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arXiv 2409.12704quant-phcond-mat.stat-mechhep-thphysics.comp-ph
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拓扑序的高效计算

Efficient computation of topological order

Louis Fraatz, Amit Jamadagni, Hendrik Weimer

AI总结:

本文对比拓扑纠缠熵与基于纠错的拓扑序检测方法,证明后者具有多项式扩展优势,并在环面码变体模型中成功计算相图,可推广到高维及非平衡量子模拟实验。

摘要:

我们分析了在量子多体系统中检测拓扑序的计算方面问题。我们将广泛使用的拓扑纠缠熵与最近引入的基于纠错性质的拓扑序操作性定义进行对比,发现前者随系统规模呈指数级扩展,而后者呈多项式级扩展。我们以具有移动粒子的典型环面码模型的一个变体为例展示了我们的方法,发现纠错方法能够处理显著更大的系统规模。特别是,该模型的相图可以通过纠错成功计算,而拓扑纠缠熵受有限尺寸效应限制过于严重,无法获得确定性结果。虽然我们主要关注基态可以用矩阵乘积态表示的一维系统,但我们的策略可以容易地推广到更高维度和非平衡系统,甚至允许在当前量子模拟实验中高效检测拓扑序。

英文摘要:

We analyze the computational aspects of detecting topological order in a quantum many-body system. We contrast the widely used topological entanglement entropy with a recently introduced operational definition for topological order based on error correction properties, finding exponential scaling with the system size for the former and polynomial scaling for the latter. We exemplify our approach for a variant of the paradigmatic toric code model with mobile particles, finding that the error correction method allows to treat substantially larger system sizes. In particular, the phase diagram of the model can be successfully computed using error correction, while the topological entanglement entropy is too severely limited by finite size effects to obtain conclusive results. While we mainly focus on one-dimensional systems whose ground states can be expressed in terms of matrix product states, our strategy can be readily generalized to higher dimensions and systems out of equilibrium, even allowing for an efficient detection of topological order in current quantum simulation experiments.

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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