4 citations · 4 across the 6 of their papers we have counts for
6 papers · 1 filter
A Theory of Finite-Noise Optima and Generalization in Quantum Machine Learning
Ziyu Zhang, Zikang Jia, Xiaosong Li +1
Quantum noise is expected to degrade quantum machine learning by driving circuits away from their noiseless implementations. Yet recent studies show moderate noise can reduce testi…
Ensemble-Based Quantum Signal Processing for Error Mitigation
Suying Liu, Yulong Dong, Dong An +1
Despite rapid advances in quantum hardware, noise remains a central obstacle to deploying quantum algorithms on near-term devices. In particular, random coherent errors that accumu…
Rethinking Noise in Quantum Machine Learning: When Noise Improves Learning
Linghua Zhu, Yulong Dong, Ziyu Zhang +1
Quantum noise is conventionally viewed as a fundamental obstacle in near-term quantum computing, motivating extensive error correction and mitigation strategies. \REV{We present nu…
In Situ Quantum Analog Pulse Characterization via Structured Signal Processing
Yulong Dong, Christopher Kang, Murphy Yuezhen Niu
Analog quantum simulators can directly emulate time-dependent Hamiltonian dynamics, enabling the exploration of diverse physical phenomena such as phase transitions, quench dynamic…
Feedforward Quantum Singular Value Transformation
Yulong Dong, Dong An, Murphy Yuezhen Niu
In this paper, we introduce a major advancement in Quantum Singular Value Transformation (QSVT) through the development of Feedforward QSVT (FQSVT), a framework that significantly…
Optimal Low-Depth Quantum Signal-Processing Phase Estimation
Yulong Dong, Jonathan A. Gross, Murphy Yuezhen Niu
Quantum effects like entanglement and coherent amplification can be used to drastically enhance the accuracy of quantum parameter estimation beyond classical limits. However, chall…