Polarity and Separation of Cones

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Nov 1, 2017 - 4400 University Drive, Fairfax, VA 22030, USA, [email protected]. Abstract. Given a closed convex cone C C Rn and its polar cone C◦, ..... Clearly, M is a nontrivial subspace of Rn. From Proposition 2.1 we easily conclude that.
Polarity and Separation of Cones Valeriu Soltan Department of Mathematical Sciences, George Mason University 4400 University Drive, Fairfax, VA 22030, USA, [email protected]

Abstract Given a closed convex cone C ⊂ Rn and its polar cone C ◦ , properties of the set C ∩(−C ◦ ) are studied. In particular, we solve a problem of Stoker concerning nonemptiness of rint C ∩ (−rint C ◦ ). Based on these properties, new results on separation of C and C ◦ by hyperplanes are established. MSC: 90C25, 52A20, 15A39 Key words: Cone, convex, polar, hyperplane, separation

1. Introduction We recall that a nonempty set C in the n-dimensional Euclidean space Rn is a cone if λx ∈ C whenever λ > 0 and x ∈ C. (Obviously, this definition implies that the origin o of Rn belongs to C, although a stronger condition λ > 0 can be beneficial; see, e. g., [6]). The cone C is called convex if it is a convex set. In a standard way, the (negative) polar cone C ◦ of C is defined by C ◦ = {e ∈ Rn : x·e 6 0 for all x ∈ C}, where x·e means the dot (scalar) product of vectors x and e. Despite a wide usage of polar cones C and C ◦ in various mathematical disciplines, not much is known about the sets D = C ∩ (−C ◦ )

and E = rint C ∩ (−rint C ◦ ),

where rint C denotes the relative interior of C (we observe that the set −C ◦ is often called the dual cone of C). Blumenthal [1] and Dines [2] showed that the existence of positive solutions of certain systems of homogenous linear inequalities can be geometrically formulated as the property D 6= {o} of a suitable convex cone C ⊂ Rn . In this regard Gaddum [4], using a simple argument, proved that D 6= {o} if and only if the cone C is not a subspace. Independently, Stoker [9] asked whether the set E is nonempty and gave a partial affirmative answer by proving that rint C ∩ (−C ◦ ) 6= ∅ for the case when C is a closed convex cone in R3 , distinct from a subspace. Another motivation for the study of the sets D and E comes from separation theory. For instance, an assertion of Klee [5] on the existence of a hyperplane specially separating closed convex cones C1 and C2 in Rn Preprint submitted to Linear Algebra and Its Applications

November 1, 2017

satisfying the condition C1 ∩ C2 = {o} can be equivalently reformulated as rint C1◦ ∩ (−rint C2◦ ) 6= ∅ (see Theorem 4.2 below). In this paper, we determine the dimensions of the sets D and E and prove that rint D = E, as shown in Theorems 3.1 and 3.2. These results allow us to answer affirmatively Stoker’s question on the nonemptiness of E (see Corollary 3.1). The concluding Section 4 contains new assertions on separation of arbitrary convex cones C1 and C2 in Rn (which refine a result of Klee [5]), and, in particular, on separation of cones C and C ◦ (see Theorems 4.1–4.3 and their corollaries) 2. Notation, Terminology, and Preliminaries We follow standard notation and terminology of finite-dimensional convex analysis (see, for instance, the books [7] and [8]). In particular, cl F , dim F , rbd F , rint F , and span F stand, respectively, for the closure, dimension, relative boundary, relative interior, and span of a convex set F ⊂ Rn . For a simplicity of language, we will be dealing with closed convex cones in Rn . Indeed, the obtained results can be easily rewritten for the case of any convex cones, based on the equalities rint C = rint (cl C) and C ◦ = (cl C)◦ . Given a closed convex cone C ⊂ Rn , the set lin C = C ∩ (−C) is called the lineality space of C, and C is called pointed provided lin C = {o}. It is known that lin C is the largest subspace contained in C and C = C + lin C (see, e. g., [8], Theorems 4.14 and 4.15). Obviously, C 6= lin C if and only if C is not a subspace. Equivalently, the number s(C) = dim C − dim (lin C)

