In my statistics textbook, it says the special correlation structure $\text{Cov}(X_i, X_k)=\sqrt{\sigma_{ii}\sigma_{kk}} \rho$, or $\text{Corr}(X_i, X_k)=\rho$, all $i \neq k$, is one important structure in which the eigenvalues of $\boldsymbol { \Sigma}$ are not distinct.
My question: I don't know why the correlation matrix $$\boldsymbol{\rho}=\begin{bmatrix}1&\rho & \cdots &\rho\\\rho&1&\cdots &\rho \\ \vdots & \vdots & \ddots & \vdots \\ \rho &\rho &\cdots &1 \\\end{bmatrix}$$
can imply the eigenvalues are not distinct.