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New bounds for linear arboricity and related problems
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abstract
A linear forest is a collection of vertex-disjoint paths. The Linear Arboricity Conjecture states that every graph of maximum degree $\Delta$ can be decomposed into at most $\lceil(\Delta+1)/2\rceil$ linear forests. We prove that $\Delta/2 + \mathcal{O}(\log n)$ linear forests suffice, where $n$ is the number of vertices of the graph. If $\Delta = \Omega(n^\varepsilon)$, this is an exponential improvement over the previous best error term. We achieve this by generalising P\'osa rotations from rotations of one endpoint of a path to simultaneous rotations of multiple endpoints of a linear forest. This method has further applications, including the resolution of a conjecture of Feige and Fuchs on spanning linear forests with few paths and the existence of optimally short tours in connected regular graphs.
Forward citations
Cited by 2 Pith papers
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Hamilton cycles in pseudorandom graphs: resilience and approximate decompositions
For pseudorandom graphs with large spectral gap, every subgraph with minimum degree above d/2 is Hamiltonian, and the whole edge set can be packed into, and covered by, about d/2 Hamilton cycles.
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Efficient Hamilton covers and linear arboricity of random graphs
Random graphs with any edge probability have Hamilton covers of the smallest possible size, once Hamilton cycles exist.
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