Bipolar theorem

Theorem in convex analysis

In mathematics, the bipolar theorem is a theorem in functional analysis that characterizes the bipolar (that is, the polar of the polar) of a set. In convex analysis, the bipolar theorem refers to a necessary and sufficient conditions for a cone to be equal to its bipolar. The bipolar theorem can be seen as a special case of the Fenchel–Moreau theorem.[1]: 76–77 

Preliminaries

Suppose that X {\displaystyle X} is a topological vector space (TVS) with a continuous dual space X {\displaystyle X^{\prime }} and let x , x := x ( x ) {\displaystyle \left\langle x,x^{\prime }\right\rangle :=x^{\prime }(x)} for all x X {\displaystyle x\in X} and x X . {\displaystyle x^{\prime }\in X^{\prime }.} The convex hull of a set A , {\displaystyle A,} denoted by co A , {\displaystyle \operatorname {co} A,} is the smallest convex set containing A . {\displaystyle A.} The convex balanced hull of a set A {\displaystyle A} is the smallest convex balanced set containing A . {\displaystyle A.}

The polar of a subset A X {\displaystyle A\subseteq X} is defined to be:

A := { x X : sup a A | a , x | 1 } . {\displaystyle A^{\circ }:=\left\{x^{\prime }\in X^{\prime }:\sup _{a\in A}\left|\left\langle a,x^{\prime }\right\rangle \right|\leq 1\right\}.}
while the prepolar of a subset B X {\displaystyle B\subseteq X^{\prime }} is:
B := { x X : sup x B | x , x | 1 } . {\displaystyle {}^{\circ }B:=\left\{x\in X:\sup _{x^{\prime }\in B}\left|\left\langle x,x^{\prime }\right\rangle \right|\leq 1\right\}.}
The bipolar of a subset A X , {\displaystyle A\subseteq X,} often denoted by A {\displaystyle A^{\circ \circ }} is the set
A := ( A ) = { x X : sup x A | x , x | 1 } . {\displaystyle A^{\circ \circ }:={}^{\circ }\left(A^{\circ }\right)=\left\{x\in X:\sup _{x^{\prime }\in A^{\circ }}\left|\left\langle x,x^{\prime }\right\rangle \right|\leq 1\right\}.}

Statement in functional analysis

Let σ ( X , X ) {\displaystyle \sigma \left(X,X^{\prime }\right)} denote the weak topology on X {\displaystyle X} (that is, the weakest TVS topology on A {\displaystyle A} making all linear functionals in X {\displaystyle X^{\prime }} continuous).

The bipolar theorem:[2] The bipolar of a subset A X {\displaystyle A\subseteq X} is equal to the σ ( X , X ) {\displaystyle \sigma \left(X,X^{\prime }\right)} -closure of the convex balanced hull of A . {\displaystyle A.}

Statement in convex analysis

The bipolar theorem:[1]: 54 [3] For any nonempty cone A {\displaystyle A} in some linear space X , {\displaystyle X,} the bipolar set A {\displaystyle A^{\circ \circ }} is given by:

A = cl ( co { r a : r 0 , a A } ) . {\displaystyle A^{\circ \circ }=\operatorname {cl} (\operatorname {co} \{ra:r\geq 0,a\in A\}).}

Special case

A subset C X {\displaystyle C\subseteq X} is a nonempty closed convex cone if and only if C + + = C = C {\displaystyle C^{++}=C^{\circ \circ }=C} when C + + = ( C + ) + , {\displaystyle C^{++}=\left(C^{+}\right)^{+},} where A + {\displaystyle A^{+}} denotes the positive dual cone of a set A . {\displaystyle A.} [3][4] Or more generally, if C {\displaystyle C} is a nonempty convex cone then the bipolar cone is given by

C = cl C . {\displaystyle C^{\circ \circ }=\operatorname {cl} C.}

Relation to the Fenchel–Moreau theorem

Let

f ( x ) := δ ( x | C ) = { 0 x C otherwise {\displaystyle f(x):=\delta (x|C)={\begin{cases}0&x\in C\\\infty &{\text{otherwise}}\end{cases}}}
be the indicator function for a cone C . {\displaystyle C.} Then the convex conjugate,
f ( x ) = δ ( x | C ) = δ ( x | C ) = sup x C x , x {\displaystyle f^{*}(x^{*})=\delta \left(x^{*}|C^{\circ }\right)=\delta ^{*}\left(x^{*}|C\right)=\sup _{x\in C}\langle x^{*},x\rangle }
is the support function for C , {\displaystyle C,} and f ( x ) = δ ( x | C ) . {\displaystyle f^{**}(x)=\delta (x|C^{\circ \circ }).} Therefore, C = C {\displaystyle C=C^{\circ \circ }} if and only if f = f . {\displaystyle f=f^{**}.} [1]: 54 [4]

See also

  • Dual system
  • Fenchel–Moreau theorem – Mathematical theorem in convex analysis − A generalization of the bipolar theorem.
  • Polar set – Subset of all points that is bounded by some given point of a dual (in a dual pairing)

References

  1. ^ a b c Borwein, Jonathan; Lewis, Adrian (2006). Convex Analysis and Nonlinear Optimization: Theory and Examples (2 ed.). Springer. ISBN 9780387295701.
  2. ^ Narici & Beckenstein 2011, pp. 225–273.
  3. ^ a b Boyd, Stephen P.; Vandenberghe, Lieven (2004). Convex Optimization (pdf). Cambridge University Press. pp. 51–53. ISBN 9780521833783. Retrieved October 15, 2011.
  4. ^ a b Rockafellar, R. Tyrrell (1997) [1970]. Convex Analysis. Princeton, NJ: Princeton University Press. pp. 121–125. ISBN 9780691015866.

Bibliography

  • 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.
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