, which is a subset of the Euclidean topology. Consequently, it is natural to expect for to be a neighborhood of in the Euclidean topology for all 1-dimensional vector subspaces which is exactly the condition that be absorbing in The fact that all neighborhoods of the origin in all TVSs are necessarily absorbing means that this pathological behavior does not occur. The reason why the Euclidean topology is distinguished is ultimately due to the defining requirement on TVS topologies that scalar multiplication be continuous when the scalar field is given the Euclidean topology.
- This condition is equivalent to: For every is a neighborhood of in when is given its unique Hausdorff TVS topology.
- contains the origin and for every 1-dimensional vector subspace of is absorbing in the
- Here "absorbing" means absorbing according to any defining condition other than this one.
- This shows that the property of being absorbing in depends only on how behaves with respect to 1 (or 0) dimensional vector subspaces of In contrast, if a finite-dimensional vector subspace of has dimension then being absorbing in is no longer sufficient to guarantee that is a neighborhood of the origin in when is endowed with its unique Hausdorff TVS topology (although it will still be a necessary condition). For this to happen, it suffices for to be a barrel in this Hausdorff TVS (because every finite-dimensional Euclidean space is a barrelled space).
If then to this list can be appended:
- The algebraic interior of contains the origin (that is, ).
If is balanced then to this list can be appended:
- For every there exists a scalar such that [1]
If is convex or balanced then to this list can be appended:
- For every there exists a positive real such that
- The proof that a balanced set satisfying this condition is necessarily absorbing in is almost immediate from the definition of a "balanced set".
- The proof that a convex set satisfying this condition is necessarily absorbing in is less trivial (but not difficult). A detailed proof is given in this footnote[proof 1] and a summary is given below.
- Summary of proof: By assumption, for any non-zero it is possible to pick positive real and such that and so that the convex set contains the open sub-interval which contains the origin ( is called an interval since we identify with and every non-empty convex subset of is an interval). Give its unique Hausdorff vector topology so it remains to show that is a neighborhood of the origin in If then we are done, so assume that The set is a union of two intervals, each of which contains an open sub-interval that contains the origin; moreover, the intersection of these two intervals is precisely the origin. So the convex hull of which is contained in the convex set clearly contains an open ball around the origin.
- For every there exists a positive real such that
- This condition is equivalent to: every belongs to the set This happens if and only if which gives the next characterization.
-
- It can be shown that for any subset of if and only if
- For every where
If (which is necessary for to be absorbing) then it suffices to check any of the above conditions for all non-zero rather than all
Examples and sufficient conditions
For one set to absorb another
Let be a linear map between vector spaces and let and be balanced sets. Then absorbs if and only if absorbs [2]
If a set absorbs another set then any superset of also absorbs A set absorbs the origin if and only if the origin is an element of
A set absorbs a finite union if and only it absorbs each set individuality (that is, if and only if absorbs for every ). In particular, a set is an absorbing subset of if and only if it absorbs every finite subset of
For a set to be absorbing
In a semi normed vector space the unit ball is absorbing. More generally, if is a topological vector space (TVS) then any neighborhood of the origin in is absorbing in This fact is one of the primary motivations for even defining the property "absorbing in "
If is a disk in then so that in particular, is an absorbing subset of [3] Thus if is a disk in then is absorbing in if and only if
Any superset of an absorbing set is absorbing. Thus the union of any family of (one or more) absorbing sets is absorbing. The image of an absorbing set under a surjective linear operator is again absorbing. The inverse image of an absorbing subset (of the codomain) under a linear operator is again absorbing (in the domain). The intersection of a finite family of (one or more) absorbing sets is absorbing. If absorbing then the same is true of the symmetric set
Auxiliary normed spaces
If is convex and absorbing in then the symmetric set will be convex and balanced (also known as an absolutely convex set or a disk) in addition to being absorbing in This guarantees that the Minkowski functional of will be a seminorm on thereby making into a seminormed space that carries its canonical pseduometrizable topology. The set of scalar multiples as ranges over (or over any other set of non-zero scalars having as a limit point) forms a neighborhood basis of absorbing disks at the origin for this locally convex topology. If is a topological vector space and if this convex absorbing subset is also a bounded subset of then the same will be true of the absorbing disk in which case will be a norm and will form what is known as an auxiliary normed space. If this normed space is a Banach space then is called a Banach disk.
