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quant-ph2026

Quantum neural network equipped with backpropagation on a qudit processor

Yibo Yuan, Zhuoyue Xu, Zhenyue Du +7

Quantum neural networks (QNNs), one of the fundamental algorithms in quantum machine learning, have been widely used in classification and identification tasks. However, the capabi…

quant-ph2026

Low-Depth Random Unitaries without Ancillae

Zhenyu Du, Siyuan Cheng, Xiongfeng Ma

Random unitaries are fundamental to quantum information and many-body physics, with widespread applications ranging from quantum learning and metrology to device benchmarking. A ce…

quant-ph2026

Quantum-classical crossover in fault-tolerant quantum dynamics simulation

Jinzhao Sun, Bozhen Zhou, Jue Xu +28

While quantum computers promise to solve classically intractable problems, identifying the point at which fault-tolerant quantum computation outperforms the best classical algorith…

quant-ph2026

No Cloning of Quantum Ensembles

Zhenyu Du, Siyuan Cheng, Qi Zhao +2

Modern quantum physics now enables control of quantum systems at the level of individual trajectories, opening a new frontier that links quantum information theory, quantum many-bo…

quant-ph2026

Complexity-driven transitions in quantum observation

Zhenyu Du, Siyuan Cheng, Han Ye +3

Observing the physical world is a foundational pursuit in science. In the quantum realm, however, observation necessitates a fundamental quantum-to-classical conversion: destructiv…

quant-ph2026

Scalable self-testing of generic multipartite quantum states

Jinchang Liu, Elias X. Huber, Zhenyu Du +2

Characterizing large quantum systems with minimal assumptions is a central challenge in quantum information science. Self-testing provides the strongest form of certification by id…