An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866912502788390912 |
|---|---|
| author | Chen, Lingyi Yuan, Deheng Zhang, Wenyi Wu, Hao Wu, Huihui |
| author_facet | Chen, Lingyi Yuan, Deheng Zhang, Wenyi Wu, Hao Wu, Huihui |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_19920 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function Chen, Lingyi Yuan, Deheng Zhang, Wenyi Wu, Hao Wu, Huihui Information Theory Quantum Physics 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. |
| title | An Efficient Alternating Minimization Algorithm for Computing Quantum Rate-Distortion Function |
| topic | Information Theory Quantum Physics |
| url | https://arxiv.org/abs/2507.19920 |