Abstract
We give offline algorithms for processing a sequence of 2- and 3-edge and vertex connectivity queries in a fully-dynamic undirected graph. While the current best fully-dynamic online data structures for 3-edge and 3-vertex connectivity require \(O(n^{2/3})\) and O(n) time per update, respectively, our per-operation cost is only \(O(\log n)\), optimal due to the dynamic connectivity lower bound of Patrascu and Demaine. Our approach utilizes a divide and conquer scheme that transforms a graph into smaller equivalents that preserve connectivity information. This construction of equivalents is closely-related to the development of vertex sparsifiers, and shares important connections to several upcoming results in dynamic graph data structures, including online models.
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Notes
- 1.
The \(\tilde{O}(\cdot )\) notation hides \(\log \log n\) factors.
- 2.
This complexity is claimed in Thorup’s STOC 2000 [34] result. As noted by Huang et al. [22], the paper provides few details, deferring to a journal version that has since not appeared. The best complexity for online fully-dynamic biconnectivity prior to this claim was \(O(\log ^5 n)\) by Holm and Thorup [18].
- 3.
See https://codeforces.com/blog/entry/15296 and https://codeforces.com/gym/100551/problem/A, for example.
- 4.
We take \(\cup \) here to be in the multigraph sense; an edge \(uv \in E_W\) is added regardless if there is already a uv edge in \(E_H\) or \(E_{G}\).
- 5.
Here we slightly abuse our requirement \(W \subseteq V_H\), where \(V_H\) are the vertices of H. A map of W onto \(V_H\) that preserves the cuts needed by c-edge/c-vertex equivalence suffices.
- 6.
Some ‘virtual’ edges are needed in this construction, because a vertex can still belong to multiple cycles.
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A Omitted Proofs
A Omitted Proofs
Proof
(Proof of Lemma 10). We prove by contradiction. Let G be a graph with no nontrivial 3-edge connected component. Suppose there exists two simple cycles a and b in G with more than one vertex, and thus at least one edge, in common.
Call the vertices in the first simple cycle \(a_1, \ldots , a_n\) and the second simple cycle \(b_1, \ldots , b_m\), in order along the cycle.
Since these cycles are not the same, there must be some vertex not common to both cycles. Without loss of generality, assume (by flipping a and b) that b is not a subset of a, and (by shifting b cyclically) that \(b_1\) is only in b and not a.
Now let \(b_{first}\) be the first vertex after \(b_1\) in b that is common to both cycles, so
and let \(b_{last}\) be the last vertex in b common to both cycles
The assumption that these two cycles have more than 1 vertex in common means that
We claim \(b_{first}\) and \(b_{last}\) are 3-edge connected.
We show this by constructing three edge-disjoint paths connecting \(b_{first}\) and \(b_{last}\). Since both \(b_{first}\) and \(b_{last}\) occur in a, we may take the two paths formed by cycle a connecting \(b_{first}\) and \(b_{last}\), which are clearly edge-disjoint.
By construction, vertices
are not shared with a. Thus they form a third edge-disjoint path connecting \(b_{first}\) and \(b_{last}\), and so the claim follows. Therefore, a graph with no 3-edge connected vertices, and thus no nontrivial 3-edge connected component has the property that two simple cycles have at most one vertex in common.
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Peng, R., Sandlund, B., Sleator, D.D. (2019). Optimal Offline Dynamic 2, 3-Edge/Vertex Connectivity. In: Friggstad, Z., Sack, JR., Salavatipour, M. (eds) Algorithms and Data Structures. WADS 2019. Lecture Notes in Computer Science(), vol 11646. Springer, Cham. https://doi.org/10.1007/978-3-030-24766-9_40
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