I have tried to find the explicit definition of them but was not able to. My guess is that they are eigenvalues of the superoperator $\Phi^{\ast}(\Phi)$, where $\Phi$ is the channel and $\Phi^{\ast}$ is its adjoint.
Then, if the channel is expressed in a matrix form, it is about the eigenvalues of matrix $F^{\dagger} \cdot F$. Numerically (by sampling over randomly generated channels), I have found that the largest singular eigenvalue $\sigma_1$ is always larger than $1$ (which is the largest eigenvalue, $\lambda_1 = 1$, of $F$). It is no problem in general, since for a generic matrix $\sigma_1 \ge \vert\lambda_1\vert$. However, I cannot understand how does it fit the following statement from the paper by R. Kukulski et al:
"Let us now discuss singular values of a random superoperator $\Phi$. The leading singular value is equal to unity, which is a consequence of preservation of trace, \begin{equation} \langle \chi | \Phi | \chi \rangle = \langle \chi | \chi \rangle = 1, \end{equation} where $| \chi \rangle = | \rho_{\rm inv} \rangle \rangle/ \Vert\rho_{\rm inv} \Vert_2$ represents the normalized vector of length $d^2$ corresponding to the invariant state of the map, $\rho_{\rm inv}=\Phi(\rho_{\rm inv})$."
So, the question is: What is meant in this excerpt?