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Let $C$ be a pointed convex cone in a vector space $V$. This means that $C$ satisfies the three following axioms:

  • $C + C \subset C$,
  • $\mathbb{R}_+ \cdot C \subset C$, and
  • $C \cap (-C) = \{ 0 \}$.

Say that $K \subset C$ is a base of $C$ if, for every $x \in C \setminus \{ 0 \}$, there is a unique $\lambda > 0$ such that $\lambda \cdot x \in K$. Usually one demands also that $K$ be convex, a hypothesis that I do not make here. Now if $C$ has at least one base, does a convex base always exist (possibly under additional topological assumptions)?

One approach I have tried is the following: if $K$ and $K'$ are two bases of $C$, say that $K \leqslant K'$ if

  • $\operatorname{co}(K) \supset \operatorname{co}(K')$ and
  • for every $x \in K$ there exists some $0 < \lambda \leqslant 1$ such that $\lambda \cdot x \in K'$.

where $\operatorname{co}$ denotes the convex hull operator. Then $\leqslant$ is a partial order, and one may wish to apply Zorn's lemma and get a maximal element to find the desired convex base. However I cannot manage to show that the partial order is inductive.

Would you have any suggestion or any other idea?

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    $\begingroup$ Every cone has a base in your sense, and this follows from the axiom of choice. In $C\setminus\{0\}$, put $x\sim y$ whenever $x$ and $y$ are positive scalar multiples of each other. This is an equivalence relation, and the axiom of choice lets you pick one representative of each equivalence class. These representatives form a base in your sense. $\endgroup$ Commented Feb 27, 2015 at 14:20
  • $\begingroup$ @TobiasFritz You are proving that a base exists. But the question is can you choose a convex base. $\endgroup$ Commented Feb 27, 2015 at 14:44
  • $\begingroup$ @OlegEroshkin: I suspect Tobias is addressing the hypothesis "if $C$ has at least one base..." which he points out is always achievable. $\endgroup$ Commented Feb 27, 2015 at 15:04
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    $\begingroup$ I may be missing something, but cannot you just intersect your cone with an appropriate hyperplane? $\endgroup$ Commented Feb 27, 2015 at 15:09
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    $\begingroup$ @AlexDegtyarev: that's a good question, but actually the answer is negative. Here's a simple example of a pointed convex cone which does not have a convex base. In $\mathbb{R}^2$, define $(x,y)$ to be in $C$ if $x>0$, or if $x=0$ and $y\geq 0$. (This cone is a simple counterexample also to many other elementary conjectures that one might have about convex cones, by the way.) $\endgroup$ Commented Feb 27, 2015 at 18:06

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This is an extended version of my observations in the comments. The upshot is that there exist pointed convex cones without a convex base, but every cone has a base. Hence what the OP is trying to do is bound not to work.

(1) There are pointed convex cones that do not have a convex base. To see this, take $V=\mathbb{R}^2$ as a simple example, with $C$ given by all those $(x,y)\in\mathbb{R}^2$ for which $x>0$, or $x=0$ and $y>0$. One can visualize the non-existence of a convex base by intersecting $C$ with a line not passing through the origin, and then rotating this line all the way around, noticing that it never hits all the rays of $C$.

More formally, suppose that $K$ is a convex base. This means that there is exactly one point of the form $(0,y_0)\in K$ with $y_0\in K$; up to rescaling, we may assume $y_0=1$. Similarly, we can assume that $(1,0)\in K$ is the only element in $K$ on the $x$-axis.

But then also the ray generated by $(1,-1)$ must intersect $K$ somewhere, say at $(t,-t)$ for $t>0$. By convexity and $(0,1)\in K$, this would imply that the point $$ \frac{t}{t+1}(0,1) + \frac{1}{t+1}(t,-t) = \left(\frac{t}{t+1},0\right) $$ is in $K$ as well, in contradiction to the assumption that $(1,0)$ is the only point in $K$ on the $x$-axis.

(2) Every convex cone has a base (not necessarily convex). This is a simple consequence of the axiom of choice: we choose one representative of each ray $(C\setminus\{0\})/\mathbb{R}_{>0}$.

Arguably, the non-existence of a convex base in (1) is due to the cone not being closed. In fact, in finite dimensions, one can show that every pointed closed convex cone has a base, using the Hahn-Banach theorem as suggested by Willie Wong in the comments. However, constructing a convex base like this requires a functional which is strictly positive on the whole cone, which one can obtain from the Hahn-Banach theorem only in certain situations, such as in finite dimensions. In fact, even a pointed closed cone in an infinite-dimensional locally convex space does not necessarily have a convex base: the following example is my own rephrasing of Exercise 1.7.6 in Aliprantis/Tourky, "Cones and Duality", following Willie Wong's request in the comments.

Let $A$ a set and $\mathcal{B}(A,\mathbb{R})$ the vector space of bounded real-valued functions on $A$. This has an obvious pointed convex cone given by the set of all functions $f$ that are pointwise nonnegative, i.e. for which $f(x)\geq 0$ for all $x\in A$. It is also a normed space via the supremum norm, and the cone is closed.

Now suppose that the cone has a convex base $K$. For nonzero $x\geq 0$, I will say that $x$ lies "above" $K$ if $x$ needs to be scaled down in order to hit $K$. Then for every $x\in A$, consider the indicator function $\chi_{\{x\}}$, and take $A'$ to be the set of all $x$ for which $\chi_{\{x\}}$ is above $K$. I claim that $A'$ is finite: if $n$ of those indicator functions are above $K$, then so is their average, and hence their sum is above $nK$; but this would mean that $\chi_{A'}$, which is greater than all those finite sums in the ordering, is above all $nK$, which is absurd. Hence $\chi_{\{x\}}$ is above $K$ for only finitely many $x$. Similarly, for every $m\in\mathbb{N}$, the function $m\chi_{\{x\}}$ can be above $K$ for only finitely many $x$. Hence the total number of $x$'s, i.e. the cardinality of $A$, is at most countable.

In other words: if $A$ is uncountable, then no convex base exists, although the pointed convex cone is about as nice as it gets!

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  • $\begingroup$ Thank you very much for this (comprehensive I think) answer. $\endgroup$
    – polmath
    Commented Mar 1, 2015 at 20:37
  • $\begingroup$ I am sort of curious about the example now in the infinite dimensional case. If you have the time, can you sketch quickly the example, since some of us don't have access to the book you references? Many thanks in advance if you have the time. $\endgroup$ Commented Mar 2, 2015 at 9:03
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    $\begingroup$ @WillieWong: sure, done! $\endgroup$ Commented Mar 3, 2015 at 3:09
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@TobiasFritz's answer is very excellent. Here is another nice example of a Banach lattice with order unit. Consider a measurable set $(S,\Sigma)$ and a $\sigma$-ring $N\subseteq \Sigma$, elements of which we call null. Now consider $L_\infty(\Sigma|N)$ of all equivalence classes of bounded measurable functionals such that $f\sim g$ if they differ on a null set in $N$. The space $L_\infty(\Sigma|N)$ is an ordered Banach lattice (with usual norm), the positive cone has non-empty interior. the positive cone has a convex base if and only if there is a (finitely additive) probability measure on $\Sigma$ that gives positive probability to every non-null set. The characterisation of the existence of such a probability is given by Kelly (1956).

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