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The Hamilton cycle space of random graphs
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abstract
The cycle space of a graph $G$, denoted $C(G)$, is a vector space over ${\mathbb F}_2$, spanned by all incidence vectors of edge-sets of cycles of $G$. If $G$ has $n$ vertices, then $C_n(G)$ denotes the subspace of $C(G)$, spanned by the incidence vectors of Hamilton cycles of $G$. A classical result in the theory of random graphs asserts that for $G \sim \mathbb{G}(n,p)$, asymptotically almost surely the necessary condition $\delta(G) \geq 2$ is also sufficient to ensure Hamiltonicity. Resolving a problem of Christoph, Nenadov, and Petrova, we augment this result by proving that for $G \sim \mathbb{G}(n,p)$, with $n$ being odd, asymptotically almost surely the condition $\delta(G) \geq 3$ (observed to be necessary by Heinig) is also sufficient for ensuring $C_n(G) = C(G)$. That is, not only does $G$ typically have a Hamilton cycle, but its Hamilton cycles are typically rich enough to span its cycle space.
Forward citations
Cited by 2 Pith papers
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On graphs whose cycle space is spanned by their Hamilton cycles
Under strengthened Chvátal-Erdős, McDiarmid-Yolov and dominating-set conditions with odd n, the cycle space equals the Hamilton-cycle subspace.
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The Hamilton cycle space of random regular graphs and randomly perturbed graphs
Hamilton cycles span the full cycle space asymptotically almost surely in random regular graphs of sufficiently large constant degree, and in randomly perturbed dense graphs.
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