Properties
Every absorbing set contains the origin. If is an absorbing disk in a vector space then there exists an absorbing disk in such that [4]
If is an absorbing subset of then and more generally, for any sequence of scalars such that Consequently, if a topological vector space is a non-meager subset of itself (or equivalently for TVSs, if it is a Baire space) and if is a closed absorbing subset of then necessarily contains a non-empty open subset of
See also
- Algebraic interior – Generalization of topological interior
- Absolutely convex set – Convex and balanced set
- Balanced set – Construct in functional analysis
- Bornivorous set – A set that can absorb any bounded subset
- Bounded set (topological vector space) – Generalization of boundedness
- Convex set – In geometry, set whose intersection with every line is a single line segment
- Locally convex topological vector space – A vector space with a topology defined by convex open sets
- Radial set
- Star domain – Property of point sets in Euclidean spaces
- Symmetric set – Property of group subsets (mathematics)
- Topological vector space – Vector space with a notion of nearness
Notes
- ^ Proof: Let be a vector space over the field with being or and endow the field with its usual normed Euclidean topology. Let be a convex set such that for every }, there exists a positive real such that Because if then the proof is complete so assume Clearly, every non-empty convex subset of the real line is an interval (possibly open, closed, or half-closed, and possibly bounded or unbounded, and possibly even degenerate (that is, a singleton set)). Recall that the intersection of convex sets is convex so that for every the sets and are convex, where now the convexity of (which contains the origin and is contained in the line ) implies that is an interval contained in the line Lemma: We will now prove that if then the interval contains an open sub-interval that contains the origin. By assumption, since we can pick some such that and (because ) we can also pick some such that where and (since ). Because is convex and contains the distinct points and it contains the convex hull of the points which (in particular) contains the open sub-interval where this open sub-interval contains the origin (to see why, take which satisfies ), which proves the lemma. Now fix let Because was arbitrary, to prove that is absorbing in it is necessary and sufficient to show that is a neighborhood of the origin in when is given its usual Hausdorff Euclidean topology, where recall that this topology makes the map defined by into a TVS-isomorphism. If then the fact that the interval contains an open sub-interval around the origin implies that is a neighborhood of the origin in so we're done. So assume that Write so that and that (so naively, is the "-axis" and is the "-axis" of so that the set (resp. ) is the strictly positive -axis (resp. -axis) while (resp. ) is the strictly negative -axis (resp. -axis)). The set is contained in the convex set so that the convex hull of is contained in By the lemma, each of and are line segments (i.e. intervals) with each segment containing the origin in an open sub-interval; moreover, they clearly intersect at the origin. Pick a real such that and Let denote the convex hull of which is contained in the convex hull of and thus also contained in the convex set So to finish the proof, it suffices to show that is a neighborhood of in Viewed as a subset of the complex plane is shaped like an open square with corners on the positive and negative and -axes. So it is readily verified that contains the open ball of radius centered at the origin of This shows that is a neighborhood of the origin in as desired.
Citations
- ^ Narici & Beckenstein 2011, pp. 107–110.
- ^ Narici & Beckenstein 2011, pp. 441–457.
- ^ Narici & Beckenstein 2011, pp. 67–113.
- ^ Narici & Beckenstein 2011, pp. 149–153.
References
- Berberian, Sterling K. (1974). Lectures in Functional Analysis and Operator Theory. Graduate Texts in Mathematics. Vol. 15. New York: Springer. ISBN 978-0-387-90081-0. OCLC 878109401.
- Bourbaki, Nicolas (1987) [1981]. Topological Vector Spaces: Chapters 1–5. Éléments de mathématique. Translated by Eggleston, H.G.; Madan, S. Berlin New York: Springer-Verlag. ISBN 3-540-13627-4. OCLC 17499190.
- Nicolas, Bourbaki (2003). Topological vector spaces Chapter 1-5 (English Translation). New York: Springer-Verlag. p. I.7. ISBN 3-540-42338-9.
- Conway, John (1990). A course in functional analysis. Graduate Texts in Mathematics. Vol. 96 (2nd ed.). New York: Springer-Verlag. ISBN 978-0-387-97245-9. OCLC 21195908.
- Diestel, Joe (2008). The Metric Theory of Tensor Products: Grothendieck's Résumé Revisited. Vol. 16. Providence, R.I.: American Mathematical Society. ISBN 9781470424831. OCLC 185095773.
- Dineen, Seán (1981). Complex Analysis in Locally Convex Spaces. North-Holland Mathematics Studies. Vol. 57. Amsterdam New York New York: North-Holland Pub. Co., Elsevier Science Pub. Co. ISBN 978-0-08-087168-4. OCLC 16549589.
- Dunford, Nelson; Schwartz, Jacob T. (1988). Linear Operators. Pure and applied mathematics. Vol. 1. New York: Wiley-Interscience. ISBN 978-0-471-60848-6. OCLC 18412261.
- Edwards, Robert E. (1995). Functional Analysis: Theory and Applications. New York: Dover Publications. ISBN 978-0-486-68143-6. OCLC 30593138.
- Grothendieck, Alexander (1973). Topological Vector Spaces. Translated by Chaljub, Orlando. New York: Gordon and Breach Science Publishers. ISBN 978-0-677-30020-7. OCLC 886098.
- Hogbe-Nlend, Henri (1977). Bornologies and Functional Analysis: Introductory Course on the Theory of Duality Topology-Bornology and its use in Functional Analysis. North-Holland Mathematics Studies. Vol. 26. Amsterdam New York New York: North Holland. ISBN 978-0-08-087137-0. MR 0500064. OCLC 316549583.