(1)

is positive if and only if C is not a subspace. We will need some known results about cones (given below as auxiliary propositions without proof). The first one holds for any closed convex sets; its first part is due to Fenchel [3, p. 44] (also see Rockafellar [7, p. 73]), while the second part can be found in [8, Corollary 5.30]. Proposition 2.1. Let C ⊂ Rn be a closed convex cone, and let L ⊂ Rn be the orthogonal complement of lin C in Rn . With S = L ∩ span C, the cone C can be expressed as the direct sum C = (C ∩ S) + lin C, (2) where C ∩ S is a closed pointed convex cone such that span (C ∩ S) = S. Furthermore, rint C = (rint C ∩ S) + lin C = rint (C ∩ S) + lin C.

(3)

The next two propositions are due to Rockafellar [7] (see, respectively, Theorem 6.5 and Corollary 9.1.2). Proposition 2.2. If closed convex cones C1 and C2 in Rn satisfy the condition rint C1 ∩ rint C2 6= ∅, then rint (C1 ∩ C2 ) = rint C1 ∩ rint C2 . 2

Proposition 2.3. If closed convex cones C1 and C2 in Rn satisfy the condition C1 ∩ C2 = lin C1 ∩ lin C2 , then the cone C1 + C2 is closed. Consequently, if both cones C1 and C2 are pointed and C1 ∩ C2 = {o}, then the cone C1 + C2 is closed and pointed. One more proposition collects some known properties of polar cones (here X ⊥ denotes the orthogonal complement of a nonempty set X ⊂ Rn ). Proposition 2.4. For a closed convex cone C ⊂ Rn , the following assertions hold. C ◦ is a closed convex cone such that C ∩ C ◦ = {o} and (C ◦ )◦ = C. C ◦ is a subspace if and only if C is a subspace. lin C ∈ rbd C (equivalently, lin C ◦ ∈ rbd C ◦ ) if and only if C is not a subspace. span C = (lin C ◦ )⊥ and span C ◦ = (lin C)⊥ . Consequently, lin C ◦ and lin C are orthogonal subspaces, and C ◦ ∩ lin C = C ∩ lin C ◦ = {o}. 5) dim C ◦ = n if and only if C is pointed. 6) Assuming C is not a subspace, a nonzero vector e ∈ Rn belongs to rint C ◦ if and only if x·e < 0 for all x ∈ C \ lin C (see, e. g., Fenchel [3, page 18]).

1) 2) 3) 4)

Also, we will need the following known identities regarding closed convex cones C1 and C2 in Rn : (C1 + C2 )◦ = C1◦ ∩ C2◦

and

(C1 ∩ C2 )◦ = cl (C1◦ + C2◦ ).

(4)

3. Cone Polarity Our approach is based on considering the subspace S from Proposition 2.1, which we will call the orthogonal complement of lin C within span C. Since span C is the sum of orthogonal subspaces lin C and S, the dimension of S equals the number s(C), defined by (1). Lemma 3.1 below shows that S may be considered as a common “axis” in decomposition of C and C ◦ . Lemma 3.1. Let C ⊂ Rn be a closed convex cone, and S be the orthogonal complement of lin C within span C. Then S is the orthogonal complement of lin C ◦ within span C ◦ . Consequently, dim S = dim C ◦ − dim (lin C ◦ ) = s(C ◦ ). (5) Furthermore, C ◦ = (C ◦ ∩ S) + lin C ◦ ,

(6)



and the conclusions of Proposition 2.1 hold for C . Proof. Proposition 2.4 and the choice of S imply that Rn is the sum of pairwise orthogonal subspaces span C, lin C ◦ , and S: Rn = span C + lin C ◦ = lin C + S + lin C ◦ .

