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Trapped Ion Quantum Computing
Quantum state tomography with disentanglement algorithm
arXiv
Authors: Juan Yao
Year
2023
Paper ID
53990
Status
Preprint
Abstract Read
~2 min
Abstract Words
121
Citations
N/A
Abstract
In this work, we report on a novel quantum state reconstruction process based on the disentanglement algorithm. Using variational quantum circuits, we disentangle the quantum state to a product of computational zero states. Inverse evolution of the zero states reconstructs the quantum state up to an overall phase. By sequentially disentangling the qubit one by one, we reduce the required measurements with only single qubit measurement. Demonstrations with our proposal for the reconstruction of the random states are presented where variational quantum circuit is optimized by disentangling process. To facilitate experimental implementation, we also employ reinforcement learning for quantum circuit design with limited discrete quantum gates. Our method is universal and imposes no specific ansatz or constrain on the quantum state.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2023 reference point for readers tracking recent quantum research.
- In this work, we report on a novel quantum state reconstruction process based on the disentanglement algorithm.
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