6 papers
Non-Markovian Noise Suppression Simplified through Channel Representation
Zhenhuan Liu, Yunlong Xiao, Zhenyu Cai
Non-Markovian noise, arising from memory effects in the environment, poses substantial challenges to conventional quantum noise suppression protocols, including quantum error corre…
No Universal Purification in Quantum Mechanics
Zhenhuan Liu, Zhenyu Du, Jens Eisert +2
Many central tasks in fundamental physics and quantum information processing are possible only insofar as mixed quantum states can be made purer. In this work, we prove that the li…
Exponential speedup in measurement property learning with post-measurement states
Zhenhuan Liu, Qi Ye, Zhenyu Cai +1
Learning properties of quantum states and channels is known to benefit from resources such as entangled operations, auxiliary qubits, and adaptivity, whereas the resource structure…
Experimental Quantum Channel Purification
Yue-Yang Fei, Zhenhuan Liu, Rui Zhang +7
Quantum networks, which integrate multiple quantum computers and the channels connecting them, are crucial for distributed quantum information processing but remain inherently susc…
Exponential Separations between Quantum Learning with and without Purification
Zhenhuan Liu, Weiyuan Gong, Zhenyu Du +1
In quantum learning tasks, quantum memory can offer exponential reductions in statistical complexity compared to any single-copy strategies, but this typically necessitates at leas…
Virtual Channel Purification
Zhenhuan Liu, Xingjian Zhang, Yue-Yang Fei +1
Quantum error mitigation is a key approach for extracting target state properties on state-of-the-art noisy machines and early fault-tolerant devices. Using the ideas from flag fau…