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Let $S_n$ be a set of $n$ points belonging to $\mathcal{B}_d:=\{\mathbf{x}\in\mathbb{R}^d:\|\mathbf{x}\|_2\le 1\}$, where $d\ll \log(n)$. Let $s_n$ and $\ell_n$ be respectively defined as follows:

$$s_n:={n\choose 3}^{-1}\cdot\!\!\!\!\sum_{1\le i<j<k\le n}\min\left(\|\mathbf{x}_i-\mathbf{x}_j\|_2, \|\mathbf{x}_j-\mathbf{x}_k\|_2, \|\mathbf{x}_k-\mathbf{x}_i\|_2\right)~,$$

$$\ell_n:={n\choose 3}^{-1}\cdot\!\!\!\!\sum_{1\le i<j<k\le n}\max\left(\|\mathbf{x}_i-\mathbf{x}_j\|_2, \|\mathbf{x}_j-\mathbf{x}_k\|_2, \|\mathbf{x}_k-\mathbf{x}_i\|_2\right)~.$$


Question: How can we find a (tight if possible) lower and upper bound for the ratio $\rho_n=\frac{\ell_n}{s_n}$?

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    $\begingroup$ This paper computes the expected triangle area in a unit disk, so might give ideas: Burrows, B. L., and R. F. Talbot. "Random triangles." International Journal of Mathematical Education in Science and Technology 27, no. 2 (1996): 253-259. doi. $\endgroup$ Commented Nov 24, 2020 at 0:53
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    $\begingroup$ And this could be useful: Edelman, Alan, and Gilbert Strang. "Random triangle theory with geometry and applications." Foundations of Computational Mathematics 15, no. 3 (2015): 681-713. arXiv abs. In their model, they compute the probability the triangle is acute. $\endgroup$ Commented Nov 24, 2020 at 0:56
  • $\begingroup$ Thank you a lot @JosephO'Rourke ! $\endgroup$ Commented Nov 24, 2020 at 0:57

1 Answer 1

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For the upper bound:

Take $n/2$ points arbitrarily close to $0$ and $n/2$ points arbitrarily close to 1.

Then, in $3/4$ths of the triangles, there will be a point close to $0$ and a point close to $1$, and therefore the longest edge will be close to 1. Otherwise, all 3 vertices will be at 0 (or at 1) and the longest edge is 0. Thus, $l_n \approx 3/4$.

Furthermore, in any triangle, there will be two points close to $0$ or two points close to $1$, and therefore the smallest edge will be close to $0$. Thus, $s_n \approx 0$.

Consequently, $l_n/s_n \approx \infty$.

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For the lower bound:

Evenly divide the $n$ points among the $d$ unit vectors, $e_1,\ldots,e_d$. The distance between any two unit vectors is $\sqrt{2}$. Approximately $\left(1-\frac{1}{d^2}\right)$ of the triangles contain at least two different $e_i$'s, so $l_n \approx \sqrt{2} \left(1-\frac{1}{d^2}\right)$.

Approximately $\left(1-\frac{1}{d}\right)\left(1 - \frac{2}{d}\right)$ of the triangles contain three different $e_i$'s, and so $s_n \approx \sqrt{2}\left(1-\frac{1}{d}\right)\left(1 - \frac{2}{d}\right)$. Taking the ratio, $l_n/s_n \approx \frac{d+1}{d-2}$. This ratio heads to $1$ as $d \rightarrow \infty$.

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PS. This can be tightened a little by noting that in the $d$-dimensional sphere, you can actually take $d+1$ equidistant points, and therefore $l_n/s_n \approx \frac{d+2}{d-1}$.

PPS. As an example, suppose that $d=20$ and $n=200$. Then, we put $200/20=10$ points at each of $e_1,\ldots,e_{20}$. Draw the first vertex at random. Draw two more vertices at random. The odds that they are at the same $e_i$ is $\approx 1/d^2=1/400$. Therefore, approximately $399/400$ of triangles will have vertices at at least two different $e_i$, and so $l_n \approx \sqrt{2} (399/400)$. When we draw three vertices at random, the odds that they are all different $e_i$ is $19/20 \cdot 18/20$ (because the second draw has to avoid the first and the third draw has to avoid the first two). Therefore, $s_n \approx \sqrt{2} (342/400)$ and $l_n / s_n \approx 399/342 = 21/18 = 7/6 = 1.1\overline{6}$. The approximations come in when we estimate the probability that a randomly drawn triangle has vertices at different $e_i$'s because once a single vertex is draw at $e_i$, there are now less vertices available there, and so the odds of repetition are slightly smaller.

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  • $\begingroup$ You wrote "Then, in any triangle, there will be a point close to $0$ and a point close to $1$, and therefore the longest edge will be close to $1$." This is false. In your example, you have $2\cdot {n/2\choose 3}$ triangles where the length of both the longest and the smallest side is $0$. Hence, it is easy to verify that in this case we have $\ell_n=\tfrac34$ instead of $1$. BTW, generalizing this argument for $d\gg 1$, one can anyway show that there is no upper bound for the ratio $\rho_n=\ell_n/s_n$. However the interesting part regarding $\rho_n$ is to find a lower bound too. $\endgroup$ Commented Dec 1, 2020 at 18:42
  • $\begingroup$ Hi, in d-dimensions, if you divide the points up evenly, n/d to each unit vector, then $l_n \approx sqrt(2) (1-1/d^2)$ and $s_n \approx sqrt(2) (d-1)(d-2)/d^2$, so for large d, $s_n \approx l_n$. Obviously $1$ is a lower bound of $l_n/s_n$ and this shows that you can get arbitrarily close as $d$ increases. $\endgroup$
    – MDR
    Commented Dec 1, 2020 at 20:30
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    $\begingroup$ For a fixed $n$ and $d$, the exact lower bound is not shown. The above construction shows that there are configurations which get arbitrarily close to 1 and of course, 1 is a lower bound. That is, the lower bound is $1+z_d$ where $z_d$ is a term that vanishes as $d$ increases. For specific values, e.g. when $d=100$, it is shown that $102/99\approx 1.02$ is achievable, but there is still a gap between $1$ and $1.02$ and it is not proven exactly how close to $1$ it is possible to get. $\endgroup$
    – MDR
    Commented Dec 2, 2020 at 16:24
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    $\begingroup$ Hi Penelope, I'm not sure what the confusion is here. You are looking for the tightest lower bound. Clearly 1 is a lower bound, but of course it isn't the tighest. The question is how much you can tighten it. The example shows that the $\rho_n$ decreases to $1$ as $d$ increases regardless of the value of $n$ and moreover that it cannot be tightened that much because $z_d \leq 3/(n-1)$. $\endgroup$
    – MDR
    Commented Dec 2, 2020 at 19:01
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    $\begingroup$ Sure, I hope that it helps! $\endgroup$
    – MDR
    Commented Dec 2, 2020 at 19:39

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