量子差异的比较研究 对于旅行销售员问题的近似优化算法
Wenyang Qian1,2, Robert A M Basili3, Mary Mehrnoosh Eshaghian-Wilner4
1Instituto Galego de Fisica de Altas Enerxias (IGFAE), Universidade de Santiago de Compostela, E-15782 Santiago de Compostela, Spain.
Entropy (Basel, Switzerland)
|August 26, 2023
概括
本研究探讨了在量子模拟器上使用量子近似优化算法 (QAOA) 的旅行销售员问题 (TSP). 一个平衡的QAOA混合器设计显示出在量子计算机上解决复杂的优化问题的希望.
科学领域:
- 量子计算是一种量子计算.
- 计算复杂性 计算复杂性
- 优化算法 优化算法
背景情况:
- 旅行销售员问题 (TSP) 是一个基准的NP-hard问题,经常用于评估量子计算范式.
- 在量子计算机上研究TSP对于理解量子算法在复杂的优化任务中的潜力至关重要.
研究的目的:
- 研究量子近似优化算法 (QAOA) 的应用,以解决旅行销售员问题 (TSP).
- 评估基于网关的量子模拟器上的不同QAOA混合器设计和优化策略.
- 评估数字量子模拟的可行性,以找到最佳的TSP解决方案.
主要方法:
- 制定了旅行销售员问题 (TSP) 作为量子计算的优化问题.
- 在QAOA框架内采用了改进的量子位编码策略和层级学习优化协议.
- 在基于网关的数字量子模拟器上进行了数字模拟,用于3,4和5个城市的TSP实例.
主要成果:
- 根据数值准确性和优化成本评估了三种不同的QAOA混合器设计的性能.
- 确定一个平衡的QAOA混合器设计表明了基于网关的模拟器和未来量子设备的优越潜力.
- 观察到噪声模型模拟支持平衡混合机设计的有效性.
结论:
- 使用问题启发式模拟器的数字量子模拟是解决旅行销售员问题 (TSP) 的可行方法.
- 选择QAOA混合器设计显著影响模拟性能和准确性.
- 建议在量子硬件上的实际应用中使用平衡的QAOA混合器设计.
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