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Let $(X,d)$ be a finite metric space, and let $\varepsilon>0$ be given. In this question I would like to understand

how to show in detail the existence of a metric $\tilde{d}$ on $X$ that is "$\varepsilon$-close to $d$": \begin{align} |\tilde{d}(x,y)-d(x,y)|\leq\varepsilon,\qquad\forall x,y\in X \end{align} and "has rational distance": \begin{align} \tilde{d}(x,y)\in\mathbb{Q},\qquad\forall x,y\in X \end{align}

My motivation comes from the encounter with the Gromov-Hausdorff metric space $(\mathcal{M},d_{GH})$. In the proof of separability of $(\mathcal{M},d_{GH})$, the countable dense subset is given by the collection of all such finite metric spaces with rational distance (up to isometry). The idea is that any compact metric space can be "approximated" by a finite metric space, but the collection of all finite metric spaces (up to isometry) may still be uncountable (due to the many choices of metric on the same underlying set), so we restrict ourselves to those that have rational distance. Then we need to make sure that any metric on a finite space can be "approximated" by one that has rational distance. It is here where I am unable to spell out the detail.

My attempt was a constructive proof: Denote $X=\{x_i\}_{i=1}^N$, and denote $d(x_i,x_j)=|x_ix_j|$. Clearly, the interval $\big(|x_ix_j|-\varepsilon,|x_ix_j|+\varepsilon\big)$ always contains some rational number $q_{ij}$. The problem is how to choose them in order to make the triangle inequality \begin{align} q_{ij}\leq q_{ik}+q_{jk} \end{align} holds, so that we can define $\tilde{d}(x_i,x_j)=\tilde{d}(x_j,x_i)=q_{ij}$. For $i<j$ we always have $|x_ix_j|>0$, so I was thinking of diminishing it a little to get $q_{ij}$ while enlarging $|x_ix_k|$, $|x_jx_k|$ a little to get $q_{ik},q_{jk}$, but this seems not to work because the same $q_{ij}$ needs to appear in both sides of the triangle inequality (e.g. $q_{12}$ is on the L.H.S. of $q_{12}\leq q_{13}+q_{23}$ while on the R.H.S. of $q_{23}\leq q_{12}+q_{13}$).

Any comment, hint or answer is welcome and greatly appreciated.

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    Since there are finitely many points there are finitely many distances between points. Construct a ball around each point with radius less than half the minimum distance between points. This ensures the balls don't overlap. After that you can choose an appropriate rational in each ball and the triangle inequality will be inherited from the triangle inequality in $\mathbb{R}$. – CyclotomicField Jan 29 '22 at 14:19
  • @CyclotomicField Sorry but may I know what do you mean by "an appropriate rational in each ball"? As far as I know, for a finite metric space, a ball $B(x,r)$ with $r>0$ sufficiently small is essentially the singleton ${x}$ itself... – Hopf eccentric Jan 29 '22 at 15:08
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    Hint: Prove first that the set of all metrics on a finite set forms a convex cone with nonempty interior. Then argue that rational vectors are dense in every such cone. – Moishe Kohan Jan 29 '22 at 17:16
  • @Hopfeccentric I mean some rational approximation of the real distance. For example you could truncate the decimal expansion to a sufficient degree of accuracy as to conform with the $\epsilon$ condition. – CyclotomicField Jan 29 '22 at 20:21
  • @CyclotomicField But the ball will still be singletons though. Please correct me if I'm wrong, I'm guessing that you are having a picture of points sitting in $\mathbb{R}^d$, in which case the choosing of rational points or the rational approximation make perfect sense, but my finite set is not assumed to be a priori in any bigger ambient space though. – Hopf eccentric Jan 30 '22 at 12:34
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    @Hopfeccentric they will still be singletons but the distances can be rationalized with respect to the metric. The ball is to ensure you don't accidentally define it in a way that includes a second point which can cause complications. If we chose a rational point in some ball in $\mathbb{R}^n$ this would be equivalent to changing the underlying set which as you noted is not reasonable in this context. Looking back I can see I worded things badly. Sorry if it caused any confusion. – CyclotomicField Jan 30 '22 at 14:00
  • @CyclotomicField I see. Thanks so much for the clarification. – Hopf eccentric Jan 30 '22 at 22:18

2 Answers2

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Here are the steps of the proof, all quite elementary.

