ICONS 2019 Paper Abstract

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Paper ThPSTPos.10

Hu, Zhilin (University of Science and Technology of China), Li, Kezhi (Imperial College), Cong, Shuang (University of Science and Technology of China), Tang, Yaru (University of Science and Technology of China)

Reconstructing Pure 14-Qubit Quantum States in Three Hours Using Compressive Sensing

Scheduled for presentation during the Regular Session "Poster session" (ThPSTPos), Thursday, August 22, 2019, 14:30−15:30,

5th IFAC International Conference on Intelligent Control and Automation Sciences, August 21-23, 2019, Queen’s University Belfast, Northern Ireland

This information is tentative and subject to change. Compiled on November 29, 2021

Keywords Modeling and identification, Signal processing, Biotechnology

Abstract

Reconstructing high-dimensional quantum state accurately with noise is a challenging problem, because of the probabilistic measurements of quantum states and the exponential growth of the computation in terms of the number of qubits. In this paper, an improved Alternating Direction Multiplier Method (ADMM) is proposed for the quantum state estimation based on the lower limit of the measurement rate inferred by Compressive Sensing (CS) theory. The proposed algorithm solves the density matrix correlation subproblems by introducing a proximal gradient step to avoid large-scale matrix inversion. Furthermore, it reduces the computational complexity by changing the order of operations. The algorithm we proposed can dramatically reduces the reconstruction time on the premise of achieving high reconstruction accuracy. When the number of qubits n=14 and sampling rate eta=0.0819%, it takes about 3 hours to reconstruct the density matrix of a pure quantum state with the reconstruction error of 4.97e-2 and fidelity of 98.79%

 

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