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arXiv · 2208.08261

Stochastic learning control of adiabatic speedup in a non-Markovian open qutrit system

Yang-Yang Xie·Feng-Hua Ren·Run-Hong He·Arapat Ablimit·Zhao-Ming Wang
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Abstract

Precise and efficient control of quantum systems is essential to perform quantum information processing tasks. In terms of adiabatic speedup via leakage elimination operator approach, for a closed system, the ideal pulse control conditions have been theoretically derived by P-Q partitioning technique. However, it is a challenge to design the corresponding control pulses for an open system, which requires to tackle noisy environments. In this paper, we apply the stochastic search procedures to an open qutrit system and successfully obtain the optimal control pulses for significant adiabatic speedup. The calculation results show that these optimal pulses allow us to acquire higher fidelities than the ideal pulses. The improvement of fidelity is large for relatively strong system-bath coupling strength and high bath temperature. For certain coupling strength and bath temperature, the maximal improvement can be achieved for a critical characteristic frequency which represents the memory time of the environment. Our investigation indicates that the stochastic search procedures are powerful tools to design control pulses for combating the detrimental effects of the environment.

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Yang-Yang Xie, Feng-Hua Ren, Run-Hong He, Arapat Ablimit, Zhao-Ming Wang. 2022-08-17. Stochastic learning control of adiabatic speedup in a non-Markovian open qutrit system. https://doi.org/10.1103/physreva.106.062612

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