The following is proved in these lecture notes.
Let $A$ be an $n\times n$ real matrix with all entries positive. Then $A$ has a unique positive eigenvector (up to positve scaling), and the eigenvalue of $A$ corresponding to this eigenvector is greater than every other real eigenvalue in absolute value.
By a positive vector we mean a vector all of whose entries are positive.
(I am alluding the statement made alongside "Perron-Frobenius Theorem" in the link provided. What I have stated is not quite what is stated in the PDF).
The proof given goes as follows.
Let $X$ be the set of all the points $(x_1, \ldots, x_n)\in\mathbf R^n$ such that each $x_i\geq 0$, and $\sum x_i^2=1$. Define $T:X\to X$ as $Tv=Av/\|Av\|_2$. Then $T$ is a contraction (I haven't yet verified this but this seems intuitively reasonable). Therefore, by Banach Fixed Point theorem, there is a unique vector $v\in X$ which is fixed by $T$. Thus $v$ is an eigenvector of $A$ and say $Av=\lambda v$.
Now let $\mu$ be any other real eigenvalue of $A$, and let $w=(w_1, \ldots, w_n)$ be a corresponding eigenvector. At least one entry of $w$ is negative. Write $|w|$ to denote the vector whose $i$-th entry is $|w_i|$.
Here is the statement I am unable to understand
Then $A(|w|)$ has smaller length than $\lambda L$, where $L$ is the length of $w$.
Can somebody explain why is this true?
It seems what is really used here is that $\|Au\|\leq \lambda \|u\|_2$ for each $u\in X$, but I don't see why is this true.
A related discussion is here.