On the Fragile Complexity of Geometric Algorithms

Surprisingly, the question of bounding the maximum number of operations undergone by each individual element in an algorithm - known as the fragile complexity of the algorithm - has not received much attention. In a foundational paper, Afshani et al. (2019) developed the concept of fragility and explored classic problems such as sorting and selection from this perspective. Motivated by a suggestion for future research by Afshani et al., we initiate a study of fragile complexity in computational geometry. We obtain bounds on several time-honored questions in 2D such as computing the maxima, closest pair, convex hull, triangulation, and approximate Euclidean Minimum Spanning Tree (apx-EMST). Our algorithms for the maxima, convex hull, and triangulation problems are competitive with the classical algorithms in terms of worst-case runtime and guarantee polylogarithmic fragility. We present an O(nlog²n) time algorithm that returns a 1.0125-apx-EMST and achieves O(log² n) fragility, thus matching the best known performance up to polylogarithmic factors.