7 citations · 16 across the 8 of their papers we have counts for
10 papers · 1 filter
Learning to Reconstruct Wigner Functions in Phase Space
Xinyu Tang, Yi-hsin Lin, Yan Zhu +5
Wigner function learning is a central tool for characterizing continuous variable quantum systems. A fundamental challenge in this setting is to infer a continuous phase-space func…
Foundation Model for Unified Characterization of Optical Quantum States
Xiaoting Gao, Yan Zhu, Feng-Xiao Sun +2
Machine learning methods have been used to infer specific properties of limited families of optical quantum states, but a unified model that predicts a broad range of properties fo…
Artificial intelligence for representing and characterizing quantum systems
Yuxuan Du, Yan Zhu, Yuan-Hang Zhang +8
Efficient characterization of large-scale quantum systems, especially those produced by quantum analog simulators and megaquop quantum computers, poses a central challenge in quant…
Sequence-Model-Guided Measurement Selection for Quantum State Learning
Jiaxin Huang, Yan Zhu, Giulio Chiribella +1
Characterization of quantum systems from experimental data is a central problem in quantum science and technology. But which measurements should be used to gather data in the first…
Controlling Unknown Quantum States via Data-Driven State Representations
Yan Zhu, Tailong Xiao, Guihua Zeng +2
Accurate control of quantum states is crucial for quantum computing and other quantum technologies. In the basic scenario, the task is to steer a quantum system towards a target st…
Noise-Agnostic Quantum Error Mitigation with Data Augmented Neural Models
Manwen Liao, Yan Zhu, Giulio Chiribella +1
Quantum error mitigation, a data processing technique for recovering the statistics of target processes from their noisy version, is a crucial task for near-term quantum technologi…