发表机构
Michigan State University; University of Oslo（密歇根州立大学; 奥斯陆大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种受成核启发的数字量子态制备方法，通过小晶格基态和Trotter化绝热增长制备大晶格态，并引入变分优化，在二维Ising模型上优于现有方法。
AI 中文摘要
量子态制备对量子算法至关重要，改进的态制备方法可以将资源需求降低数个数量级。在本工作中，我们提出一种受成核现象启发的、用于数字量子计算机上晶格哈密顿量的态制备方法。在我们的方法中，首先在量子线路中制备一个小尺寸晶格哈密顿量的精确基态，然后通过Trotter化的绝热演化执行一系列增长阶段，将晶格尺寸增大到目标模型。利用绝热定理和Trotter误差界，我们给出了成核方法制备具有期望保真度的初始态所需的总演化时间和Trotter步数的充分条件。此外，我们引入了优化成核方法，该方法在成核结构之上考虑变分优化。对于二维Ising模型，我们展示了优化成核方法可以优于当前数字量子计算机上领先的态制备方法。
英文摘要
Quantum state preparation is crucial for quantum algorithms, and improved state preparation methods can reduce resource requirements by orders of magnitude. In this work, we introduce a state preparation method for lattice Hamiltonians on digital quantum computers inspired by nucleation. In our method, the exact ground state of a small lattice Hamiltonian is prepared in a quantum circuit, then a series of growth stages are performed via Trotterized adiabatic evolution to increase the size of the lattice to the desired model. Using the adiabatic theorem and Trotter error bounds, we provide sufficient conditions on the total evolution time and number of Trotter steps required for nucleation to prepare an initial state with desired fidelity. In addition, we introduce optimized nucleation which considers variational optimization on top of the nucleation structure. For a two-dimensional Ising model, we show that optimized nucleation can outperform a current leading method for state preparation on digital quantum computers.
Comments10 pages, 7 figures
