Asymptotically faster algorithms for recognizing $(k,\ell)$-sparse graphs

TL;DR

This paper introduces new, faster algorithms for recognizing $(k, ext{ell})$-sparse graphs across various parameter ranges, improving efficiency from quadratic to near-linear time in many cases.

Contribution

The authors develop the first subquadratic, near-linear recognition algorithms for $(k, ext{ell})$-sparse graphs, combining advanced techniques like bounded-indegree orientations and centroid decomposition.

Findings

Achieved near-linear time recognition algorithms for $0 \\leq \\ell \\leq k$.

Developed $O(n \\sqrt{n})$ and $O(n \\sqrt{n \\log n})$ algorithms for specific ranges.

Provided algorithms that certify non-sparsity with explicit violating sets.

Abstract

The family of $(k,\ell)$-sparse graphs, introduced by Lorea, plays a central role in combinatorial optimization and has a wide range of applications, particularly in rigidity theory. A key algorithmic problem is to decide whether a given graph is $(k,\ell)$-sparse and, if not, to produce a vertex set certifying the failure of sparsity. While pebble game algorithms have long yielded $O(n^2)$-time recognition throughout the classical range $0 \leq \ell < 2k$, and $O(n^3)$-time algorithms in the extended range $2k \leq \ell < 3k$, substantially faster bounds were previously known only in a few special cases. We present new recognition algorithms for the parameter ranges $0 \le \ell \le k$, $k < \ell < 2k$, and $2k \leq \ell < 3k$. Our approach combines bounded-indegree orientations, reductions to rooted arc-connectivity, augmenting-path techniques, and a divide-and-conquer method based on centroid decomposition. This yields the first subquadratic, and in fact near-linear-time, recognition algorithms throughout the classical range when instantiated with the fastest currently available subroutines. Under purely combinatorial implementations, the running times become $O(n\sqrt n)$ for $0 \leq \ell \leq k$ and $O(n\sqrt{n\log n})$ for $k< \ell <2k$. For $2k \leq \ell < 3k$, we obtain an $O(n^2)$-time algorithm when $\ell \leq 2k+1$ and an $O(n^2\log n)$-time algorithm otherwise. In each case, the algorithm can also return an explicit violating set certifying that the input graph is not $(k,\ell)$-sparse.