Hamilton cycles in weighted Erdos-R\'enyi graphs
Abstract
Given a symmetric n× n matrix P with 0 P(u, v) 1, we define a random graph Gn, P on [n] by independently including any edge \u, v\ with probability P(u, v). For k 1 let Ak be the property of containing k/2 Hamilton cycles, and one perfect matching if k is odd, all edge-disjoint. With an eigenvalue condition on P, and conditions on its row sums, Gn, P∈ Ak happens with high probability if and only if Gn, P has minimum degree k whp. We also provide a hitting time version. As a special case, the random graph process on pseudorandom (n, d, μ)-graphs with μ d(d/n)α for some constant α > 0 has property Ak as soon as it acquires minimum degree k with high probability.
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