24 citations · 35 across the 9 of their papers we have counts for
10 papers
Complementing Quantum Error Correction in Quantum Metrology via Swap Test
Xiaodie Lin, Linxuan Li, Haidong Yuan
The precision and sensitivity achievable in quantum metrology are often compromised by the presence of noise. While quantum error correction has emerged as a promising strategy, it…
Scalable Quantum Error Mitigation with Neighbor-Informed Learning
Zhenyu Chen, Bin Cheng, Minbo Gao +4
Noise in quantum hardware is the primary obstacle to realizing the transformative potential of quantum computing. Quantum error mitigation (QEM) offers a promising pathway to enhan…
Variational Optimization for Quantum Problems using Deep Generative Networks
Lingxia Zhang, Xiaodie Lin, Peidong Wang +4
Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems.…
Certifying bipartite pure quantum states efficiently using untrusted devices
Lijinzhi Lin, Zhenyu Chen, Xiaodie Lin +1
It has been known that all bipartite pure quantum states can be certified by quantum self-testing, i.e., any such states can be pinned down completely based on the statistics produ…
The Generations of Classical Correlations via Quantum Schemes
Zhenyu Chen, Lijinzhi Lin, Xiaodie Lin +2
Suppose two separated parties, Alice and Bob, share a bipartite quantum state or a classical correlation called a \emph{seed}, and they try to generate a target classical correlati…
Certifying Unknown Genuine Multipartite Entanglement by Neural Networks
Zhenyu Chen, Xiaodie Lin, Zhaohui Wei
Suppose we have an unknown multipartite quantum state, how can we experimentally find out whether it is genuine multipartite entangled or not? Recall that even for a bipartite quan…
Quantifying Unknown Quantum Entanglement via a Hybrid Quantum-Classical Machine Learning Framework
Xiaodie Lin, Zhenyu Chen, Zhaohui Wei
Quantifying unknown quantum entanglement experimentally is a difficult task, but also becomes more and more necessary because of the fast development of quantum engineering. Machin…
Quantifying Unknown Entanglement by Neural Networks
Xiaodie Lin, Zhenyu Chen, Zhaohui Wei
Quantum entanglement plays a crucial role in quantum information processing tasks and quantum mechanics, hence quantifying unknown entanglement is a fundamental task. However, this…
Experimental Entanglement Quantification for Unknown Quantum States in a Semi-Device-Independent Manner
Yu Guo, Lijinzhi Lin, Huan Cao +9
Using the concept of non-degenerate Bell inequality, we show that quantum entanglement, the critical resource for various quantum information processing tasks, can be quantified fo…
Quantum and Classical Hybrid Generations for Classical Correlations
Xiaodie Lin, Zhaohui Wei, Penghui Yao
We consider two-stage hybrid protocols that combine quantum resource and classical resource to generate classical correlations shared by two separated players. Our motivation is tw…