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arXiv · 1206.1374

Recognizing Treelike k-Dissimilarities

Sven Herrmann·Katharina T. Huber·Vincent Moulton·Andreas Spillner
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Abstract

A k-dissimilarity D on a finite set X, |X| >= k, is a map from the set of size k subsets of X to the real numbers. Such maps naturally arise from edge-weighted trees T with leaf-set X: Given a subset Y of X of size k, D(Y) is defined to be the total length of the smallest subtree of T with leaf-set Y . In case k = 2, it is well-known that 2-dissimilarities arising in this way can be characterized by the so-called "4-point condition". However, in case k > 2 Pachter and Speyer recently posed the following question: Given an arbitrary k-dissimilarity, how do we test whether this map comes from a tree? In this paper, we provide an answer to this question, showing that for k >= 3 a k-dissimilarity on a set X arises from a tree if and only if its restriction to every 2k-element subset of X arises from some tree, and that 2k is the least possible subset size to ensure that this is the case. As a corollary, we show that there exists a polynomial-time algorithm to determine when a k-dissimilarity arises from a tree. We also give a 6-point condition for determining when a 3-dissimilarity arises from a tree, that is similar to the aforementioned 4-point condition.

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BibTeXRIS

Sven Herrmann, Katharina T. Huber, Vincent Moulton, Andreas Spillner. 2012-06-07. Recognizing Treelike k-Dissimilarities. https://doi.org/10.1007/s00357-012-9115-2

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