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Balanced set

Construct in functional analysis

In linear algebra and related areas of mathematics a balanced set, circled set or disk in a vector space (over a field \mathbb {K} with an absolute value function |\cdot |) is a set S such that aS\subseteq S for all scalars a satisfying |a|\leq 1.

The balanced hull or balanced envelope of a set S is the smallest balanced set containing S. The balanced core of a set S is the largest balanced set contained in S.

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.

01Definition

Let X be a vector space over the field \mathbb {K} of real or complex numbers.

Notation

If S is a set, a is a scalar, and B\subseteq \mathbb {K} then let aS=\{as:s\in S\} and BS=\{bs:b\in B,s\in S\} and for any 0\leq r\leq \infty , let B_{r}=\{a\in \mathbb {K} :|a|<r\}\qquad {\text{ and }}\qquad B_{\leq r}=\{a\in \mathbb {K} :|a|\leq r\}. denote, respectively, the open ball and the closed ball of radius r in the scalar field \mathbb {K} centered at 0 where B_{0}=\varnothing ,B_{\leq 0}=\{0\}, and B_{\infty }=B_{\leq \infty }=\mathbb {K} . Every balanced subset of the field \mathbb {K} is of the form B_{\leq r} or B_{r} for some 0\leq r\leq \infty .

Balanced set

A subset S of X is called a balanced set or balanced if it satisfies any of the following equivalent conditions:

  1. Definition: as\in S for all s\in S and all scalars a satisfying |a|\leq 1.
  2. aS\subseteq S for all scalars a satisfying |a|\leq 1.
  3. B_{\leq 1}S\subseteq S (where B_{\leq 1}:=\{a\in \mathbb {K} :|a|\leq 1\}).
  4. S=B_{\leq 1}S.
  5. For every s\in S, S\cap \mathbb {K} s=B_{\leq 1}(S\cap \mathbb {K} s).
    • \mathbb {K} s=\operatorname {span} \{s\} is a 0 (if s=0) or 1 (if s\neq 0) dimensional vector subspace of X.
    • If R:=S\cap \mathbb {K} s then the above equality becomes R=B_{\leq 1}R, which is exactly the previous condition for a set to be balanced. Thus, S is balanced if and only if for every s\in S, S\cap \mathbb {K} s is a balanced set (according to any of the previous defining conditions).
  6. For every 1-dimensional vector subspace Y of \operatorname {span} S, S\cap Y is a balanced set (according to any defining condition other than this one).
  7. For every s\in S, there exists some 0\leq r\leq \infty such that S\cap \mathbb {K} s=B_{r}s or S\cap \mathbb {K} s=B_{\leq r}s.
  8. S is a balanced subset of \operatorname {span} S (according to any defining condition of "balanced" other than this one).
    • Thus S is a balanced subset of X if and only if it is balanced subset of every (equivalently, of some) vector space over the field \mathbb {K} that contains S. So assuming that the field \mathbb {K} is clear from context, this justifies writing "S is balanced" without mentioning any vector space.

If S is a convex set then this list may be extended to include:

  1. aS\subseteq S for all scalars a satisfying |a|=1.

If \mathbb {K} =\mathbb {R} then this list may be extended to include:

  1. S is symmetric (meaning -S=S) and [0,1)S\subseteq S.

Balanced hull

\operatorname {bal} S~=~\bigcup _{|a|\leq 1}aS=B_{\leq 1}S

The balanced hull of a subset S of X, denoted by \operatorname {bal} S, is defined in any of the following equivalent ways:

  1. Definition: \operatorname {bal} S is the smallest (with respect to \,\subseteq \,) balanced subset of X containing S.
  2. \operatorname {bal} S is the intersection of all balanced sets containing S.
  3. \operatorname {bal} S=\bigcup _{|a|\leq 1}(aS).
  4. \operatorname {bal} S=B_{\leq 1}S.

