Concentration of measure for the number of isolated vertices in the   Erd\H{o}s-R\'{e}nyi random graph by size bias couplings
  A concentration of measure result is proved for the number of isolated vertices $Y$ in the Erd\H{o}s-R\'{e}nyi random graph model on $n$ edges with edge probability $p$. When $\mu$ and $\sigma^2$ denote the mean and variance of $Y$ respectively, $P((Y-\mu)/\sigma\ge t)$ admits a bound of the form $e^{-kt^2}$ for some constant positive $k$ under the assumption $p \in (0,1)$ and $np\rightarrow c \in (0,\infty)$ as $n \rightarrow \infty$. The left tail inequality $$ P(\frac{Y-\mu}{\sigma}\le -t)&\le& \exp(-\frac{t^2\sigma^2}{4\mu}) $$ holds for all $n \in {2,3,...},p \in (0,1)$ and $t \ge 0$. The results are shown by coupling $Y$ to a random variable $Y^s$ having the $Y$-size biased distribution, that is, the distribution characterized by $E[Yf(Y)]=\mu E[f(Y^s)] $ for all functions $f$ for which these expectations exist. 
Subhankar Ghosh, Larry Goldstein and Martin Raic
math.PR