Balanced set - Wikipedia
From Wikipedia, the free encyclopedia
In linear algebra and related areas of mathematics a balanced set, circled set or disk in a vector space (over a field with an absolute value function
) is a set
such that
for all scalars
satisfying
The balanced hull or balanced envelope of a set is the smallest balanced set containing
The balanced core of a set
is the largest balanced set contained in
Balanced sets are ubiquitous in functional analysis because every neighborhood of the origin in every topological vector space (TVS) contains a balanced neighborhood of the origin and every convex neighborhood of the origin contains a balanced convex neighborhood of the origin (even if the TVS is not locally convex). This neighborhood can also be chosen to be an open set or, alternatively, a closed set.
Let be a vector space over the field
of real or complex numbers.
Notation
If is a set,
is a scalar, and
then let
and
and for any
let
denote, respectively, the open ball and the closed ball of radius
in the scalar field
centered at
where
and
Every balanced subset of the field
is of the form
or
for some
Balanced set
A subset of
is called a balanced set or balanced if it satisfies any of the following equivalent conditions:
- Definition:
for all
and all scalars
satisfying
for all scalars
satisfying
(where
).
[1]
- For every
- For every 1-dimensional vector subspace
of
is a balanced set (according to any defining condition other than this one).
- For every
there exists some
such that
or
is a balanced subset of
(according to any defining condition of "balanced" other than this one).
If is a convex set then this list may be extended to include:
for all scalars
satisfying
[2]
If then this list may be extended to include:
is symmetric (meaning
) and
The balanced hull of a subset of
denoted by
is defined in any of the following equivalent ways:
- Definition:
is the smallest (with respect to
) balanced subset of
containing
is the intersection of all balanced sets containing
[1]
The balanced core of a subset of
denoted by
is defined in any of the following equivalent ways:
- Definition:
is the largest (with respect to
) balanced subset of
is the union of all balanced subsets of
if
while
if
The empty set is a balanced set. As is any vector subspace of any (real or complex) vector space. In particular, is always a balanced set.
Any non-empty set that does not contain the origin is not balanced and furthermore, the balanced core of such a set will equal the empty set.
Normed and topological vector spaces
The open and closed balls centered at the origin in a normed vector space are balanced sets. If is a seminorm (or norm) on a vector space
then for any constant
the set
is balanced.
If is any subset and
then
is a balanced set.
In particular, if
is any balanced neighborhood of the origin in a topological vector space
then
Balanced sets in and
Let be the field real numbers
or complex numbers
let
denote the absolute value on
and let
denotes the vector space over
So for example, if
is the field of complex numbers then
is a 1-dimensional complex vector space whereas if
then
is a 1-dimensional real vector space.
The balanced subsets of are exactly the following:[3]
for some real
for some real
Consequently, both the balanced core and the balanced hull of every set of scalars is equal to one of the sets listed above.
The balanced sets are itself, the empty set and the open and closed discs centered at zero. Contrariwise, in the two dimensional Euclidean space there are many more balanced sets: any line segment with midpoint at the origin will do. As a result,
and
are entirely different as far as scalar multiplication is concerned.
Balanced sets in
Throughout, let (so
is a vector space over
) and let
is the closed unit ball in
centered at the origin.
If is non-zero, and
then the set
is a closed, symmetric, and balanced neighborhood of the origin in
More generally, if
is any closed subset of
such that
then
is a closed, symmetric, and balanced neighborhood of the origin in
This example can be generalized to
for any integer
Let be the union of the line segment between the points
and
and the line segment between
and
Then
is balanced but not convex. Nor is
is absorbing (despite the fact that
is the entire vector space).
For every let
be any positive real number and let
be the (open or closed) line segment in
between the points
and
Then the set
is a balanced and absorbing set but it is not necessarily convex.
The balanced hull of a closed set need not be closed. Take for instance the graph of in
The next example shows that the balanced hull of a convex set may fail to be convex (however, the convex hull of a balanced set is always balanced). For an example, let the convex subset be which is a horizontal closed line segment lying above the
axis in
The balanced hull
is a non-convex subset that is "hour glass shaped" and equal to the union of two closed and filled isosceles triangles
and
where
and
is the filled triangle whose vertices are the origin together with the endpoints of
(said differently,
is the convex hull of
while
is the convex hull of
).
