The application of quantum algorithms has attracted much attention as it holds the promise of solving practical problems that are intractable to classical algorithms. One such application is the recent development of a quantum-walk-based optimization algorithm approach to portfolio optimization under the modern portfolio theory framework. In this paper, we demonstrate an experimental realization of the alternating phase-shift and continuous-time quantum walk unitaries that underpin this quantum algorithm using optical networks and single photons. The experimental analysis confirms that the probability of states corresponding to high-quality solutions is efficiently amplified by increasing the number of phase-shift and quantum walk iterations. This work provides strong evidence for practical applications of quantum-walk-based algorithms such as financial portfolio optimization.

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基于量子行走的投资组合优化的实验实施

量子算法的应用引起了广泛关注，因为它有望解决经典算法难以解决的实际问题。其中一个应用是最近开发的基于量子行走的优化算法方法，用于现代投资组合理论框架下的投资组合优化。在本文中，我们展示了交替相移和连续时间量子行走酉的实验实现，它支持使用光网络和单光子的量子算法。实验分析证实，通过增加相移和量子行走迭代的次数，可以有效放大高质量解对应的状态概率。这项工作为基于量子行走的算法（例如金融投资组合优化）的实际应用提供了强有力的证据。