Sharp Thresholds for Temporal Motifs and Doubling Time in Random Temporal Graphs

In this paper we study two natural models of random temporal graphs.

In the first, the continuous model, each edge $e$ is assigned $l_e$ labels, each drawn uniformly at random from $(0,1]$, where the numbers $l_e$ are independent random variables following the same discrete probability distribution.

In the second, the discrete model, the $l_e$ labels of each edge $e$ are chosen uniformly at random from a set $\{1,2,\ldots,T\}$.

In both models we study the existence of $\delta$-temporal motifs.

Here a $\delta$-temporal motif consists of a pair $(H,P)$, where $H$ is a fixed static graph and $P$ is a partial order over its edges.

A temporal graph $\mathcal{G}=(G,\lambda)$ contains $(H,P)$ as a $\delta$-temporal motif if $\mathcal{G}$ has a simple temporal subgraph on the edges of $H$ whose time labels are ordered according to $P$, and whose life duration is at most $\delta$.

We prove sharp existence thresholds for all $\delta$-temporal motifs, and we identify a qualitatively different behavior from the analogous static thresholds in Erdos-Renyi random graphs.

Applying the same techniques, we then characterize the growth of the largest $\delta$-temporal clique in the continuous variant of our random temporal graphs model.

Finally, we consider the doubling time of the reachability ball centered on a small set of vertices of the random temporal graph as a natural proxy for temporal expansion.

We prove sharp upper and lower bounds for the maximum doubling time in the continuous model.