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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.

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  • 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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