Multi-round QAOA and advanced mixers on a trapped-ion quantum computer
Multi-round QAOA and advanced mixers on a trapped-ion quantum computer
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DOI：
10.1088/2058-9565/ac91ef
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发表时间：
2022-01
影响因子：
6.7
通讯作者：
Yingyue Zhu;Zewen Zhang;Bhuvanesh Sundar;Alaina M. Green;C. Huerta Alderete;N. Nguyen;K. Hazzard;N. Linke
中科院分区：
文献类型：
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作者：
Yingyue Zhu;Zewen Zhang;Bhuvanesh Sundar;Alaina M. Green;C. Huerta Alderete;N. Nguyen;K. Hazzard;N. Linke
图上的组合优化问题在科学和工程中具有广泛的应用。量子近似优化算法（QAOA）是一种通过应用多轮变分电路在量子计算机上解决这些问题的方法。然而，存在一些挑战限制了 QAOA 在现实世界问题中的应用。在本文中，我们在俘获离子量子计算机上证明了 QAOA 结果随着多个任意图上多个问题的轮数而提高。我们还演示了一种先进的混合哈密顿量，它允许对具有预定权重的所有最佳解决方案进行采样。我们的结果是将量子算法应用于现实世界问题的一步。
Combinatorial optimization problems on graphs have broad applications in science and engineering. The quantum approximate optimization algorithm (QAOA) is a method to solve these problems on a quantum computer by applying multiple rounds of variational circuits. However, there exist several challenges limiting the application of QAOA to real-world problems. In this paper, we demonstrate on a trapped-ion quantum computer that QAOA results improve with the number of rounds for multiple problems on several arbitrary graphs. We also demonstrate an advanced mixing Hamiltonian that allows sampling of all optimal solutions with predetermined weights. Our results are a step toward applying quantum algorithms to real-world problems.