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arXiv 2603.06286quant-ph
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稳定子基态及其在量子模拟中的应用

The stabilizer ground state and applications to quantum simulation

School of Science, Huzhou University(湖州学院理学院);New York University Shanghai(纽约大学上海分校;纽约大学上海NYU-ECNU物理研究所);NYU-ECNU Institute of Physics at NYU Shanghai(华东师范大学物理与材料科学学院精密光谱科学国家重点实验室);State Key Laboratory of Precision Spectroscopy, School of Physical and Material Sciences, East China Normal University(纽约大学阿布扎比分校NYUAD研究院量子与拓扑系统中心);Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, New York University Abu Dhabi(纽约大学物理系);Department of Physics, New York University

Yuping Mao, Chang Chen, Jiaxing Feng, Yimeng Mao, Tim Byrnes

AI总结:

本文提出通过最优稳定子基态近似真实基态,并利用遗传算法和稳定子表格形式实现高效量子模拟。

摘要:

稳定子基态被定义为相对于给定哈密顿量的最低能量稳定子态。在许多情况下,它高度简并且不给出唯一的稳定子态。我们定义最优稳定子基态为具有最高保真度的稳定子基态。这在量子模拟中很有用,因为它允许用克莱因电路近似基态,可以进一步细化到真实的基态。我们展示了如何评估最优稳定子基态。我们展示了该状态在测量基确定性虚时间演化的应用中,能够以高效率收敛到基态。通过经典选择最优稳定子生成器群并运用稳定子表格形式,该方法可以以最大保真度准备相应的稳定子基态。识别和细化该生成器群是通过针对目标哈密顿量结构定制的遗传算法进行的。复杂性分析进一步表明,该算法的量子资源成本与系统规模成多项式关系,突显了其高效性和潜在的量子优势。

英文摘要:

The stabilizer ground state is defined is the lowest energy stabilizer state with respect to a given Hamiltonian. In many cases it is highly degenerate and does not give a unique stabilizer state. We define the optimal stabilizer ground state as the stabilizer ground state which has the highest fidelity with the true ground state. This is useful in quantum simulation contexts as it allows for a Clifford circuit approximation of a ground state that can be further refined towards the true ground state. We show how the optimal stabilizer ground state may be evaluated. We show applications of this state in the context of measurement-based deterministic imaginary time evolution (MITE), which converges to the ground state with high efficiency. By classically selecting the optimal stabilizer generator group and employing the stabilizer tableaux formalism, the method prepares the corresponding stabilizer ground state with maximal fidelity. The identification and refinement of this generator group are performed using a genetic algorithm tailored to the structure of the target Hamiltonian. The complexity analysis further demonstrates that algorithm's quantum resource cost scales polynomially with system size, highlighting its high efficiency and potential quantum advantage.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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