Paper detail

Packing a randomly edge-colored random graph with rainbow $k$-outs

Let $G$ be a graph on $n$ vertices and let $k$ be a fixed positive integer. We denote by $\mathcal G_{\text{$k$-out}}(G)$ the probability space consisting of subgraphs of $G$ where each vertex $v\in V(G)$ randomly picks $k$ neighbors from $G$, independently from all other vertices. We show that if $δ(G)=ω(\log n)$ and $k\geq 2$, then the following holds for every $p=ω(\log n/δ(G))$. Let $H$ be a random graph obtained by keeping each $e\in E(G)$ with probability $p$ independently at random and then coloring its edges independently and uniformly at random with elements from the set $[kn]$. Then, w.h.p. $H$ contains $t:=(1-o(1))δ(G)p/(2k)$ edge-disjoint graphs $H_1,...,H_t$ such that each of the $H_i$ is \emph{rainbow} (that is, all the edges are colored with distinct colors), and such that for every monotone increasing property of graphs $\mathcal P$ and for every $1\leq i\leq t$ we have $\Pr[\mathcal G_{\text{$k$-out}}(G)\models \mathcal P]\leq \Pr[H_i\models \mathcal P]+n^{-ω(1)}$. Note that since (in this case) a typical member of $\mathcal G_{\text{$k$-out}}(G)$ has average degree roughly $2k$, this result is asymptotically best possible. We present several applications of this; for example, we use this result to prove that for $p=ω(\log n/n)$ and $c=23n$, a graph $H\sim \mathcal G_{c}(K_n,p)$ w.h.p. contains $(1-o(1))np/46$ edge-disjoint rainbow Hamilton cycles. More generally, using a recent result of Frieze and Johansson, the same method allows us to prove that if $G$ has minimum degree $δ(G)\geq (1+\varepsilon)n/2$, then there exist functions $c=O(n)$ and $t=Θ(np)$ (depending on $\varepsilon$) such that the random subgraph $H\sim \mathcal G_{c}(G,p)$ w.h.p. contains $t$ edge-disjoint rainbow Hamilton cycles.

preprint2014arXivOpen access

Signal facts

What is known right now

Open access4 authors2 topics

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.