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{{Short description|Concepts in convex analysis}}
[[File:Dual cone illustration.svg|right|thumb|A set <math>C</math> and its dual cone <math>C^*</math>.]]
[[File:PolarDual cone illustration1illustration.svg|right|thumb|A set <math>''C</math>'' and its polardual cone <math>''C^o</math>. The dual cone and the polar cone are symmetric to each other with respect to the origin{{sup|*}}''.]]
[[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^{{sup|* </math>}}'' of a [[subset]] <math>''C</math>'' in a [[linear space]] <math>''X</math>'' over the [[real numbers|real]]s, e.g. [[Euclidean space]] '''R'''<mathsup>\mathbb R^''n''</mathsup>, with [[topological]] [[dual space]] <math>''X^{{sup|*</math>}}'' is the set
 
:<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>.
 
between <math>X</math> and <math>X^*</math>, i.e. <math>\langle y, x \rangle = y(x) </math>.
The set <math>C^* </math> is always a [[convex cone]], even if <math>C </math> is neither [[convex set|convex]] nor a [[linear cone|cone]].
 
=== 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) ===
<math>C^* </math> is always a [[convex cone]], even if <math>C </math> is neither [[convex set|convex]] nor a [[linear cone|cone]].
 
Alternatively, many authors define the dual cone in the context of a real [[Hilbert space,]] (such as '''R'''<mathsup>\mathbb{R}^''n''</mathsup> 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 ===
Using this latter definition for <math>C^*</math>, we have that
whenUsing <math>this latter definition for ''C{{sup|*}}'', </math>we have that when ''C'' is a cone, the following properties hold:<ref name="Boyd">{{cite book|title=Convex Optimization | first1=Stephen P. |last1=Boyd |first2=Lieven|last2=Vandenberghe|year=2004|publisher=Cambridge University Press|isbn=978-0-521-83378-3 | url=httphttps://wwwweb.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf#page=65 |format=pdf|accessdateaccess-date=October 15, 2011|pages=51–53}}</ref>
* A non-zero vector <math>''y</math>'' is in <math>''C^{{sup|*</math>}}'' if and only if both of the following conditions hold: (i) <math>
#''y </math>'' is a [[surface normal|normal]] at the origin of a [[hyperplane]] that [[supporting hyperplane|supports]] <math>''C </math>''. (ii) <math>
#''y </math>'' and <math>''C </math>'' lie on the same side of that supporting hyperplane.
*<math>''C^{{sup|* </math>}}'' is [[closed set|closed]] and convex.
*<math>C_1 \subseteq C_2</math> implies <math>C_2^* \subseteq C_1^*</math>.
*If <math>''C </math>'' has nonempty interior, then <math>''C^{{sup|* </math>}}'' is ''pointed'', i.e. <math>''C^* </math>'' contains no line in its entirety.
*If <math>''C </math>'' is a cone and the closure of <math>''C </math>'' is pointed, then <math>''C^{{sup|* </math>}}'' has nonempty interior.
*<math>''C^{{sup|**} </math>}'' is the closure of the smallest convex cone containing <math>''C'' (a consequence of the [[hyperplane separation </math>.theorem]])
 
== 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>
A cone <math>C</math> in a vector space <math>X</math> is said to be ''self-dual'' if
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.
<math>X</math> can be equipped with an [[inner product]]
This is slightly different from the above definition, which permits a change of inner product.
<math>\langle . , . \rangle</math> such that the
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.
internal dual cone relative to this inner product
is equal to <math>C</math>.<ref>Iochum, Bruno, "Cônes autopolaires et algèbres de Jordan", Springer, 1984.</ref> 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. This is slightly different than the above definition, which permits a change of inner product. For instance, the above definition makes a cone in <math>\mathbb{R}^n</math> with ellipsoidal base self-dual, because the inner product can be changed to make the base spherical, and a with spherical base
in <math>\mathbb{R}^n</math> is equal to its internal dual.
 
The nonnegative [[orthant]] of '''R'''<mathsup>\mathbb{R}^''n''</mathsup> 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").
So are all cones in '''R'''<mathsup>\mathbb{R}^3</mathsup> 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'''<mathsup>\mathbb{R}^3</mathsup> 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 ==
[[File: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.]]
For a set <math>C</math> in <math>X</math>, the '''polar cone''' of <math>C</math> is the set
 
[[File:Polar cone illustration.svg|right|thumb|The polar of the closed convex cone <math>''C</math>'' is the closed convex cone ''C<mathsup>C^o,</mathsup>'', and vice- versa.]]
:<math>C^oFor =a \leftset ''C'' \{y\in ''X^*: \langle y '', x \ranglethe \leq'''polar 0cone''' \quad \forall x\inof ''C'' is \rightthe \}.</math>set<ref name="Rockafellar">{{cite book|author=[[Rockafellar, R. Tyrrell]]|author-link=Rockafellar, R. Tyrrell|title=Convex Analysis | publisher=Princeton University Press |___location=Princeton, NJ|year=1997|origyearorig-year=1970|isbn=978-0-691-01586-6|pages=121–122}}</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 cone is equal to the negative of the dual cone, i.e. <math>C^o=-C^*</math>.
 
ForIt acan closedbe convexseen that the polar cone is equal to the negative of the dual cone, i.e. ''C<mathsup>Co</mathsup>'' = −''C{{sup|*}}''.

For a closed convex cone ''C'' in <math>''X</math>'', the polar cone is equivalent to the [[polar set]] for <math>''C</math>''.<ref>{{cite book|lastlast1=Aliprantis |firstfirst1=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>
 
== 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
| year = 2002
| pages =
| isbn = 0-415-27479-6
}}
 
*{{cite book
| last = Boltyanski
| first = V. G.
| authorlinkauthor-link= Vladimir Boltyansky
| coauthors author2= Martini, H., |author3=Soltan, P.
| title = Excursions into combinatorial geometry
| publisher = New York: Springer
| year = 1997
| pages =
| isbn = 3-540-61341-2
}}
*{{cite book
 
| last = Goh
| first = C. J.
| coauthors author2= Yang, X.Q.
| title = Duality in optimization and variational inequalities
| publisher = London; New York: Taylor & Francis
| year = 2002
| isbn = 0-415-27479-6
}}
* {{Narici Beckenstein Topological Vector Spaces|edition=2}} <!-- {{sfn | Narici | 2011 | p=}} -->
*{{cite book
| last = Ramm
| first = A.G.
| coauthors editor= Shivakumar, P.N.; |editor2=Strauss, A.V. editors
| title = Operator theory and its applications
| publisher = Providence, R.I.: American Mathematical Society
| year = 2000
| pages =
| isbn = 0-8218-1990-9
}}
* {{Schaefer Wolff Topological Vector Spaces|edition=2}} <!-- {{sfn | Schaefer|Wolff| 1999 | p=}} -->
 
{{Ordered topological vector spaces}}
[[Category:Mathematical optimization]]
 
[[Category:Convex analysis]]
[[Category:Convex geometry]]
[[Category:Linear programming]]
[[Category:Convex analysis]]
 
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