(7)

By the same proposition, Rn = span C ◦ + lin C. 3

(8)

Comparing (7) and (8), we see that span C ◦ is the sum of orthogonal subspaces lin C ◦ and S: span C ◦ = lin C ◦ + S. Hence S is the orthogonal complement of lin C ◦ within span C ◦ . The remaining part of the lemma follows from Proposition 2.1. The example below illustrates Lemma 3.1. Example 3.1. For the 2-dimensional closed convex cone C = {(x, y, 0) : x > 0} in R3 , its polar cone is another 2-dimensional closed convex cone, given by C ◦ = {(x, 0, z) : x 6 0}. The lineality spaces lin C and lin C ◦ are, respectively, the y- and z-coordinate axes of R3 , and the subspace S is the x-axis, confirming the compositions (2) and (6). Lemma 3.2. Let C ⊂ Rn be a closed convex cone, and S be the orthogonal complement of lin C within span C. Then (C ∩ S)◦ = C ◦ + lin C

and

(C ◦ ∩ S)◦ = C + lin C ◦ .

Proof. Since S ◦ = S ⊥ , the equalities (4) and (7) give (C ∩ S)◦ = cl (C ◦ + S ◦ ) = cl (C ◦ + S ⊥ ) = cl (C ◦ + lin C + lin C ◦ ). Because C ◦ ∩ lin C = {o}, Proposition 2.3 shows that the convex cone C ◦ + lin C is closed. Based on this argument and the equality C ◦ + lin C ◦ = C ◦ , we have cl (C ◦ + lin C + lin C ◦ ) = cl (C ◦ + lin C) = C ◦ + lin C. Similarly, (C ◦ ∩ S)◦ = cl ((C ◦ )◦ + S ◦ ) = cl (C + S ⊥ ) = cl (C + lin C + lin C ◦ ) = cl (C + lin C ◦ ) = C + lin C ◦ . Theorem 3.1. Let C ⊂ Rn be a closed convex cone which is not a subspace. Also, let S be the orthogonal complement of lin C within span C. Then the set D = C ∩ (−C ◦ ) is a closed convex pointed cone of positive dimension s(C), with span D = S

and

D◦ = C ◦ − C.

Proof. According to Proposition 2.1 and Lemma 3.1, C = (C ∩ S) + lin C

and C ◦ = (C ◦ ∩ S) + lin C ◦ .

This argument and the equalities (7) give D = C ∩ (−C ◦ ) = ((C ∩ S) + lin C) ∩ ((−C ◦ ∩ S) + lin C ◦ ) = (C ∩ S) ∩ (−C ◦ ∩ S) = D ∩ S. 4

Hence D is a closed convex pointed cone as the intersection of closed convex pointed cones C ∩ S and −C ◦ ∩ S (see again Proposition 2.1 and Lemma 3.1). Furthermore, since (C ∩ S) ∩ (C ◦ ∩ S) = (C ∩ C ◦ ) ∩ S = {o} ∩ S = {o}, Proposition 2.3 implies that the set B = (C ∩ S) + (−C ◦ ∩ S) also is a closed convex pointed cone. Consequently, dim B ◦ = n, as follows from Proposition 2.4. On the other hand, a combination of the equalities (2), (4), (6), (7), and Lemma 3.2 gives B ◦ = ((C ∩ S) + (−C ◦ ∩ S))◦ = (C ∩ S)◦ ∩ (−C ◦ ∩ S)◦ = (C ◦ + lin C) ∩ (−C + lin C ◦ ) = ((C ◦ ∩ S) + lin C ◦ + lin C) ∩ (−(C ∩ S) + lin C + lin C ◦ ) = ((C ◦ ∩ S) + S ⊥ ) ∩ (−(C ∩ S) + S ⊥ ) = (C ◦ ∩ S) ∩ −(C ∩ S)) + S ⊥ = (D ∩ S) + S ⊥ . Therefore, dim D = dim (D ∩ S) = dim B ◦ − dim S ⊥ = n − dim S ⊥ = dim S = s(C). Combined with the inclusion D ⊂ S, the last equality implies that span D = S. A similar argument gives D◦ = (C ∩ (−C ◦ ))◦ = cl (C ◦ + (−C ◦ )◦ ) = cl (C ◦ + (−C)) = C ◦ − C, where the last equality follows from C ∩ C ◦ = {o} and Proposition 2.3. Theorem 3.2. Under the assumptions of Theorem 3.1, the following assertions hold. 1) The relative interior, rint D, of the cone D = C ∩ (−C ◦ ) is a convex set of positive dimension s(C). 2) rint D = E = rint (C ∩ S) ∩ (−rint (C ◦ ∩ S)). Proof. 1) This part immediately follows from Theorem 3.1 and the fact that the relative interior of a nonempty convex set F ⊂ Rn is nonempty and has the same dimension as F (see, e. g., [7, Section 6]). 2) According to Proposition 2.1, Lemma 3.1, and Theorem 3.1, span D = span (C ∩ S) = span (C ◦ ∩ S) = S. From the definition of relative interior, one can easily obtain the following elementary fact: if C1 and C2 are convex cones in Rn such that C1 ⊂ C2 and span C1 = span C2 , then rint C1 ⊂ rint C2 . Consequently, the equality D = (C ∩ S) ∩ (−C ◦ ∩ S) 5

