Bounded set (topological vector space)

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In functional analysis and related areas of mathematics, a set in a topological vector space is called bounded or von Neumann bounded, if every neighborhood of the zero vector can be inflated to include the set. Conversely a set which is not bounded is called unbounded.

Bounded sets are a natural way to define a locally convex polar topologies on the vector spaces in a dual pair, as the polar of a bounded set is an absolutely convex and absorbing set. The concept was first introduced by John von Neumann and Andrey Kolmogorov in 1935.

Contents 1 Definition 2 Examples and nonexamples 3 Properties 4 Generalization 5 See also 6 References

[edit] Definition

Given a topological vector space (X,τ) over a field F, S is called bounded if for every neighborhood N of the zero vector there exists a scalar α so that

with

.

In other words a set is called bounded if it is absorbed by every neighborhood of the zero vector.

In locally convex topological vector spaces the topology τ of the space can be specified by a family P of semi-norms. An equivalent characterization of bounded sets in this case is, a set S in (X,P) is bounded if and only if it is bounded for all semi normed spaces (X,p) with p a semi norm of P.

[edit] Examples and nonexamples

• Every finite set of points is bounded
• The set of points of a Cauchy sequence is bounded, the set of points of a Cauchy net need not to be bounded.
• Every relatively compact set in a topological vector space is bounded. If the space is equipped with the weak topology the converse is also true.
• A (non null) subspace of a hausdorff topological vector space is not bounded

[edit] Properties

• The closure of a bounded set is bounded.
• In a locally convex space, the convex envelope of a bounded set is bounded. (Without local convexity this is false, as the L^p spaces for 0 < p < 1 have no nontrivial open convex subsets.)
• The finite union or finite sum of bounded sets is bounded.
• Continuous linear mappings between topological vector spaces preserve boundedness.
• A locally convex space is seminormable if and only if there exists a bounded neighbourhood of zero.
• The polar of a bounded set is an absolutely convex and absorbing set.
• A set A is bounded if and only if every countable subset of A is bounded

[edit] Generalization

The definition of bounded sets can be generalized to topological modules. A subset A of a topological module M over a topological ring R is bounded if for any neighborhood N of 0_M there exists a neighborhood w of 0_R such that w A ⊂ N.

[edit] See also

• Totally bounded space
• Local boundedness
• bounded function

[edit] References

• Robertson, A.P.; W.J. Robertson (1964). Topological vector spaces. Cambridge Tracts in Mathematics. 53. Cambridge University Press. pp. 44–46. 
• H.H. Schaefer (1970). Topological Vector Spaces. GTM. 3. Springer-Verlag. pp. 25–26. ISBN 0-387-05380-8.