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Robust quantum state transfer by optimal invariant-based reverse engineering

delete2022-10-28
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OA
AI
C
Chun‐Ling Zhang
陈祥 封面图
陈祥 (Xiang Chen)
S
Shuang-Juan Shen
X
Xiu‐Min Lin *
DOI:10.1364/OE.472909delete
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摘要

摘要

En 中文
Shortening the operation time of implementing scheme and reducing the influence of harmful factors have always been the research objectives pursued by people. Based on invariantbased reverse engineering, we present a general scheme for implementing robust population transfer in a three-level system via optimal shortcut to adiabatic passage. The systematic error sensitivity is introduced to measure the robustness of the process. The smooth Rabi frequencies are expressed with some coefficients, which are also related to the systematic error sensitivity and the population of intermediate state. When the amplitude of control field is given, the transfer can be optimized within as small systematic error sensitivity as possible, i.e., the robustness against systematic errors is further improved by choosing suitable correlation coefficient. Additionally, we apply the technique to achieve robust excitation fluctuation transfer between two membranes in an optomechanical system. The relation between the fidelity of excitation fluctuation transfer and variation of effective optomechanical coupling strengths is analysed. Numerical result shows that the fidelity keeps over 0.95 even if the coupling strengths deviates from 20% of the theoretical value. Moreover, comparison with existing literature [Opt. Express 29, 7998 (2021)], the proposed scheme possesses stronger robustness against variations of effective optomechanical coupling strengths and lower population of unwanted states. The idea may provide a promising approach for quantum information processing. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
Keyword:
COHERENT POPULATION TRANSFER
ADIABATIC PASSAGE
OSCILLATOR

期刊

Optics Express 封面图
Optics Express
IF:
3.3
论文数:
6.1W
被引数:
14.3W

机构

F
Fujian Normal University
学者数:
1.2W
论文数: 8.0K
被引数: 1.3W
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