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Convex set
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== Convex hulls and Minkowski sums == === Convex hulls === {{Main|convex hull}} Every subset {{mvar|A}} of the vector space is contained within a smallest convex set (called the ''convex hull'' of {{mvar|A}}), namely the intersection of all convex sets containing {{mvar|A}}. The convex-hull operator Conv() has the characteristic properties of a [[closure operator]]: * ''extensive'': {{math|''S'' ⊆ Conv(''S'')}}, * ''[[Monotone function#Monotonicity in order theory|non-decreasing]]'': {{math|''S'' ⊆ ''T''}} implies that {{math|Conv(''S'') ⊆ Conv(''T'')}}, and * ''[[idempotence|idempotent]]'': {{math|Conv(Conv(''S'')) {{=}} Conv(''S'')}}. The convex-hull operation is needed for the set of convex sets to form a <!-- complete -->[[lattice (order)|lattice]], in which the [[join and meet|"''join''" operation]] is the convex hull of the union of two convex sets <math display=block>\operatorname{Conv}(S)\vee\operatorname{Conv}(T) = \operatorname{Conv}(S\cup T) = \operatorname{Conv}\bigl(\operatorname{Conv}(S)\cup\operatorname{Conv}(T)\bigr).</math> The intersection of any collection of convex sets is itself convex, so the convex subsets of a (real or complex) vector space form a complete [[lattice (order)|lattice]]. === Minkowski addition === {{Main|Minkowski addition}} [[File:Minkowski sum graph - vector version.svg|thumb|alt=Three squares are shown in the nonnegative quadrant of the Cartesian plane. The square {{math|''Q''<sub>1</sub> {{=}} [0, 1] × [0, 1]}} is green. The square {{math|''Q''<sub>2</sub> {{=}} [1, 2] × [1, 2]}} is brown, and it sits inside the turquoise square {{math|1=Q<sub>1</sub>+Q<sub>2</sub>{{=}}[1,3]×[1,3]}}.|[[Minkowski addition]] of sets. The <!-- [[Minkowski addition|Minkowski]] -->[[sumset|sum]] of the squares Q<sub>1</sub>=[0,1]<sup>2</sup> and Q<sub>2</sub>=[1,2]<sup>2</sup> is the square Q<sub>1</sub>+Q<sub>2</sub>=[1,3]<sup>2</sup>.]] In a real vector-space, the ''[[Minkowski addition|Minkowski sum]]'' of two (non-empty) sets, {{math|''S''<sub>1</sub>}} and {{math|''S''<sub>2</sub>}}, is defined to be the [[sumset|set]] {{math|''S''<sub>1</sub> + ''S''<sub>2</sub>}} formed by the addition of vectors element-wise from the summand-sets <math display=block>S_1+S_2=\{x_1+x_2: x_1\in S_1, x_2\in S_2\}.</math> More generally, the ''Minkowski sum'' of a finite family of (non-empty) sets {{math|''S<sub>n</sub>''}} is <!-- defined to be --> the set <!-- of vectors --> formed by element-wise addition of vectors<!-- from the summand-sets --> <math display=block> \sum_n S_n = \left \{ \sum_n x_n : x_n \in S_n \right \}.</math> For Minkowski addition, the ''zero set'' {{math|{0} }} containing only the [[null vector|zero vector]] {{math|0}} has [[identity element|special importance]]: For every non-empty subset S of a vector space <math display=block>S+\{0\}=S;</math> in algebraic terminology, {{math|{0} }} is the [[identity element]] of Minkowski addition (on the collection of non-empty sets).<ref>The [[empty set]] is important in Minkowski addition, because the empty set annihilates every other subset: For every subset {{mvar|S}} of a vector space, its sum with the empty set is empty: <math>S+\emptyset=\emptyset</math>.</ref> === Convex hulls of Minkowski sums === Minkowski addition behaves well with respect to the operation of taking convex hulls, as shown by the following proposition: Let {{math|''S''<sub>1</sub>, ''S''<sub>2</sub>}} be subsets of a real vector-space, the [[convex hull]] of their Minkowski sum is the Minkowski sum of their convex hulls <math display=block>\operatorname{Conv}(S_1+S_2)=\operatorname{Conv}(S_1)+\operatorname{Conv}(S_2).</math> This result holds more generally for each finite collection of non-empty sets: <math display=block>\text{Conv}\left ( \sum_n S_n \right ) = \sum_n \text{Conv} \left (S_n \right).</math> In mathematical terminology, the [[operation (mathematics)|operation]]s of Minkowski summation and of forming [[convex hull]]s are [[commutativity|commuting]] operations.<ref>Theorem 3 (pages 562–563): {{cite journal|first1=M.|last1=Krein|author-link1=Mark Krein|first2=V.|last2=Šmulian|year=1940|title=On regularly convex sets in the space conjugate to a Banach space|journal=Annals of Mathematics |series=Second Series| volume=41 |issue=3 |pages=556–583|jstor=1968735|doi=10.2307/1968735}}</ref><ref name="Schneider">For the commutativity of [[Minkowski addition]] and [[convex hull|convexification]], see Theorem 1.1.2 (pages 2–3) in Schneider; this reference discusses much of the literature on the [[convex hull]]s of [[Minkowski addition|Minkowski]] [[sumset]]s in its "Chapter 3 Minkowski addition" (pages 126–196): {{cite book|last=Schneider|first=Rolf|title=Convex bodies: The Brunn–Minkowski theory|series=Encyclopedia of mathematics and its applications|volume=44|publisher=Cambridge University Press|location=Cambridge|year=1993|pages=xiv+490|isbn=0-521-35220-7|mr=1216521|url=https://archive.org/details/convexbodiesbrun0000schn}}</ref> === Minkowski sums of convex sets === The Minkowski sum of two compact convex sets is compact. The sum of a compact convex set and a closed convex set is closed.<ref>Lemma 5.3: {{cite book|first1=C.D.|last1= Aliprantis|first2=K.C.| last2=Border|title=Infinite Dimensional Analysis, A Hitchhiker's Guide| publisher=Springer| location=Berlin|year=2006|isbn=978-3-540-29587-7}}</ref> The following famous theorem, proved by Dieudonné in 1966, gives a sufficient condition for the difference of two closed convex subsets to be closed.<ref name="Zalinescu p. 7">{{cite book|last=Zălinescu|first=C.|title=Convex analysis in general vector spaces|url=https://archive.org/details/convexanalysisge00zali_934|url-access=limited|publisher=World Scientific Publishing Co., Inc|location= River Edge, NJ |date= 2002|page=[https://archive.org/details/convexanalysisge00zali_934/page/n27 7]|isbn=981-238-067-1|mr=1921556}}</ref> It uses the concept of a '''recession cone''' of a non-empty convex subset ''S'', defined as: <math display=block>\operatorname{rec} S = \left\{ x \in X \, : \, x + S \subseteq S \right\},</math> where this set is a [[convex cone]] containing <math>0 \in X </math> and satisfying <math>S + \operatorname{rec} S = S</math>. Note that if ''S'' is closed and convex then <math>\operatorname{rec} S</math> is closed and for all <math>s_0 \in S</math>, <math display=block>\operatorname{rec} S = \bigcap_{t > 0} t (S - s_0).</math> '''Theorem''' (Dieudonné). Let ''A'' and ''B'' be non-empty, closed, and convex subsets of a [[locally convex topological vector space]] such that <math>\operatorname{rec} A \cap \operatorname{rec} B</math> is a linear subspace. If ''A'' or ''B'' is [[locally compact]] then ''A'' − ''B'' is closed.
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