<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title>Giant components in biased graph processes</dc:title>
<dc:creator>Gideon Amir</dc:creator><dc:creator>Ori Gurel-Gurevich</dc:creator><dc:creator>Eyal Lubetzky</dc:creator><dc:creator>Amit Singer</dc:creator>
<dc:subject>05C80</dc:subject><dc:subject>74H10</dc:subject><dc:subject>giant component</dc:subject><dc:subject>random graphs</dc:subject><dc:subject>Wormald&#39;s differential equation method</dc:subject>
<dc:description>A random graph process, $\mathcal{G}_1(n)$, is a sequence of graphs on $n$ vertices which begins with the edgeless graph, and where at each step a single edge is added according to a uniform distribution on the missing edges. It is well known that in such a process a giant component (of linear size) typically emerges after $(1+o(1))n/2$ edges (a phenomenon known as `the double jump&#39;), i.e., at time $t=1$ when using a timescale of $n/2$ edges in each step. We consider a generalization of this process, $\mathcal{G}_K(n)$, proposed by Itai Benjamini in order to model the spreading of an epidemic. This generalized process gives a weight of size $1$ to missing edges between pairs of isolated vertices, and a weight of size $K\in[0,\infty)$ otherwise. This corresponds to a case where links are added between $n$ initially isolated settlements, where the probability of a new link in each step is biased according to whether or not its two endpoint settlements are still isolated. Combining methods of [J. Spencer and N.C. Wormald, \textit{Birth control for giants}, Combinatorica \textbf{27} (2007), 587--628] with analytical techniques, we describe the typical emerging time of a giant component in this process, $t_c(K)$, as the singularity point of a solution to a set of differential equations. We proceed to analyze these differential equations and obtain properties of $\mathcal{G}_K$, and in particular, we show that $t_c(K)$ strictly decreases from $\frac{3}{2}$ to $0$ as $K$ increases from $0$ to $\infty$, and that $t_c(K) = (4/\sqrt{3K})(1+o(1))$, where the $o(1)$-term tends to $0$ as $K\to\infty$. Numerical approximations of the differential equations agree both with computer simulations of the process $\mathcal{G}_K(n)$ and with the analytical results.</dc:description>
<dc:publisher>Indiana University Mathematics Journal</dc:publisher>
<dc:date>2010</dc:date>
<dc:type>text</dc:type>
<dc:format>pdf</dc:format>
<dc:identifier>10.1512/iumj.2010.59.4008</dc:identifier>
<dc:source>10.1512/iumj.2010.59.4008</dc:source>
<dc:language>en</dc:language>
<dc:relation>Indiana Univ. Math. J. 59 (2010) 1893 - 1930</dc:relation>
<dc:coverage>state-of-the-art mathematics</dc:coverage>
<dc:rights>http://iumj.org/access/</dc:rights>
</oai_dc:dc>