Quantum state tomography (QST) of discrete variable can be interpreted as the optimization problem of likelihood function on semi-definite cone.
The non-linear constraint of semi-definiteness is conventionally parametrized by using matrix decomposition.
However, this parameterizing make the likelihood function non-convex.
In this research, we applied the augmented Lagrangian method to QST, and show the performance of the method.