For a fixed set of vertices, let be the first step at which they all belong to one graph component. In the uniform random graph process, lies between and with high probability for every . Below that scale the marked isolated vertex count has divergent expected value and small relative variance. Above it the logarithmic-regime giant component misses vertices; exchangeability and a union bound show that none are marked. The label coupling then transfers the two assertions to the process.
It suffices to prove the assertion after replacing by : that replacement gives a tighter interval. Thus assume and , and put
At , let count isolated vertices in . The same indicator random variable calculation as for all isolated vertices gives
By the Chebyshev inequality, with high probability. Since eventually, the marked vertices are then not all connected.
At , the logarithmic-regime giant component result applies with and any fixed . Its unique giant component misses vertices. On the event that it misses at most twice that number, exchangeability makes the missed vertex set uniform conditional on its size. A union bound therefore gives
Thus all of is connected at with high probability.
For the uniform random graph process, assign uniform labels to the edges of the complete graph as independent random variables and reveal them in label order. The binomial random graph is the prefix containing the labels at most , where has a binomial distribution with parameters and . Its variance at is , whereas the gap between and the relevant endpoint is . The Chebyshev inequality gives and with high probability, with harmless integer rounding. The monotone graph property that all marked vertices are connected now implies
The marked-set connectivity threshold is lower than the threshold for connecting every vertex, because only about specified vertices need to avoid the small graph components.