implies the inclusion ∅ 6= rint D ⊂ rint (C ∩ S) ∩ rint (−C ◦ ∩ S), and Proposition 2.2 gives rint D = rint (C ∩ S) ∩ (−rint (C ◦ ∩ S)). Finally, combining Propositions 2.1, 2.4, and Lemma 3.1, we obtain E = rint C ∩ (−rint C ◦ ) = (rint (C ∩ S) + lin C) ∩ (−rint (C ◦ ∩ S) + lin C ◦ ) = rint (C ∩ S) ∩ (−rint (C ◦ ∩ S)) = rint D. Theorem 3.2 gives an affirmative answer to the question of Stoker (see the introduction). Corollary 3.1. If C ⊂ Rn is a closed convex cone, then the set E = rint C ∩ (−rint C ◦ ) is nonempty. Proof. If C is not a subspace, then the assertion immediately follows from Theorem 3.2. If C is a subspace, then rint C = C and C ◦ = C ⊥ is a subspace orthogonal to C. Therefore, rint C ◦ = C ◦ , which gives E = rint C ∩ (−rint C ◦ ) = C ∩ C ◦ = C ∩ C ⊥ = {o} = 6 ∅. 4. Separation of Convex Cones If a hyperplane H ⊂ Rn separates closed convex cones C1 and C2 , then, due to the inclusion o ∈ C1 ∩ C2 , it has to be of the form H = {x ∈ Rn : x·e = 0}

(9)

for some nonzero vector e. Following Rockafellar [7, p. 95], a hyperplane of the form (9) properly separates C1 and C2 provided C1 and C2 lie in distinct closed halfspaces of Rn determined by H such that C1 ∪ C2 6⊂ H. As proved in [7, Theorem 11.3], nonzero convex cones C1 and C2 are properly separated by a hyperplane if and only if rint C1 ∩ rint C2 = ∅. The theorem below shows that polar cones poses a stronger form of proper separation. Theorem 4.1. Let C ⊂ Rn be a closed convex cone distinct from a subspace. Also, let D = C ∩ (−C ◦ ). The following assertions hold. 1) There is a hyperplane H ⊂ Rn separating C and C ◦ . 2) Every hyperplane H ⊂ Rn separating C and C ◦ satisfies the conditions C 6⊂ H

and

C ◦ 6⊂ H.

(10)

3) A hyperplane of the form (9) separates C and C ◦ if and only if e ∈ D ∪ (−D) for some nonzero vector e. 6

Proof. 1) The above criterion of proper separation and the inclusions rint C ∩ rint C ◦ ⊂ (C \ lin C) ∩ (C ◦ \ lin C ◦ ) ⊂ (C \ {o}) ∩ (C ◦ \ {o}) = (C ∩ C ◦ ) \ {o} = {o} \ {o} = ∅ (which follow from assertions 1) and 3) of Proposition 2.4) show the existence of at least one hyperplane H of the form (9) properly separating C and C ◦ . 2) Let a hyperplane H ⊂ Rn separate C and C ◦ . Assume, for contradiction, that one of the cones C and C ◦ , say C, is contained in H. Then span C ⊂ H. Consider the line l = span {e}. By Proposition 2.4, l = H ⊥ ⊂ (span C)⊥ = lin C ◦ . Since l meets both open halfspaces determined by H, the hyperplane H cannot support C ◦ , contrary to the choice of H. 3) Suppose a hyperplane of the form (9) separates C and C ◦ . Then C and C ◦ are included into the opposite closed halfspaces V1 = {x ∈ Rn : x·e 6 0}

and V2 = {x ∈ Rn : x·(−e) 6 0}.

