In mathematics, a subset
A
⊆
X
{\displaystyle A\subseteq X}
of a linear space
X
{\displaystyle X}
is radial at a given point
a
0
∈
A
{\displaystyle a_{0}\in A}
if for every
x
∈
X
{\displaystyle x\in X}
there exists a real
t
x
>
0
{\displaystyle t_{x}>0}
such that for every
t
∈
[
0
,
t
x
]
,
{\displaystyle t\in [0,t_{x}],}
a
0
+
t
x
∈
A
.
{\displaystyle a_{0}+tx\in A.}
[1]
Geometrically, this means
A
{\displaystyle A}
is radial at
a
0
{\displaystyle a_{0}}
if for every
x
∈
X
,
{\displaystyle x\in X,}
there is some (non-degenerate) line segment (depend on
x
{\displaystyle x}
) emanating from
a
0
{\displaystyle a_{0}}
in the direction of
x
{\displaystyle x}
that lies entirely in
A
.
{\displaystyle A.}
Every radial set is a star domain although not conversely.
Relation to the algebraic interior
The points at which a set is radial are called internal points.[2][3]
The set of all points at which
A
⊆
X
{\displaystyle A\subseteq X}
is radial is equal to the algebraic interior.[1][4]
Relation to absorbing sets
Every absorbing subset is radial at the origin
a
0
=
0
,
{\displaystyle a_{0}=0,}
and if the vector space is real then the converse also holds. That is, a subset of a real vector space is absorbing if and only if it is radial at the origin.
Some authors use the term radial as a synonym for absorbing.[5]
See also
- Absorbing set – Set that can be "inflated" to reach any point
- Algebraic interior – Generalization of topological interior
- Minkowski functional – Function made from a set
- Star domain – Property of point sets in Euclidean spaces
References
- Jaschke, Stefan; Küchler, Uwe (2000). "Coherent Risk Measures, Valuation Bounds, and (
μ
,
ρ
{\displaystyle \mu ,\rho }
)-Portfolio Optimization" (PDF). Humboldt University of Berlin.
- Aliprantis & Border 2006, p. 199–200.
- John Cook (May 21, 1988). "Separation of Convex Sets in Linear Topological Spaces" (PDF). Retrieved November 14, 2012.
- Nikolaĭ Kapitonovich Nikolʹskiĭ (1992). Functional analysis I: linear functional analysis. Springer. ISBN 978-3-540-50584-6.
- Schaefer & Wolff 1999, p. 11.
- Aliprantis, Charalambos D.; Border, Kim C. (2006). Infinite Dimensional Analysis: A Hitchhiker's Guide (Third ed.). Berlin: Springer Science & Business Media. ISBN 978-3-540-29587-7. OCLC 262692874.
- 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.