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优化器性能在变量量子自溶解器中的比较研究
1Beijing National Laboratory for Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
The Journal of chemical physics
|December 16, 2025
概括
经典优化器对于变量量子自溶解器 (VQE) 计算至关重要. 基于梯度的方法通常优于其他方法,威尔方法显示出减轻量子计算中荒的高原问题的承诺.
科学领域:
- 量子计算是一种量子计算.
- 计算化学的计算化学
- 量子算法 量子算法 量子算法
背景情况:
- 变量量子Eigensolver (VQE) 是复杂问题的领先量子算法.
- 经典优化器对于VQE的预期值估计至关重要.
- 量子电路中的优化器性能仍未得到充分探索.
研究的目的:
- 在VQE框架内评估和比较12个经典优化器的性能.
- 了解优化器选择如何影响各种系统大小和电路深度的VQE融合.
- 为了确定优化器,可以有效地应对挑战,如荒的高原问题.
主要方法:
- 对12个不同的经典优化器进行系统的比较.
- 用不同的量子位数和电路深度进行了VQE计算.
- 在不同的初始猜测和测量计数中分析了趋同.
主要成果:
- 基于梯度的优化器通常与没有导数的方法相比显示出更高的收率.
- 使用随机过程的优化人员经常无法找到全球最小值.
- 优化器的步骤长度显著影响了趋同,威尔方法表明了缓解荒高原的潜力.
结论:
- 优化器的选择对于高效的VQE性能至关重要.
- 推基于梯度的方法用于VQE,并仔细调整步骤长度.
- 威尔方法成为增强VQE可扩展性和克服荒高原的有希望的候选者.
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