  1. Suppose $X$ has cardinality $n$. Then each pseudometric on $X$ is encoded by a vector in ${\mathbb R}^N$, $N=n(n-1)/2$. The semipositivity conditions and triangle inequalities satisfied by the pseudometrics amount to a system of nonstrict linear (homogeneous) inequalities $f_k({\mathbf v})\ge 0$, $k=1,...,K$. Thus, the space of possible pseudometrics on $X$ is a closed convex cone $C$ in ${\mathbb R}^N$. Let $C^\circ\subset C$ denote the subset given by the strict inequalities $f_k({\mathbf v})> 0$, $k=1,...,K$. Then each vector in $C^\circ$ corresponds to a genuine metric on $X$ and $C^\circ$ is open in ${\mathbb R}^N$.

  2. Show that the cone $C$ has nonempty interior. For instance, the discrete metric belongs to $C^\circ$, which is contained in the interior of $C$ (in fact, it equals to the interior of $C$ but we will not need this).

  3. Use the fact that each closed convex subset of ${\mathbb R}^N$ (with nonempty interior) is the closure of its interior. (This is true in much greater generality of convex subsets in topological vector spaces, see here.)

  4. Lastly, use density of rational points in the interior of $C$.

Moishe Kohan
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  • Thanks. I'm sorry but I still have some questions. 1. I'm fine with Step 1,3,4, but how to prove Step 2? The discrete metric is encoded by the vector $v=(1,\ldots,1)$. To show that it's an interior point I'd need to find an open ball $B(v,r)$ such that any vector in this ball has entries satisfying the system of inequalities, but I'm not sure how this is done. I'd think that this is the same difficulty as described in my post above. – Hopf eccentric Jan 30 '22 at 12:18
  • Some texts define a cone by requiring whenever $d$ is a metric then so is $\lambda d$ for all $\lambda\geq 0$, but $0d$ is definitely not a metric, since distinct points will not have nonzero distance. If $\lambda$ is only required to be $>0$ then this problem disappears, but then the cone will not be closed though...
  • – Hopf eccentric Jan 30 '22 at 12:22
  • May I know how do you come up with this proof? I've never thought of viewing the space of metrics as a convex cone in $\mathbb{R}^N$ before...
  • – Hopf eccentric Jan 30 '22 at 12:25
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    First, the closed cone $C$ I defined (by nonstrict inequalities) encodes not only metrics but also pseudometrics. Thus, $0$ is not a problem. The subset $C^\circ\subset C$ (the "open cone"), defined by strict inequalities, consists entirely of metrics. It is obviosly an open subset (since it is the intersection of finitely many open half-spaces). For the discrete metric on $X$ all triangle inequalities are strict, hence, it lies in the open cone $C^\circ$, hence, is an interior point of $C$. In my proof shows that one can approximate every psedumetric on $X$ by rational metrics. – Moishe Kohan Jan 30 '22 at 14:11
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    As for the last question, I am sure I saw it elsewhere and many times. But how else would you describe the totality of all metrics on a set? I think, this is the most natural idea. – Moishe Kohan Jan 30 '22 at 14:14
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    Ah yes the set satisfying the strict triangle inequalities are open half-spaces... silly me. Thanks so much for the answer. For the last question, I'm asking it because, as seen from my post above, I'm tackling the problem by focusing on the given metric alone, while your approach is looking instead at the totality of all metrics (kind of "local vs global"?), which I didn't manage to think of before despite knowing that a "global" approach is often very powerful. – Hopf eccentric Jan 30 '22 at 22:11