Balanced core

\operatorname {balcore} S~=~{\begin{cases}\displaystyle \bigcap _{|a|\geq 1}aS&{\text{ if }}0\in S\\\varnothing &{\text{ if }}0\not \in S\\\end{cases}}

The balanced core of a subset S of X, denoted by \operatorname {balcore} S, is defined in any of the following equivalent ways:

  1. Definition: \operatorname {balcore} S is the largest (with respect to \,\subseteq \,) balanced subset of S.
  2. \operatorname {balcore} S is the union of all balanced subsets of S.
  3. \operatorname {balcore} S=\varnothing if 0\not \in S while \operatorname {balcore} S=\bigcap _{|a|\geq 1}(aS) if 0\in S.

02Examples

The empty set is a balanced set. As is any vector subspace of any (real or complex) vector space. In particular, \{0\} 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 p is a seminorm (or norm) on a vector space X then for any constant c>0, the set \{x\in X:p(x)\leq c\} is balanced.

If S\subseteq X is any subset and B_{1}:=\{a\in \mathbb {K} :|a|<1\} then B_{1}S is a balanced set. In particular, if U\subseteq X is any balanced neighborhood of the origin in a topological vector space X then \operatorname {Int} _{X}U~\subseteq ~B_{1}U~=~\bigcup _{0<|a|<1}aU~\subseteq ~U.

Balanced sets in \mathbb {R} and \mathbb {C}

Let \mathbb {K} be the field real numbers \mathbb {R} or complex numbers \mathbb {C} , let |\cdot | denote the absolute value on \mathbb {K} , and let X:=\mathbb {K} denotes the vector space over \mathbb {K} . So for example, if \mathbb {K} :=\mathbb {C} is the field of complex numbers then X=\mathbb {K} =\mathbb {C} is a 1-dimensional complex vector space whereas if \mathbb {K} :=\mathbb {R} then X=\mathbb {K} =\mathbb {R} is a 1-dimensional real vector space.

The balanced subsets of X=\mathbb {K} are exactly the following:

  1. \varnothing
  2. X
  3. \{0\}
  4. \{x\in X:|x|<r\} for some real r>0
  5. \{x\in X:|x|\leq r\} for some real r>0.

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 \mathbb {C} 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, \mathbb {C} and \mathbb {R} ^{2} are entirely different as far as scalar multiplication is concerned.

Balanced sets in \mathbb {R} ^{2}

Throughout, let X=\mathbb {R} ^{2} (so X is a vector space over \mathbb {R}) and let B_{\leq 1} is the closed unit ball in X centered at the origin.

If x_{0}\in X=\mathbb {R} ^{2} is non-zero, and L:=\mathbb {R} x_{0}, then the set R:=B_{\leq 1}\cup L is a closed, symmetric, and balanced neighborhood of the origin in X. More generally, if C is any closed subset of X such that (0,1)C\subseteq C, then S:=B_{\leq 1}\cup C\cup (-C) is a closed, symmetric, and balanced neighborhood of the origin in X. This example can be generalized to \mathbb {R} ^{n} for any integer n\geq 1.

Let B\subseteq \mathbb {R} ^{2} be the union of the line segment between the points (-1,0) and (1,0) and the line segment between (0,-1) and (0,1). Then B is balanced but not convex. Nor is B is absorbing (despite the fact that \operatorname {span} B=\mathbb {R} ^{2} is the entire vector space).

For every 0\leq t\leq \pi , let r_{t} be any positive real number and let B^{t} be the (open or closed) line segment in X:=\mathbb {R} ^{2} between the points (\cos t,\sin t) and -(\cos t,\sin t). Then the set B=\bigcup _{0\leq t<\pi }r_{t}B^{t} 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 xy=1 in X=\mathbb {R} ^{2}.

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 S:=[-1,1]\times \{1\}, which is a horizontal closed line segment lying above the x-axis in X:=\mathbb {R} ^{2}. The balanced hull \operatorname {bal} S is a non-convex subset that is "hour glass shaped" and equal to the union of two closed and filled isosceles triangles T_{1} and T_{2}, where T_{2}=-T_{1} and T_{1} is the filled triangle whose vertices are the origin together with the endpoints of S (said differently, T_{1} is the convex hull of S\cup \{(0,0)\} while T_{2} is the convex hull of (-S)\cup \{(0,0)\}).