If, for instance, C ⊂ V1 and C ◦ ⊂ V2 , then e ∈ C ◦ ∩ (−C ◦ )◦ = C ◦ ∩ (−C) = −D. Similarly, e ∈ D if C ⊂ V2 and C ◦ ⊂ V1 . The converse assertion is obvious. We will need the following lemma. Lemma 4.1. If a hyperplane H ⊂ Rn supports a closed convex cone C ⊂ Rn , then lin C ⊂ H and H = {x ∈ Rn : x·e = 0} for a suitable vector e 6= o. Proof. Let H = {x ∈ Rn : x·e = γ}, where e 6= o and γ ∈ R. Denote by V a closed halfspace determined by H and containing C. Without loss of generality, we may assume that V = {x ∈ Rn : x·e 6 γ}. Since o ∈ C ⊂ V , one has 0 = o·e 6 γ. By the hypothesis, H ∩ C 6= ∅. Choose any point u ∈ H ∩ C. Then u·e = γ. Since λu ∈ C ⊂ V for all λ > 0, one has λγ = (λu)·e 6 γ whenever λ > 0. The latter is possible only if γ = 0. So, H = {x ∈ Rn : x·e = 0}. For the inclusion lin C ⊂ H, choose any point v ∈ lin C. Because lin C is a subspace, one has µv ∈ lin C ⊂ V whenever µ ∈ R. Thus (µv)·e 6 0 for all µ ∈ R, which is possible only if v·e = 0. Hence v ∈ H. Suppose that a hyperplane H of the form (9) separates convex cones C1 and C2 . By Lemma 4.1, both subspaces lin C1 and lin C2 lie H. Consequently, lin C1 ⊂ C1 ∩ H

and

lin C2 ⊂ C2 ∩ H.

In this regard, we will say that H sharply separates C1 and C2 provided H separates them and C1 ∩ H = lin C1 and C2 ∩ H = lin C2 . (11) A result of Klee [5, Theorem 2.7], formulated here for the case of Rn , states that closed convex cones C1 and C2 in Rn satisfying the condition C1 ∩ C2 = {o} are sharply separated by a hyperplane. The theorem below refines this assertion. 7

Theorem 4.2. Let C1 and C2 be closed convex cones in Rn , each distinct from a subspace. The following conditions are equivalent. 1) C1 and C2 are sharply separated by a hyperplane. 2) C1 ∩ C2 = lin C1 ∩ lin C2 . 3) The set F = rint C1◦ ∩ (−rint C2◦ ) has positive dimension. Proof. 1) ⇔ 2). Suppose C1 and C2 are sharply separated by a hyperplane H ⊂ Rn such that C1 and C2 lie, respectively in the closed halfspaces V1 and V2 determined by H. Then, by (11), C1 ∩ C2 = (C1 ∩ V1 ) ∩ (C2 ∩ V2 ) = (C1 ∩ C2 ) ∩ (V1 ∩ V2 ) = (C1 ∩ C2 ) ∩ H = (C1 ∩ H) ∩ (C2 ∩ H) = lin C1 ∩ lin C2 . Conversely, suppose that C1 ∩ C2 = lin C1 ∩ lin C2 . Put M = lin C1 ∩ lin C2 ,

N = M ⊥,

Ci0 = Ci ∩ N,

i = 1, 2.

Clearly, M is a nontrivial subspace of Rn . From Proposition 2.1 we easily conclude that Ci = Ci0 + M

and

lin Ci0 = lin Ci ∩ N,

i = 1, 2.

