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{{Short description|Concepts in convex analysis}}
[[
[[File:Polar cone illustration1.svg|right|thumb|A set ''C'' and its polar cone ''C<sup>o</sup>''. The dual cone and the polar cone are symmetric to each other with respect to the origin.]]
'''Dual cone''' and '''polar cone''' are closely related concepts in [[convex analysis]], a branch of [[mathematics]].
== Dual cone ==
The '''dual cone''' <math>C^* </math> of a [[subset]] <math>C</math> in a [[linear space]] <math>X</math>, e.g. [[Euclidean space]] <math>\mathbb R^n</math>, with [[topological]] [[dual space]] <math>X^*</math> is the set▼
=== In a vector space ===
▲The '''dual cone'''
:<math>C^* = \left \{y\in X^*: \langle y , x \rangle \geq 0 \quad \forall x\in C \right \},</math>
where <math>\langle y, x \rangle</math> is the [[dual system|duality pairing]] between ''X'' and ''X{{sup|*}}'', i.e. <math>\langle y, x\rangle = y(x)</math>.
<math>C^* </math> is always a [[convex cone]], even if <math>C </math> is neither [[convex set|convex]] nor a [[linear cone|cone]]. ▼
▲The set <math>C^*
=== In a topological vector space ===
If ''X'' is a [[topological vector space]] over the real or complex numbers, then the '''dual cone''' of a subset ''C'' ⊆ ''X'' is the following set of continuous linear functionals on ''X'':
:<math>C^{\prime} := \left\{ f \in X^{\prime} : \operatorname{Re} \left( f (x) \right) \geq 0 \text{ for all } x \in C \right\}</math>,{{sfn | Schaefer|Wolff| 1999 | pp=215–222}}
which is the [[polar set|polar]] of the set -''C''.{{sfn | Schaefer|Wolff| 1999 | pp=215–222}}
No matter what ''C'' is, <math>C^{\prime}</math> will be a convex cone.
If ''C'' ⊆ {0} then <math>C^{\prime} = X^{\prime}</math>.
=== In a Hilbert space (internal dual cone) ===
Alternatively, many authors define the dual cone in the context of a real [[Hilbert space]] (such as '''R'''<sup>''n''</sup> equipped with the Euclidean inner product) to be what is sometimes called the ''internal dual cone''.
:<math>C^*_\text{internal} := \left \{y\in X: \langle y , x \rangle \geq 0 \quad \forall x\in C \right \}.</math>
=== Properties ===
* A non-zero vector ''y'' is in ''C{{sup|*}}'' if and only if both of the following conditions hold:
*<math>C^* </math> is [[closed set|closed]] and convex.▼
#''y'' is a [[surface normal|normal]] at the origin of a [[hyperplane]] that [[supporting hyperplane|supports]] ''C''.
#''y'' and ''C'' lie on the same side of that supporting hyperplane.
*<math>C_1 \subseteq C_2</math> implies <math>C_2^* \subseteq C_1^*</math>.
*If
*If
*
== Self-dual cones ==
A cone ''C'' in a vector space ''X'' is said to be ''self-dual'' if ''X'' can be equipped with an [[inner product]] ⟨⋅,⋅⟩ such that the internal dual cone relative to this inner product is equal to ''C''.<ref>Iochum, Bruno, "Cônes autopolaires et algèbres de Jordan", Springer, 1984.</ref>
==Polar cone==▼
Those authors who define the dual cone as the internal dual cone in a real Hilbert space usually say that a cone is self-dual if it is equal to its internal dual.
[[Image:Polar cone illustration.svg|right|thumb|The polar of the closed convex cone <math>C</math> is the closed convex cone <math>C^o,</math> and vice-versa.]]▼
This is slightly different from the above definition, which permits a change of inner product.
For instance, the above definition makes a cone in '''R'''<sup>''n''</sup> with ellipsoidal base self-dual, because the inner product can be changed to make the base spherical, and a cone with spherical base in '''R'''<sup>''n''</sup> is equal to its internal dual.
The nonnegative [[orthant]] of '''R'''<sup>''n''</sup> and the space of all [[positive semidefinite matrix|positive semidefinite matrices]] are self-dual, as are the cones with ellipsoidal base (often called "spherical cones", "Lorentz cones", or sometimes "ice-cream cones").
:<math>C^o = \left \{y\in X^*: \langle y , x \rangle \leq 0 \quad \forall x\in C \right \}.</math><ref name="Rockafellar">{{cite book|author=[[Rockafellar, R. Tyrrell]]|title=Convex Analysis|publisher=Princeton University Press|___location=Princeton, NJ|year=1997|origyear=1970|isbn=9780691015866|pages=121-122}}</ref>▼
So are all cones in '''R'''<sup>3</sup> whose base is the convex hull of a regular polygon with an odd number of vertices.
A less regular example is the cone in '''R'''<sup>3</sup> whose base is the "house": the convex hull of a square and a point outside the square forming an equilateral triangle (of the appropriate height) with one of the sides of the square.
▲== Polar cone ==
It can be seen that the polar cone cone is equal to the negative of the dual cone, i.e. <math>C^o=-C^*</math>.▼
▲[[
For a closed convex cone <math>C</math> in <math>X</math>, the polar cone is equivalent to the [[polar set]] for <math>C</math>.<ref>{{cite book|last=Aliprantis|first=C.D.|last2=Border|first2=K.C.|title=Infinite Dimensional Analysis: A Hitchhiker's Guide|edition=3|publisher=Springer|year=2007|isbn=978-3-540-32696-0|doi=10.1007/3-540-29587-9|page=215}}</ref>▼
▲
:<math>C^o = \left \{y\in X^*: \langle y , x \rangle \leq 0 \quad \forall x\in C \right \}.</math>
▲It can be seen that the polar
▲For a closed convex cone
== See also ==
* [[Bipolar theorem]]
* [[Polar set]]
== References ==
{{Reflist}}
==Bibliography==
*{{cite book▼
| last = Goh▼
| first = C. J.▼
| coauthors = Yang, X.Q.▼
| title = Duality in optimization and variational inequalities▼
| publisher = London; New York: Taylor & Francis▼
| date = 2002▼
| isbn = 0415274796▼
}}▼
*{{cite book
| last = Boltyanski
| first = V. G.
|
|
| title = Excursions into combinatorial geometry
| publisher = New York: Springer
|
|
}}
▲*{{cite book
▲ | last = Goh
▲ | first = C. J.
▲ | title = Duality in optimization and variational inequalities
▲ | publisher = London; New York: Taylor & Francis
▲}}
* {{Narici Beckenstein Topological Vector Spaces|edition=2}} <!-- {{sfn | Narici | 2011 | p=}} -->
*{{cite book
| last = Ramm
| first = A.G.
|
| title = Operator theory and its applications
| publisher = Providence, R.I.: American Mathematical Society
|
|
}}
* {{Schaefer Wolff Topological Vector Spaces|edition=2}} <!-- {{sfn | Schaefer|Wolff| 1999 | p=}} -->
{{Ordered topological vector spaces}}
[[Category:
[[Category:Convex geometry]]
[[Category:Linear programming]]
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