In this lecture we will learn about a quantum generalization of the matrix scaling problem devised by Gurvits in 2004 — the operator scaling problem.

We will see how we can generalize the tools from invariant theory developed in the first lecture to this setting, and how we can analyse a similar alternating minimization algorithm for this problem.

Time permitting, we will discuss how this method can be vastly generalized to other settings.