Sufficient conditions
[edit]
A set is balanced if and only if it is equal to its balanced hull
or to its balanced core
in which case all three of these sets are equal:
The Cartesian product of a family of balanced sets is balanced in the product space of the corresponding vector spaces (over the same field ).
Balanced neighborhoods
[edit]
In any topological vector space, the closure of a balanced set is balanced.[5] The union of the origin and the topological interior of a balanced set is balanced. Therefore, the topological interior of a balanced neighborhood of the origin is balanced.[5][proof 1] However,
is a balanced subset of
that contains the origin
but whose (nonempty) topological interior does not contain the origin and is therefore not a balanced set.[6] Similarly for real vector spaces, if
denotes the convex hull of
and
(a filled triangle whose vertices are these three points) then
is an (hour glass shaped) balanced subset of
whose non-empty topological interior does not contain the origin and so is not a balanced set (and although the set
formed by adding the origin is balanced, it is neither an open set nor a neighborhood of the origin).
Every neighborhood (respectively, convex neighborhood) of the origin in a topological vector space contains a balanced (respectively, convex and balanced) open neighborhood of the origin. In fact, the following construction produces such balanced sets. Given
the symmetric set
will be convex (respectively, closed, balanced, bounded, a neighborhood of the origin, an absorbing subset of
) whenever this is true of
It will be a balanced set if
is a star shaped at the origin,[note 2] which is true, for instance, when
is convex and contains
In particular, if
is a convex neighborhood of the origin then
will be a balanced convex neighborhood of the origin and so its topological interior will be a balanced convex open neighborhood of the origin.[5]
Suppose that is a convex and absorbing subset of
Then
will be convex balanced absorbing subset of
which 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
if in addition
does not contain any non-trivial vector subspace then
will be a norm and
will form what is known as an auxiliary normed space.[7] If this normed space is a Banach space then
is called a Banach disk.
Properties of balanced sets
A balanced set is not empty if and only if it contains the origin.
By definition, a set is absolutely convex if and only if it is convex and balanced.
Every balanced set is star-shaped (at 0) and a symmetric set.
If is a balanced subset of
then:
Properties of balanced hulls and balanced cores
For any collection of subsets of
In any topological vector space, the balanced hull of any open neighborhood of the origin is again open.
If is a Hausdorff topological vector space and if
is a compact subset of
then the balanced hull of
is compact.[8]
If a set is closed (respectively, convex, absorbing, a neighborhood of the origin) then the same is true of its balanced core.
For any subset and any scalar
For any scalar
This equality holds for
if and only if
Thus if
or
then
for every scalar
A function on a real or complex vector space is said to be a balanced function if it satisfies any of the following equivalent conditions:[9]
whenever
is a scalar satisfying
and
whenever
and
are scalars satisfying
and
is a balanced set for every non-negative real
If is a balanced function then
for every scalar
and vector
so in particular,
for every unit length scalar
(satisfying
) and every
[9]
Using
shows that every balanced function is a symmetric function.
A real-valued function is a seminorm if and only if it is a balanced sublinear function.
- Absolutely convex set – Convex and balanced set
- Absorbing set – Set that can be "inflated" to reach any point
- Bounded set (topological vector space) – Generalization of boundedness
- Convex set – In geometry, set whose intersection with every line is a single line segment
- 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
- ^ a b Swartz 1992, pp. 4–8.
- ^ a b Narici & Beckenstein 2011, pp. 107–110.
- ^ Jarchow 1981, p. 34.
- ^ Narici & Beckenstein 2011, pp. 156–175.
- ^ a b c Rudin 1991, pp. 10–14.
- ^ Rudin 1991, p. 38.
- ^ Narici & Beckenstein 2011, pp. 115–154.
- ^ Trèves 2006, p. 56.
- ^ a b Schechter 1996, p. 313.
Proofs
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 (October 24, 1996). Handbook of Analysis and Its Foundations. Academic Press. ISBN 978-0-08-053299-8.
- 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.