As the title shows, is there a way to calculate the eigenvalues of $A\equiv \vec x\vec x^T+\vec y \vec y^T$, where $\vec x$ and $\vec y$ are two linearly independent vectors in $\mathbb{R}^n$(don't have to be unit vector).
Here're some of my thoughts. We can see that $A$ is of rank 2 since it can be seen as a map from $\mathbb{R}^n$ to $\mathbb{R}^n$ and there are only two linearly independent vectors in its range. So we may set the eigenvectors of $A$ as $a\vec x+b\vec y$, where $a$ and $b$ are two real numbers, then we have chances to get the eigenvalues by solving $$A(a\vec x+b\vec y) =\lambda (a\vec x+b\vec y)\tag{1}.$$
For example, if $\vec{x}=\frac{1}{\sqrt{2}}\left( \begin{array}{c} 1\\ 1\\ \end{array} \right) , \vec{y}=\left( \begin{array}{c} 1\\ 0\\ \end{array} \right) $, we can solve eq(1) to get the eigenvalues $1\pm \frac{1}{\sqrt 2}$. But eq(1) only have two equations while with 3 parameters $a,b,\lambda$.
So my question is: is there a way to calculate the eigenvalues of $xx^T+yy^T$, such as a formula related to $\vec x$ and $\vec y$ that I don't know?