In mathematics, a subset C of a real or complex vector space is said to be absolutely convex or disked if it is convex and balanced (some people use the term "circled" instead of "balanced"), in which case it is called a disk. The disked hull or the absolute convex hull of a set is the intersection of all disks containing that set.

Definition

The light gray area is the absolutely convex hull of the cross.

A subset ${\displaystyle S}$ of a real or complex vector space ${\displaystyle X}$ is called a disk and is said to be disked, absolutely convex, and convex balanced if any of the following equivalent conditions is satisfied:

1. ${\displaystyle S}$ is a convex and balanced set.
2. for any scalars ${\displaystyle a}$ and ${\displaystyle b,}$ if ${\displaystyle |a|+|b|\leq 1}$ then ${\displaystyle aS+bS\subseteq S.}$
3. for all scalars ${\displaystyle a,b,}$ and ${\displaystyle c,}$ if ${\displaystyle |a|+|b|\leq |c|,}$ then ${\displaystyle aS+bS\subseteq cS.}$
4. for any scalars ${\displaystyle a_{1},\ldots ,a_{n}}$ and ${\displaystyle c,}$ if ${\displaystyle |a_{1}|+\cdots +|a_{n}|\leq |c|}$ then ${\displaystyle a_{1}S+\cdots +a_{n}S\subseteq cS.}$
5. for any scalars ${\displaystyle a_{1},\ldots ,a_{n},}$ if ${\displaystyle |a_{1}|+\cdots +|a_{n}|\leq 1}$ then ${\displaystyle a_{1}S+\cdots +a_{n}S\subseteq S.}$

The smallest convex (respectively, balanced) subset of ${\displaystyle X}$ containing a given set is called the convex hull (respectively, the balanced hull) of that set and is denoted by ${\displaystyle \operatorname {co} S}$ (respectively, ${\displaystyle \operatorname {bal} S}$).

Similarly, the disked hull, the absolute convex hull, and the convex balanced hull of a set ${\displaystyle S}$ is defined to be the smallest disk (with respect to subset inclusion) containing ${\displaystyle S.}$^[1] The disked hull of ${\displaystyle S}$ will be denoted by ${\displaystyle \operatorname {disk} S}$ or ${\displaystyle \operatorname {cobal} S}$ and it is equal to each of the following sets:

1. ${\displaystyle \operatorname {co} (\operatorname {bal} S),}$ which is the convex hull of the balanced hull of ${\displaystyle S}$; thus, ${\displaystyle \operatorname {cobal} S=\operatorname {co} (\operatorname {bal} S).}$
   • In general, ${\displaystyle \operatorname {cobal} S\neq \operatorname {bal} (\operatorname {co} S)}$ is possible, even in finite dimensional vector spaces.
2. the intersection of all disks containing ${\displaystyle S.}$
3. ${\displaystyle \left\{a_{1}s_{1}+\cdots a_{n}s_{n}~:~n\in \mathbb {N} ,\,s_{1},\ldots ,s_{n}\in S,\,{\text{ and }}a_{1},\ldots ,a_{n}{\text{ are scalars satisfying }}|a_{1}|+\cdots +|a_{n}|\leq 1\right\}.}$

Sufficient conditions

The intersection of arbitrarily many absolutely convex sets is again absolutely convex; however, unions of absolutely convex sets need not be absolutely convex anymore.

If ${\displaystyle D}$ is a disk in ${\displaystyle X,}$ then ${\displaystyle D}$ is absorbing in ${\displaystyle X}$ if and only if ${\displaystyle \operatorname {span} D=X.}$^[2]

Properties

If ${\displaystyle S}$ is an absorbing disk in a vector space ${\displaystyle X}$ then there exists an absorbing disk ${\displaystyle E}$ in ${\displaystyle X}$ such that ${\displaystyle E+E\subseteq S.}$^[3] If ${\displaystyle D}$ is a disk and ${\displaystyle r}$ and ${\displaystyle s}$ are scalars then ${\displaystyle sD=|s|D}$ and ${\displaystyle (rD)\cap (sD)=(\min _{}\{|r|,|s|\})D.}$

The absolutely convex hull of a bounded set in a locally convex topological vector space is again bounded.

