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20212025
most citedQuantifying Unknown Quantum Entanglement via a Hybrid Quantum-Classical Machine Learning Framework

24 citations · 24 across the 6 of their papers we have counts for

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7 papers

quant-ph2025

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…

quant-ph2025

Taming Barren Plateaus in Arbitrary Parameterized Quantum Circuits without Sacrificing Expressibility

Zhenyu Chen, Yuguo Shao, Zhengwei Liu +1

Quantum algorithms based on parameterized quantum circuits (PQCs) have enabled a wide range of applications on near-term quantum devices. However, existing PQC architectures face s…

quant-ph2023

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…

quant-ph2023

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…

quant-ph2022

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…

quant-ph2022★ 24 cited

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…

quant-ph2021

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…