用克里福德电路增强密度矩阵重正化群

IF 8.1 1区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY
Xiangjian Qian, Jiale Huang, Mingpu Qin
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引用次数: 0

摘要

密度矩阵重正化群(DMRG)被公认为是求解一维量子多体系统的高效而精确的方法。然而,由于底层波函数解析(即矩阵乘积态)中编码的纠缠有限,将 DMRG 直接应用于二维系统的研究遇到了挑战。相反,克利福德电路为模拟具有大量纠缠力的状态提供了一条大有可为的途径,尽管这种状态仅限于稳定器状态。在这项研究中,我们利用克利福德电路和 DMRG 的优势,将克利福德电路无缝集成到 DMRG 算法中。这种集成大大提高了仿真精度,而额外的计算成本却很小。此外,这一框架不仅在当前应用中非常有用,而且还可以轻松地适用于其他各种数值方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Augmenting Density Matrix Renormalization Group with Clifford Circuits
The density matrix renormalization group (DMRG) is widely acknowledged as a highly effective and accurate method for solving one-dimensional quantum many-body systems. However, the direct application of DMRG to the study of two-dimensional systems encounters challenges due to the limited entanglement encoded in the underlying wave-function Ansatz, known as the matrix product state. Conversely, Clifford circuits offer a promising avenue for simulating states with substantial entanglement, albeit confined to stabilizer states. In this work, we present the seamless integration of Clifford circuits within the DMRG algorithm, leveraging the advantages of both Clifford circuits and DMRG. This integration leads to a significant enhancement in simulation accuracy with small additional computational cost. Moreover, this framework is useful not only for its current application but also for its potential to be easily adapted to various other numerical approaches.
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来源期刊
Physical review letters
Physical review letters 物理-物理:综合
CiteScore
16.50
自引率
7.00%
发文量
2673
审稿时长
2.2 months
期刊介绍: Physical review letters(PRL)covers the full range of applied, fundamental, and interdisciplinary physics research topics: General physics, including statistical and quantum mechanics and quantum information Gravitation, astrophysics, and cosmology Elementary particles and fields Nuclear physics Atomic, molecular, and optical physics Nonlinear dynamics, fluid dynamics, and classical optics Plasma and beam physics Condensed matter and materials physics Polymers, soft matter, biological, climate and interdisciplinary physics, including networks
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