文件夹
计算机科学
量子
量子行走
数学优化
安萨茨
量子算法
投资组合优化
比例(比率)
量子计算机
操作员(生物学)
算法
数学
物理
量子力学
经济
财务
生物化学
化学
抑制因子
转录因子
数学物理
基因
作者
N. Slate,Edric Matwiejew,S. Marsh,Jingbo Wang
出处
期刊:Quantum
[Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften]
日期:2021-07-28
卷期号:5: 513-513
被引量:39
标识
DOI:10.22331/q-2021-07-28-513
摘要
This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near-term noisy intermediate-scale quantum computers. Recent work by Hodson et al. (2019) explored potential application of hybrid quantum-classical algorithms to the problem of financial portfolio rebalancing. In particular, they deal with the portfolio optimisation problem using the Quantum Approximate Optimisation Algorithm and the Quantum Alternating Operator Ansatz. In this paper, we demonstrate substantially better performance using a newly developed Quantum Walk Optimisation Algorithm in finding high-quality solutions to the portfolio optimisation problem.
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