An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function
Information Theory
2025-07-29 v1 math.IT
Quantum Physics
Abstract
We consider the computation of the entanglement-assisted quantum rate-distortion function, which plays a central role in quantum information theory. We propose an efficient alternating minimization algorithm based on the Lagrangian analysis. Instead of fixing the multiplier corresponding to the distortion constraint, we update the multiplier in each iteration. Hence the algorithm solves the original problem itself, rather than the Lagrangian relaxation of it. Moreover, all the other variables are iterated in closed form without solving multi-dimensional nonlinear equations or multivariate optimization problems. Numerical experiments show the accuracy of our proposed algorithm and its improved efficiency over existing methods.
Cite
@article{arxiv.2507.19920,
title = {An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function},
author = {Lingyi Chen and Deheng Yuan and Wenyi Zhang and Hao Wu and Huihui Wu},
journal= {arXiv preprint arXiv:2507.19920},
year = {2025}
}