In our previous work, we presented a Blahut-Arimoto type algorithm for computing the discrete memoryless (DM) classical-quantum channel capacity. And the speed of convergence is analyzed. In this paper, we present numerical experiment to show that the algorithm converged much faster than the theoretical prediction. Also we present an explicit approximate solution for the binary inputs, two dimensional outputs classical-quantum channel, which has an error within
3×10−4We derive converging hierarchies of efficiently computable semidefinite programming outer bounds on the optimal fidelity for the transmission of quantum information over noisy quantum channels. Based on positive partial transpose conditions we give a sufficient criterion for the exact convergence at any given level of the hierarchies. The worst case convergence speed of our hierarchies is quantified via positive semidefinite representable outer approximations on the set of separable Choi states, which are based on novel finite de Finetti theorems for quantum channels.
We generalize alternating optimization algorithms of Blahut-Arimoto type to the quantum setting. In particular, we give iterative algorithms to compute the mutual information of quantum channels, the Holevo quantity of classical-quantum channels, the coherent information of less noisy quantum channels, and the thermodynamic capacity of quantum channels. Our convergence analysis is based on quantum entropy inequalities and leads to a priori additive
ε-approximations after
O(ε−1logN) iterations, where
N denotes the input dimension of the channel. We complement our analysis with an a posteriori stopping criterion which allows us to terminate the algorithm after significantly fewer iterations compared to the a priori criterion in numerical examples. Finally, we discuss heuristics to accelerate the convergence.