6 papers
Enhancing classical simulation with noisy quantum devices
Ruiqi Zhang, Fuchuan Wei, Zhaohui Wei
As quantum devices continue to improve in scale and precision, a central challenge is how to effectively utilize noisy hardware for meaningful computation. Most existing approaches…
A Unified Frequency Principle for Quantum and Classical Machine Learning
Rundi Lu, Ruiqi Zhang, Weikang Li +3
Quantum neural networks constitute a key class of near-term quantum learning models, yet their training dynamics remain not fully understood. Here, we present a unified theoretical…
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…
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…
Clifford Perturbation Approximation for Quantum Error Mitigation
Ruiqi Zhang, Yuguo Shao, Fuchuan Wei +3
Quantum error mitigation (QEM) is critical for harnessing the potential of near-term quantum devices. Particularly, QEM protocols can be designed based on machine learning, where t…
Detecting unfaithful entanglement by multiple fidelities
Ruiqi Zhang, Zhaohui Wei
Certifying entanglement for unknown quantum states experimentally is a fundamental problem in quantum computing and quantum physics. Because of being easy to implement, a most popu…