Furthermore, C10 ∩ C20 = (C1 ∩ C2 ) ∩ N = (lin C1 ∩ lin C2 ) ∩ N = M ∩ N = {o}. By the above assertion of Klee, used now for the case of vector space N , there is a subspace G ⊂ N of dimension dim N − 1 sharply separating C10 and C20 . It is easy to see that the subspace H = G + M is a hyperplane in Rn sharply separating C1 and C2 . 1) ⇔ 3). Suppose C1 and C2 are sharply separated by a hyperplane of the form (9) such that C1 ⊂ V1 = {x ∈ Rn : x·e 6 0}

and C2 ⊂ V2 = {x ∈ Rn : x·(−e) 6 0}.

Combining assertion 6) of Proposition 2.4 and the equalities (11), we obtain the inclusions e ∈ rint C1◦ and −e ∈ rint C2◦ . Thus e ∈ F . Similarly, −e ∈ F if C1 ⊂ V2 and C2 ⊂ V1 . Summing up, e ∈ F ∪ (−F ), which shows that F has positive dimension. Conversely, if F has positive dimension and e is a nonzero vector in F ∪ (−F ), then the above argument implies that the hyperplane (9) sharply separates C1 and C2 . Remark 4.1. From the proof of Theorem 4.2 it follows that a hyperplane of the form (9) sharply separates closed convex cones C1 and C2 if and only if e ∈ F ∪ (−F ) for some nonzero vector e. A combination of Theorems 3.2 and 4.2 gives the corollary below. Corollary 4.1. Let C ⊂ Rn be a closed convex cone which is not a subspace. Also, let D = C ∩ (−C ◦ ). The following assertions hold. 1) There is a hyperplane sharply separating C and C ◦ . 8

2) A hyperplane of the form (9) sharply separates C and C ◦ if and only if e ∈ rint D ∪ (−rint D) for some nonzero vector e. The next result describes conditions for the uniqueness of a hyperplane which sharply separates given cones. Theorem 4.3. Let C1 and C2 be closed convex cones in Rn , neither being a subspace, which are separated by a hyperplane. The following conditions are equivalent. 1) There is a unique hyperplane sharply separating C1 and C2 . 2) C1 ∩ C2 = lin C1 ∩ lin C2 and the subspace lin C1 + lin C2 is a hyperplane. 3) The set F = rint C1◦ ∩ (−rint C2◦ ) is one-dimensional. Proof. 1) ⇔ 2). Let H be a unique hyperplane of the form (9) sharply separating C1 and C2 . Without loss of generality, we may assume that kek = 1. Then C1 ∩ C2 = lin C1 ∩ lin C2 according to Theorem 4.2. Since both subspaces lin C1 and lin C2 lie in H, their sum M = lin C1 + lin C2 also lies in H. Thus dim M 6 n − 1. Assume, for contradiction, that dim M < n − 1. Then the orthogonal complement of M is at least two-dimensional. Clearly, e ∈ M ⊥ . By Proposition 2.1, we can write Ci = (Ci ∩ Si ) + lin Ci , where Si is the orthogonal complement of lin Ci within span Ci , i = 1, 2. The condition Ci ∩ H = lin Ci obviously implies that (Ci ∩ Si ) ∩ H = {o}, i = 1, 2. Let Pi denote the intersection of Ci ∩ Si with the unit sphere of Rn , i = 1, 2. Clearly, Pi 6= ∅ because Ci ∩ Si is not a subspace, i = 1, 2. The above argument shows that Pi ∩ H = ∅, i = 1, 2. Since both sets P1 and P2 are nonempty compacts, there is a scalar ε > 0 such that, for any unit vector e0 ∈ Rn satisfying the condition ke − e0 k < ε, the hyperplane H 0 = {x ∈ Rn : x·e0 = 0} is disjoint from P1 ∪ P2 . Because Ci ∩ Si = {λy : λ > 0, y ∈ Pi },

i = 1, 2,

we have (Ci ∩ Si ) ∩ H 0 = {o},

i = 1, 2,

whenever ke − e0 k < ε. Finally, choose e0 in M ⊥ such that e and e0 are not collinear (this is possible due to dim M ⊥ > 2) and ke − e0 k < ε. Then M ⊂ H0

and Ci ∩ H 0 = lin Ci ,

i = 1, 2.

