Nonlocality Distillation for High-Dimensional System
Guo-Zhu Pan, Chao Li, Zheng-Gen Chen, Ming Yang, Zhuo-Liang Cao

TL;DR
This paper develops universal distillation protocols for high-dimensional nonlocality in bipartite systems, demonstrating that nonlocality can be amplified beyond binary systems and that class differences affect distillation efficiency.
Contribution
It introduces comparators-based protocols for high-dimensional nonlocality distillation, extending previous binary protocols to any dimension and highlighting the importance of class-based nonlocality representations.
Findings
High-dimensional nonlocality can be distilled using new protocols.
Efficiency depends on wiring and class of initial nonlocality boxes.
Protocols are more powerful and universal than previous two-dimensional methods.
Abstract
The intriguing and powerful capability of nonlocality in communication field ignites the research of the nonlocality distillation. The first protocol presented in Ref[Phys. Rev. Lett. 102, 120401] shows that the nonlocality of bipartite binary-input and binary-output nonsignaling correlated boxes could be amplified by 'wiring' two copies of weaker-nonlocality boxes. Several optimized distillation protocols were presented later for bipartite binary-input and binary-output nonsignaling correlated boxes. In this paper, we focus on the bipartite binary-input and multi-nary-output nonsignaling correlated boxes---high-dimensional boxes, and design comparators-based protocols to achieve the distillation of high-dimensional nonlocality. The results show that the high-dimensional nonlocality can be distilled in different ways, and we find that the efficiencies of the protocols are influenced not…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProcess Optimization and Integration · Field-Flow Fractionation Techniques · Crystallization and Solubility Studies
