经典优化器和Ansatz深度对噪音设备中QAOA性能的影响
Aidan Pellow-Jarman1,2, Shane McFarthing1,3, Ilya Sinayskiy4,5
1Qunova Computing Inc, Daejeon, 34051, South Korea.
Scientific reports
|July 11, 2024
概括
噪音对量子近似优化算法 (QAOA) 有重大影响. 像Adam和AMSGrad这样的某些优化器在射击或真实噪音下表现最好,并且最佳电路深度对于噪音大的量子设备的性能至关重要.
科学领域:
- 量子计算是一种量子计算.
- 组合优化的优化.
- 算法性能分析 算法性能分析
背景情况:
- 量子近似优化算法 (QAOA) 是NISQ设备的关键变量算法,旨在进行组合优化.
- QAOA采用混合量子-经典方法,使用量子电路和经典优化器来最大限度地降低成本.
研究的目的:
- 调查现实噪声对QAOA经典优化器的影响.
- 在噪音条件下确定QAOA的最佳电路深度.
主要方法:
- 在不同噪声模型下对经典优化器 (Adam,AMSGrad,SPSA) 的比较分析 (状态矢量模拟,射击噪声,真实噪声).
- 在5量子比特系统上对具有不同电路深度 (层) 的最小顶点覆盖问题的QAOA性能评估.
主要成果:
- 亚当和AMSGrad优化器在有射击噪声的情况下表现出卓越的性能.
- 在真实的噪音条件下,SPSA,Adam和AMSGrad的表现最高.
- 解决最小顶点覆盖问题的解决质量提高到大约六个QAOA层,然后退化.
结论:
- 在杂的量子环境中,经典优化器的选择对于QAOA性能至关重要.
- 增加QAOA电路深度超出最佳点可以降低噪音硬件上的解决方案质量.
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