If ${\displaystyle D}$ is a bounded disk in a TVS ${\displaystyle X}$ and if ${\displaystyle x_{\bullet }=\left(x_{i}\right)_{i=1}^{\infty }}$ is a sequence in ${\displaystyle D,}$ then the partial sums ${\displaystyle s_{\bullet }=\left(s_{n}\right)_{n=1}^{\infty }}$ are Cauchy, where for all ${\displaystyle n,}$ ${\displaystyle s_{n}:=\sum _{i=1}^{n}2^{-i}x_{i}.}$^[4] In particular, if in addition ${\displaystyle D}$ is a sequentially complete subset of ${\displaystyle X,}$ then this series ${\displaystyle s_{\bullet }}$ converges in ${\displaystyle X}$ to some point of ${\displaystyle D.}$

The convex balanced hull of ${\displaystyle S}$ contains both the convex hull of ${\displaystyle S}$ and the balanced hull of ${\displaystyle S.}$ Furthermore, it contains the balanced hull of the convex hull of ${\displaystyle S;}$ thus

$${\displaystyle \operatorname {bal} (\operatorname {co} S)~\subseteq ~\operatorname {cobal} S~=~\operatorname {co} (\operatorname {bal} S),}$$

where the example below shows that this inclusion might be strict. However, for any subsets ${\displaystyle S,T\subseteq X,}$ if ${\displaystyle S\subseteq T}$ then ${\displaystyle \operatorname {cobal} S\subseteq \operatorname {cobal} T}$ which implies ${\displaystyle \operatorname {cobal} (\operatorname {co} S)=\operatorname {cobal} S=\operatorname {cobal} (\operatorname {bal} S).}$

Generalizations

Given a fixed real number ${\displaystyle 0<p\leq 1,}$ a ${\displaystyle p}$-convex set is any subset ${\displaystyle C}$ of a vector space ${\displaystyle X}$ with the property that ${\displaystyle rc+sd\in C}$ whenever ${\displaystyle c,d\in C}$ and ${\displaystyle r,s\geq 0}$ are non-negative scalars satisfying ${\displaystyle r^{p}+s^{p}=1.}$ It is called an absolutely ${\displaystyle p}$-convex set or a ${\displaystyle p}$-disk if ${\displaystyle rc+sd\in C}$ whenever ${\displaystyle c,d\in C}$ and ${\displaystyle r,s}$ are scalars satisfying ${\displaystyle |r|^{p}+|s|^{p}\leq 1.}$^[5]

A ${\displaystyle p}$-seminorm^[6] is any non-negative function ${\displaystyle q:X\to \mathbb {R} }$ that satisfies the following conditions:

1. Subadditivity/Triangle inequality: ${\displaystyle q(x+y)\leq q(x)+q(y)}$ for all ${\displaystyle x,y\in X.}$
2. Absolute homogeneity of degree ${\displaystyle p}$: ${\displaystyle q(sx)=|s|^{p}q(x)}$ for all ${\displaystyle x\in X}$ and all scalars ${\displaystyle s.}$

This generalizes the definition of seminorms since a map is a seminorm if and only if it is a ${\displaystyle 1}$-seminorm (using ${\displaystyle p:=1}$). There exist ${\displaystyle p}$-seminorms that are not seminorms. For example, whenever ${\displaystyle 0<p<1}$ then the map ${\displaystyle q(f)=\int _{\mathbb {R} }|f(t)|^{p}dt}$ used to define the Lp space ${\displaystyle L_{p}(\mathbb {R} )}$ is a ${\displaystyle p}$-seminorm but not a seminorm.^[6]

Given ${\displaystyle 0<p\leq 1,}$ a topological vector space is ${\displaystyle p}$-seminormable (meaning that its topology is induced by some ${\displaystyle p}$-seminorm) if and only if it has a bounded ${\displaystyle p}$-convex neighborhood of the origin.^[5]

See also

The Wikibook Algebra has a page on the topic of: Vector spaces

• Absorbing set – Set that can be "inflated" to reach any point
• Auxiliary normed space
• Balanced set – Construct in functional analysis
• 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)
• Vector (geometric) – Geometric object that has length and directionPages displaying short descriptions of redirect targets, for vectors in physics
• Vector field – Assignment of a vector to each point in a subset of Euclidean space

References

Bibliography

• Robertson, A.P.; W.J. Robertson (1964). Topological vector spaces. Cambridge Tracts in Mathematics. Vol. 53. Cambridge University Press. pp. 4–6.
• Narici, Lawrence; Beckenstein, Edward (2011). Topological Vector Spaces. Pure and applied mathematics (Second ed.). Boca Raton, FL: CRC Press. ISBN 978-1584888666. OCLC 144216834.
• 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.
• Trèves, François (2006) [1967]. Topological Vector Spaces, Distributions and Kernels. Mineola, N.Y.: Dover Publications. ISBN 978-0-486-45352-1. OCLC 853623322.