- Hogbe-Nlend, Henri; Moscatelli, V. B. (1981). Nuclear and Conuclear Spaces: Introductory Course on Nuclear and Conuclear Spaces in the Light of the Duality "topology-bornology". North-Holland Mathematics Studies. Vol. 52. Amsterdam New York New York: North Holland. ISBN 978-0-08-087163-9. OCLC 316564345.
- Husain, Taqdir; Khaleelulla, S. M. (1978). Barrelledness in Topological and Ordered Vector Spaces. Lecture Notes in Mathematics. Vol. 692. Berlin, New York, Heidelberg: Springer-Verlag. ISBN 978-3-540-09096-0. OCLC 4493665.
- Jarchow, Hans (1981). Locally convex spaces. Stuttgart: B.G. Teubner. ISBN 978-3-519-02224-4. OCLC 8210342.
- Keller, Hans (1974). Differential Calculus in Locally Convex Spaces. Lecture Notes in Mathematics. Vol. 417. Berlin New York: Springer-Verlag. ISBN 978-3-540-06962-1. OCLC 1103033.
- Khaleelulla, S. M. (1982). Counterexamples in Topological Vector Spaces. Lecture Notes in Mathematics. Vol. 936. Berlin, Heidelberg, New York: Springer-Verlag. ISBN 978-3-540-11565-6. OCLC 8588370.
- Jarchow, Hans (1981). Locally convex spaces. Stuttgart: B.G. Teubner. ISBN 978-3-519-02224-4. OCLC 8210342.
- Köthe, Gottfried (1983) [1969]. Topological Vector Spaces I. Grundlehren der mathematischen Wissenschaften. Vol. 159. Translated by Garling, D.J.H. New York: Springer Science & Business Media. ISBN 978-3-642-64988-2. MR 0248498. OCLC 840293704.
- Köthe, Gottfried (1979). Topological Vector Spaces II. Grundlehren der mathematischen Wissenschaften. Vol. 237. New York: Springer Science & Business Media. ISBN 978-0-387-90400-9. OCLC 180577972.
- Narici, Lawrence; Beckenstein, Edward (2011). Topological Vector Spaces. Pure and applied mathematics (Second ed.). Boca Raton, FL: CRC Press. ISBN 978-1584888666. OCLC 144216834.
- Pietsch, Albrecht (1979). Nuclear Locally Convex Spaces. Ergebnisse der Mathematik und ihrer Grenzgebiete. Vol. 66 (Second ed.). Berlin, New York: Springer-Verlag. ISBN 978-0-387-05644-9. OCLC 539541.
- Robertson, Alex P.; Robertson, Wendy J. (1980). Topological Vector Spaces. Cambridge Tracts in Mathematics. Vol. 53. Cambridge England: Cambridge University Press. ISBN 978-0-521-29882-7. OCLC 589250.
- Robertson, A.P.; W.J. Robertson (1964). Topological vector spaces. Cambridge Tracts in Mathematics. Vol. 53. Cambridge University Press. p. 4.
- Rudin, Walter (1991). Functional Analysis. International Series in Pure and Applied Mathematics. Vol. 8 (Second ed.). New York, NY: McGraw-Hill Science/Engineering/Math. ISBN 978-0-07-054236-5. OCLC 21163277.
- Thompson, Anthony C. (1996). Minkowski Geometry. Encyclopedia of Mathematics and Its Applications. Cambridge University Press. ISBN 0-521-40472-X.
- Schaefer, Helmut H. (1971). Topological vector spaces. GTM. Vol. 3. New York: Springer-Verlag. p. 11. ISBN 0-387-98726-6.
- Schaefer, Helmut H.; Wolff, Manfred P. (1999). Topological Vector Spaces. GTM. Vol. 8 (Second ed.). New York, NY: Springer New York Imprint Springer. ISBN 978-1-4612-7155-0. OCLC 840278135.
- Schechter, Eric (1996). Handbook of Analysis and Its Foundations. San Diego, CA: Academic Press. ISBN 978-0-12-622760-4. OCLC 175294365.
- Schaefer, H. H. (1999). Topological Vector Spaces. New York, NY: Springer New York Imprint Springer. ISBN 978-1-4612-7155-0. OCLC 840278135.
- Swartz, Charles (1992). An introduction to Functional Analysis. New York: M. Dekker. ISBN 978-0-8247-8643-4. OCLC 24909067.
- Trèves, François (2006) [1967]. Topological Vector Spaces, Distributions and Kernels. Mineola, N.Y.: Dover Publications. ISBN 978-0-486-45352-1. OCLC 853623322.
- Wilansky, Albert (2013). Modern Methods in Topological Vector Spaces. Mineola, New York: Dover Publications, Inc. ISBN 978-0-486-49353-4. OCLC 849801114.
- Wong, Yau-Chuen (1979). Schwartz Spaces, Nuclear Spaces, and Tensor Products. Lecture Notes in Mathematics. Vol. 726. Berlin New York: Springer-Verlag. ISBN 978-3-540-09513-2. OCLC 5126158.