Sufficient conditions


A set T is balanced if and only if it is equal to its balanced hull \operatorname {bal} T or to its balanced core \operatorname {balcore} T, in which case all three of these sets are equal: T=\operatorname {bal} T=\operatorname {balcore} T.

The Cartesian product of a family of balanced sets is balanced in the product space of the corresponding vector spaces (over the same field \mathbb {K}).

  • The balanced hull of a compact (respectively, totally bounded, bounded) set has the same property.
  • The convex hull of a balanced set is convex and balanced (that is, it is absolutely convex). However, the balanced hull of a convex set may fail to be convex (a counter-example is given above).
  • Arbitrary unions of balanced sets are balanced, and the same is true of arbitrary intersections of balanced sets.
  • Scalar multiples and (finite) Minkowski sums of balanced sets are again balanced.
  • Images and preimages of balanced sets under linear maps are again balanced. Explicitly, if L:X\to Y is a linear map and B\subseteq X and C\subseteq Y are balanced sets, then L(B) and L^{-1}(C) are balanced sets.

Balanced neighborhoods

In any topological vector space, the closure of a balanced set is balanced. The union of the origin \{0\} and the topological interior of a balanced set is balanced. Therefore, the topological interior of a balanced neighborhood of the origin is balanced. However, \left\{(z,w)\in \mathbb {C} ^{2}:|z|\leq |w|\right\} is a balanced subset of X=\mathbb {C} ^{2} that contains the origin (0,0)\in X but whose (nonempty) topological interior does not contain the origin and is therefore not a balanced set. Similarly for real vector spaces, if T denotes the convex hull of (0,0) and (\pm 1,1) (a filled triangle whose vertices are these three points) then B:=T\cup (-T) is an (hour glass shaped) balanced subset of X:=\mathbb {R} ^{2} whose non-empty topological interior does not contain the origin and so is not a balanced set (and although the set \{(0,0)\}\cup \operatorname {Int} _{X}B 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 X contains a balanced (respectively, convex and balanced) open neighborhood of the origin. In fact, the following construction produces such balanced sets. Given W\subseteq X, the symmetric set \bigcap _{|u|=1}uW\subseteq W will be convex (respectively, closed, balanced, bounded, a neighborhood of the origin, an absorbing subset of X) whenever this is true of W. It will be a balanced set if W is a star shaped at the origin, which is true, for instance, when W is convex and contains 0. In particular, if W is a convex neighborhood of the origin then \bigcap _{|u|=1}uW will be a balanced convex neighborhood of the origin and so its topological interior will be a balanced convex open neighborhood of the origin.

Proof

Let 0\in W\subseteq X and define A=\bigcap _{|u|=1}uW (where u denotes elements of the field \mathbb {K} of scalars). Taking u:=1 shows that A\subseteq W. If W is convex then so is A (since an intersection of convex sets is convex) and thus so is A's interior. If |s|=1 then sA=\bigcap _{|u|=1}suW\subseteq \bigcap _{|u|=1}uW=A and thus sA=A. If W is star shaped at the origin then so is every uW (for |u|=1), which implies that for any 0\leq r\leq 1, rA=\bigcap _{|u|=1}ruW\subseteq \bigcap _{|u|=1}uW=A thus proving that A is balanced. If W is convex and contains the origin then it is star shaped at the origin and so A will be balanced.

