美国北卡罗莱纳州立大学A. F. Kemper团队实现了使用特征向量延拓制备更便宜、更抗噪声的量子态。相关论文发表在2025年3月10日出版的《物理评论A》杂志上。

子空间方法是一种强大的、抗噪声的方法，可以在量子计算机上有效地制备基态。挑战在于使用最少的量子资源获得一个条件数较小的子空间，该子空间跨越了感兴趣的状态。在这项工作中，研究组将使用特征向量延拓从一组哈密顿量的低态构建一个子空间。基向量是使用标准状态制备方法的截断版本制备的，如虚时间演化（ITE）、绝热状态制备（ASP）和变分量子本征求解器。通过将这些截断方法与特征向量延拓相结合，可直接对其进行改进，以较低的成本获得更精确的基态能量。

研究组使用几个自旋系统来证明收敛性，即使在ITE和ASP等方法失败的情况下，例如存在平交点的ASP和能量间隙消失的ITE。他们还展示了这种方法的噪声弹性，超越了通过使用较浅的量子电路已经取得的成果。该研究结果表明，特征向量延拓可用于在短期内改进现有的状态准备方法。

附：英文原文

Title: Cheaper and more noise-resilient quantum state preparation using eigenvector continuation

Author: Anjali A. Agrawal, Joo C. Getelina, Akhil Francis, A. F. Kemper

Issue&Volume: 2025/03/10

Abstract: Subspace methods are powerful, noise-resilient methods that can effectively prepare ground states on quantum computers. The challenge is to get a subspace with a small condition number that spans the states of interest using minimal quantum resources. In this work, we will use eigenvector continuation to build a subspace from the low-lying states of a set of Hamiltonians. The basis vectors are prepared using truncated versions of standard state preparation methods such as imaginary-time evolution (ITE), adiabatic state preparation (ASP), and variational quantum eigensolver. By using these truncated methods combined with eigenvector continuation, we can directly improve upon them, obtaining more accurate ground-state energies at a reduced cost. We use several spin systems to demonstrate convergence even when methods like ITE and ASP fail, such as ASP in the presence of level crossings and ITE with vanishing energy gaps. We also showcase the noise resilience of this approach beyond the gains already made by having shallower quantum circuits. Our findings suggest that eigenvector continuation can be used to improve existing state preparation methods in the near term.

DOI: 10.1103/PhysRevA.111.032607

Source: https://journals.aps.org/pra/abstract/10.1103/PhysRevA.111.032607