Article ID Journal Published Year Pages File Type
6875874 Theoretical Computer Science 2017 20 Pages PDF
Abstract
In this paper, we investigate the SPR graph of rooted trees (rSPR graph) in a new way: by calculating the Ricci-Ollivier curvature with respect to uniform and Metropolis-Hastings random walks. This value quantifies the degree to which a pair of random walkers from specified points move towards each other; negative curvature means that they move away from one another on average, while positive curvature means that they move towards each other. In order to calculate this curvature, we develop fast new algorithms for rSPR graph computation. We then develop formulas characterizing how the number of rSPR neighbors of a tree changes after an rSPR operation is applied to that tree. These give bounds on the curvature, as well as a flatness-in-the-limit theorem indicating that paths of small topology changes are easy to traverse. However, we find that large topology changes (i.e. moving a large subtree) give pairs of trees with negative curvature. We show using simulation that mean access time distributions depend on distance, degree, and curvature, demonstrating the relevance of these results to stochastic tree search.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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