arXiv:2507.19920 · IEEE Information Theory Workshop (ITW)

An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function

Lingyi Chen, Deheng Yuan, Wenyi Zhang, Hao Wu, Huihui Wu

Published Sep 29, 2025• 0 citations

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 multidimensional nonlinear equations or multivariate optimization problems. Numerical experiments show the accuracy of our proposed algorithm and its improved efficiency over existing methods.

DOI: 10.1109/itw62417.2025.11240306

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