Now suppose W is a neighborhood of the origin in X. Since scalar multiplication M:\mathbb {K} \times X\to X (defined by M(a,x)=ax) is continuous at the origin (0,0)\in \mathbb {K} \times X and M(0,0)=0\in W, there exists some basic open neighborhood B_{r}\times V (where r>0 and B_{r}:=\{c\in \mathbb {K} :|c|<r\}) of the origin in the product topology on \mathbb {K} \times X such that M\left(B_{r}\times V\right)\subseteq W; the set M\left(B_{r}\times V\right)=B_{r}V is balanced and it is also open because it may be written as B_{r}V=\bigcup _{|a|<r}aV=\bigcup _{0<|a|<r}aV\qquad {\text{ (since }}0\cdot V=\{0\}\subseteq aV{\text{ )}} where aV is an open neighborhood of the origin whenever a\neq 0. Finally, A=\bigcap _{|u|=1}uW\supseteq \bigcap _{|u|=1}uB_{r}V=\bigcap _{|u|=1}B_{r}V=B_{r}V shows that A is also a neighborhood of the origin. If A is balanced then because its interior \operatorname {Int} _{X}A contains the origin, \operatorname {Int} _{X}A will also be balanced. If W is convex then A is convex and balanced and thus the same is true of \operatorname {Int} _{X}A. \blacksquare

Suppose that W is a convex and absorbing subset of X. Then D:=\bigcap _{|u|=1}uW will be convex balanced absorbing subset of X, which guarantees that the Minkowski functional p_{D}:X\to \mathbb {R} of D will be a seminorm on X, thereby making \left(X,p_{D}\right) into a seminormed space that carries its canonical pseduometrizable topology. The set of scalar multiples rD as r ranges over \left\{{\tfrac {1}{2}},{\tfrac {1}{3}},{\tfrac {1}{4}},\ldots \right\} (or over any other set of non-zero scalars having 0 as a limit point) forms a neighborhood basis of absorbing disks at the origin for this locally convex topology. If X is a topological vector space and if this convex absorbing subset W is also a bounded subset of X, then the same will be true of the absorbing disk D:={\textstyle \bigcap \limits _{|u|=1}}uW; if in addition D does not contain any non-trivial vector subspace then p_{D} will be a norm and \left(X,p_{D}\right) will form what is known as an auxiliary normed space. If this normed space is a Banach space then D is called a Banach disk.

03Properties

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 B is a balanced subset of X then:

  • for any scalars c and d, if |c|\leq |d| then cB\subseteq dB and cB=|c|B. Thus if c and d are any scalars then (cB)\cap (dB)=\min _{}\{|c|,|d|\}B.
  • B is absorbing in X if and only if for all x\in X, there exists r>0 such that x\in rB.
  • for any 1-dimensional vector subspace Y of X, the set B\cap Y is convex and balanced. If B is not empty and if Y is a 1-dimensional vector subspace of \operatorname {span} B then B\cap Y is either \{0\} or else it is absorbing in Y.
  • for any x\in X, if B\cap \operatorname {span} x contains more than one point then it is a convex and balanced neighborhood of 0 in the 1-dimensional vector space \operatorname {span} x when this space is endowed with the Hausdorff Euclidean topology; and the set B\cap \mathbb {R} x is a convex balanced subset of the real vector space \mathbb {R} x that contains the origin.

Properties of balanced hulls and balanced cores

For any collection {\mathcal {S}} of subsets of X, \operatorname {bal} \left(\bigcup _{S\in {\mathcal {S}}}S\right)=\bigcup _{S\in {\mathcal {S}}}\operatorname {bal} S\quad {\text{ and }}\quad \operatorname {balcore} \left(\bigcap _{S\in {\mathcal {S}}}S\right)=\bigcap _{S\in {\mathcal {S}}}\operatorname {balcore} S.

In any topological vector space, the balanced hull of any open neighborhood of the origin is again open. If X is a Hausdorff topological vector space and if K is a compact subset of X then the balanced hull of K is compact.

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 S\subseteq X and any scalar c, \operatorname {bal} (c\,S)=c\operatorname {bal} S=|c|\operatorname {bal} S.

For any scalar c\neq 0, \operatorname {balcore} (c\,S)=c\operatorname {balcore} S=|c|\operatorname {balcore} S. This equality holds for c=0 if and only if S\subseteq \{0\}. Thus if 0\in S or S=\varnothing then \operatorname {balcore} (c\,S)=c\operatorname {balcore} S=|c|\operatorname {balcore} S for every scalar c.

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Sources and credits

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