Experimental implementation of quantum-walk-based portfolio optimization
Dengke Qu, Edric Matwiejew, Kunkun Wang, Jingbo B. Wang, Peng Xue
Beijing Computational Science Research Center The University of Western Australia
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摘要与影响
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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计算机 / AIQuantum Computing Algorithms and Architecture
Quantum Information and Cryptography · Quantum Mechanics and Applications
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