通过资历驱动的操作员选择来有效地准备量子状态
Dipanjali Halder1, Dibyendu Mondal1, Rahul Maitra1,2
1Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India.
The Journal of chemical physics
|October 15, 2025
概括
这项研究引入了一种新的量子算法框架,以准确地代表强相关系统中的电子状态. 该方法通过最小化前电路测量来提高近期量子硬件的计算效率和准确性.
科学领域:
- 量子计算是一种量子计算.
- 计算化学计算化学
- 强烈相关的系统 强烈相关的系统
背景情况:
- 准确的电子状态表示对于量子算法至关重要,特别是对于强相关系系统.
- 现有的方法在平衡化学精度与门效率方面面临挑战,并且通常需要广泛的前电路测量,从而导致效率低下.
- 对于这些系统来说,电子波函数的近似仍然是一个重要的理论障碍.
研究的目的:
- 开发一个算法框架,有效地捕捉分子强相关性.
- 为了最大限度地减少量子计算中的前电路测量开销.
- 提高量子算法的准确性,稳定性和资源效率,用于近期量子硬件上强烈相关的系统.
主要方法:
- 提出一个参数化的Ansatz使用排名一和资历零对联激发为浅门深度.
- 通过混合方法实现刺激的选择性修剪,将化学洞察力和能量分类优化结合起来.
- 通过粒子保护交换电路结合基于量子比特的激发来减少量子复杂性.
主要成果:
- 动态的Ansatz显著提高了强烈相关的系统的计算效率.
- 这种方法提供了极高的准确性和稳定性,即使在杂的量子环境中.
- 证明了量子复杂性的减少和提高资源效率.
结论:
- 拟议的框架为量子计算中的化学精度和门效率的挑战提供了协同解决方案.
- 这种方法为准确和高效的强相关系系统量子模拟提供了可行的途径.
- 动态的Ansatz显示出在杂的近期量子设备上的实际应用的前景.
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