.png){kind=icon}
返回
Practical distributed quantum information processing with LOCCNet
.png){kind=icon}
OA
AI
DOI：10.1038/s41534-021-00496-x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Distributed quantum information processing is essential for building quantum networks and enabling more extensive quantum computations. In this regime, several spatially separated parties share a multipartite quantum system, and the most natural set of operations is Local Operations and Classical Communication (LOCC). As a pivotal part in quantum information theory and practice, LOCC has led to many vital protocols such as quantum teleportation. However, designing practical LOCC protocols is challenging due to LOCC's intractable structure and limitations set by near-term quantum devices. Here we introduce LOCCNet, a machine learning framework facilitating protocol design and optimization for distributed quantum information processing tasks. As applications, we explore various quantum information tasks such as entanglement distillation, quantum state discrimination, and quantum channel simulation. We discover protocols with evident improvements, in particular, for entanglement distillation with quantum states of interest in quantum information. Our approach opens up new opportunities for exploring entanglement and its applications with machine learning, which will potentially sharpen our understanding of the power and limitations of LOCC. An implementation of LOCCNet is available in Paddle Quantum, a quantum machine learning Python package based on PaddlePaddle deep learning platform.
Keyword:
ENTANGLEMENT PURIFICATION
LOCAL OPERATIONS
STATE
DISTINGUISHABILITY
COMMUNICATION
TELEPORTATION
CRYPTOGRAPHY
DISTILLATION
NONLOCALITY
期刊
IF:
8.3
论文数:
1.4K
被引数:
8.1K
机构
引用论文
A variational eigenvalue solver on a photonic quantum processor光子量子处理器上的变分特征值求解器.png)
NATURE COMMUNICATIONS
OAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏分享收藏分享收藏
查看更多内容