12 papers
Quantum memory advantage for quantum process tomography
Carlos Bravo-Prieto, Weiyuan Gong, Antonio Anna Mele
Quantum process tomography, the task of learning an unknown quantum channel from black-box access, is a central problem in quantum information. In this setting, protocols with quan…
The log log jam in Gaussian state tomography
Sitan Chen, Weiyuan Gong, Qi Ye +1
Unlike in finite dimensions, quantum information in continuous-variable systems has the peculiar feature that without imposing physical constraints, the sample complexity of state…
Learning and Generating Mixed States Prepared by Shallow Channel Circuits
Fangjun Hu, Christian Kokail, Milan Kornjača +5
Learning quantum states from measurement data is a central problem in quantum information and computational complexity. In this work, we study the problem of learning to generate m…
Ansatz-Free Learning of Lindbladian Dynamics In Situ
Petr Ivashkov, Nikita Romanov, Weiyuan Gong +3
Characterizing the dynamics of open quantum systems at the level of microscopic interactions and error mechanisms is essential for calibrating quantum hardware, designing robust si…
Instance-optimal high-precision shadow tomography with few-copy measurements: A metrological approach
Senrui Chen, Weiyuan Gong, Sisi Zhou
We study the sample complexity of shadow tomography in the high-precision regime under realistic measurement constraints. Given an unknown -dimensional quantum state and a k…
Noisy Quantum Learning Theory
Jordan Cotler, Weiyuan Gong, Ishaan Kannan
We develop a framework for learning from noisy quantum experiments in which fault-tolerant devices access uncharacterized systems through noisy couplings. Introducing the complexit…