Consequently, H 0 sharply separates C1 and C2 , contrary to condition 1). Thus M is a hyperplane. Conversely, if condition 2) is satisfied, then, by Theorem 4.2, there is a hyperplane H sharply separating C1 and C2 . Furthermore, the inclusion lin C1 + lin C2 ⊂ H and the assumption dim (lin C1 + lin C2 ) = n − 1 show that lin C1 + lin C2 = H, implying the uniqueness of H. 9

1) ⇔ 3). By Theorem 4.2 and Remark 4.1, the set F has positive dimension and every nonzero vector e ∈ F ∪ (−F ) determines the hyperplane of the form (9) which sharply separates C1 and C2 . Assuming condition 1), suppose for a moment that dim F > 2 and choose in F non-collinear vectors e1 and e2 . Then the hyperplanes H1 = {x ∈ Rn : x·e1 = 0}

and H2 = {x ∈ Rn : x·e2 = 0}

are distinct and both sharply separate C1 and C2 , contrary to 1). Hence 1) ⇒ 3). Similarly, 3) ⇒ 1). Corollary 4.2. For a closed convex cone C ⊂ Rn , which is not a subspace, the following conditions are equivalent. 1) There is a unique hyperplane sharply separating C and C ◦ . 2) The subspace lin C + lin C ◦ is a hyperplane. 3) C is a closed halfplane of the form C = L + h, where L is a subspace, with 0 6 dim L 6 n − 1, and h is a closed halfline with endpoint o, orthogonal to L. Proof. By Proposition 2.4, C ∩ C ◦ = lin C ∩ lin C ◦ = {o}. This argument and Theorem 4.3 show that it suffices to prove the equivalence of conditions 2) and 3). Assume first that lin C + lin C ◦ is a hyperplane and let L = lin C. Denote by S the orthogonal complement of L within span C. Then (7) implies the equality dim S = 1. Consequently, the set h = C ∩ S is a closed halfline with endpoint o, orthogonal to L. This argument and Proposition 2.1 immediately imply that C = lin C + (C ∩ S) = L + h. Conversely, suppose that C is the sum of a subspace L and a closed halfline h with endpoint o, orthogonal to L. Obviously, lin C = L and

span C = L + (h ∪ −h).

If S is the one-dimensional subspace containing h, then S is the orthogonal complement of lin C within span C. A combination of Propositions 2.1 and 2.4 shows that dim (lin C ◦ ) = dim (span C)⊥ = n − dim (span C) = n − dim (lin C) − 1. Since the subspaces lin C and lin C ◦ are orthogonal, their sum lin C + lin C ◦ is a hyperplane. Acknowledgment. The author thanks the anonymous referees for helpful suggestions on the original manuscript.

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References [1] L.M. Blumenthal, Metric methods in linear inequalities, Duke Math. J. 15 (1948), 955–966. [2] L.L. Dines, Note on certain associated systems of linear equalities and inequalities, Ann. Math. 28 (1926-27), 41–42. [3] W. Fenchel, Convex Cones, Sets, and Functions, Mimeographed lecture notes. Spring Term 1951, Princeton University, 1953. [4] J.W. Gaddum, A theorem on convex cones with applications to linear inequalities, Proc. Amer. Math. Soc. 3 (1952), 957–960. [5] V.L. Klee, Separation properties of convex cones, Proc. Amer. Math. Soc. 6 (1955), 313–318. [6] J. Lawrence, V. Soltan, On unions and intersections of nested families of cones, Beitr. Algebra Geom. 57 (2016), 655–665. [7] R.T. Rockafellar, Convex Analysis, Princeton Universty Press, Princeton, NJ, 1970. [8] V. Soltan, Lectures on Convex Sets, World Scientific, Hackensack, NJ, 2015. [9] J.J. Stoker, Unbounded convex sets, Amer. J. Math. 62 (1940), 165–179.

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