Eigenspace of Euclidean distance matrix. - MathOverflow most recent 30 from http://mathoverflow.net2013-05-22T03:05:47Zhttp://mathoverflow.net/feeds/question/72356http://www.creativecommons.org/licenses/by-nc/2.5/rdfhttp://mathoverflow.net/questions/72356/eigenspace-of-euclidean-distance-matrixEigenspace of Euclidean distance matrix.Sunni2011-08-08T14:33:48Z2011-08-08T14:55:13Z
<p>What is the necessary and sufficient condition (if there is any) that $n$ orthonormal vectors $v_1,v_2,\cdots,v_n$ are eigenvectors of a <a href="http://en.wikipedia.org/wiki/Euclidean_distance_matrix" rel="nofollow">Euclidean distance matrix</a>. When $n=2$, the orthonormal vectors are easily charcterized, i.e., $(1/\sqrt{2}, 1/\sqrt{2})$ and $(1/\sqrt{2}, -1/\sqrt{2})$.</p>
http://mathoverflow.net/questions/72356/eigenspace-of-euclidean-distance-matrix/72357#72357Answer by Tom Leinster for Eigenspace of Euclidean distance matrix.Tom Leinster2011-08-08T14:55:13Z2011-08-08T14:55:13Z<p>This isn't an answer, but it's too long for a comment. As you're maybe aware, a real $n \times n$ matrix $M$ is a Euclidean distance matrix if and only if the following conditions hold:</p>
<ul>
<li>$M_{ij} \geq 0$ for all $i, j$</li>
<li>$M_{ii} = 0$ for all $i$</li>
<li>$M$ is symmetric</li>
<li>$M$ is <strong>conditionally negative definite</strong>, that is,
$$
x^t M x \leq 0
$$
whenever $x \in \mathbb{R}^n$ with $\sum_i x_i = 0$. </li>
</ul>
<p>This was shown in: I. J. Schoenberg, Metric spaces and positive definite functions, Transactions of the AMS 44 (1938), 522-536.</p>