I was reading a proof of the Caro-Wei Theorem using the probabilistic method when I came acroos something that I did not understand.
I learned characteristic functions such that $1_{s\in A}$ equals 1 if s is in A, and 0 otherwise. However, when the proof defines $X$, it says $1_{\sigma\in A_i}$, which does not make sense to me as $A_i$ was defined as an event. Is this a different type of usage of characteristic functions? Could anyone explain it to me?
Thank you!
The characteristic function you’re thinking of is $\mathbb{1}_S$, defined as $\mathbb{1}_S(x)=1$ when $x\in S$ and $\mathbb{1}_S(x)=0$ when $x\notin S$. In the proof you reproduced, don’t think of $1_{\sigma\in A_i}$ as a characteristic function; it’s just a number that depends on $i$. It’s the number $1$ if $\sigma\in A_i$, and it’s $0$ if $\sigma\notin A_i$. So $X(\sigma)$ (defined as $X(\sigma)=\sum_{i=1}^n 1_{\sigma\in A_i}$) is the number of values of $i$ between $1$ and $n$ for which $\sigma\in A_i$, or, using the definition of $A_i$ (and the unmentioned assumption that the vertex set of the graph is $\{1,\dots,n\}$), it’s the number of vertices $i$ in the graph $G$ for which $\sigma(i)<\sigma(j)$ for some vertex $j$ that is a neighbor of of $i$ in $G$.