Journal
PHYSICAL REVIEW A
Volume 101, Issue 3, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevA.101.032321
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Funding
- Ministry of Science and Technology of China [2016YFA0302104, 2016YFA0300600]
- National Natural Science Foundation of China [11934018, 11774406, 11774398]
- National Training Program of Innovation for Undergraduates
- Chinese Academy of Sciences [XDB28000000]
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We propose a quantum tomography scheme for pure qudit systems which adopts a certain version of random basis measurements and a generative learning method, along with a built-in fidelity estimation approach to assess the reliability of the tomographic states. We prove the validity of the scheme theoretically, and we perform numerically simulated experiments on several target states that have compact matrix product state representation, demonstrating its efficiency and robustness. We find the number of replicas required by a fixed fidelity criterion grows only linearly as the system size scales up, which saturates a lower bound from information theory. Thus the scheme achieves the highest possible scalability that is crucial for practical quantum state tomography.
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