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For a $n$-polygon in $\mathbb{R}^3$ the set of distances between all pairs of vertices is given. (How) is it possible to reconstruct the geometric structure of the polygone?

Symbolically: For a set of coordinates $(x_i,y_i,z_i)$ with $i=1,...,n$ we have given $r_{k} = (x_i -x_j)^2 + (y_i - y_j)^2 + (z_i - z_j)^2$, for $k = 1,...,n(n-1)/2$ without knowing the map $k\rightarrow (i,j)$ and want to know the set of $(x_i,y_i,z_i)$.

It seems clear, that the distances between the points determine the polygon only up to translations and rotations. So we are seeking to determine only 3$n$-6 degrees of freedom and we have $n(n-1)/2$ equations. As well the coordinates are at most determined up to an arbitrary permutation. The question of the assignment of the distances to actual vertices seems a key in the solution.

I have absolutely now clue as to how address the question, I guess the answer will somehow involve group theory.

It is motivated by the determination of molecular structures using diffraction
methods. Its a kind of toy-version (all elements the same) of the so called inverse structure problem. I am doing experimental research on this subject. It is usually solved using model structures (you just assume the type of polygon including the mapping between $k$ and $(i,j)$ and fit the structure parameters (coordinates) to the diffraction data).

(I am also clueless about the correct tags for the disciplines that involves, so sorry for wrong guesses in case).

2 Answers2

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A related question is as follows: Let $P$ be a polytope in $\mathbb{R}^n$, with say integer vertices.

Consider the new Laurent generating function $$F(x) = \sum_{p,q \in P} x^{p-q}$$, where the sum ranges over all vertices of $P$ (or maybe lattice points of $P$), with the convention $x^a = x_1^{a_1} \dotsm x_n^{a_n}$. Note that $F(x)$ encodes all information you are given, and a bit more.

Is it always possible to recover $P$ from $F(x)$? If no, then your question also has no as an answer.

This might be related to Minkovski sums of polytopes.

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Check out this quite recent paper of Dokmanic et al (arxiv 1502.07541v2)

Igor Rivin
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