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arXiv 2603.02011cond-mat.str-elcond-mat.mes-hallcond-mat.mtrl-sciphysics.comp-phquant-ph
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张量网络方法用于超过十亿个站点的超摩尔 exciton

Tensor-network methodology for real-space super-moiré excitons

Aalto University(阿尔托大学);Utrecht University(乌得勒支大学)

Anouar Moustaj, Yitao Sun, Tiago V. C. Antão, Lumen Eek, Jose L. Lado

AI总结:

本文提出了一种张量网络方法,用于计算超摩尔系统中超过十亿个站点的激发能谱,展示了激子子带形成和摩尔诱导的空间限制。

摘要:

在准晶体和超摩尔系统中计算激发态能谱是一个巨大的挑战,因为激发态希尔伯特空间的规模异常庞大。在这里,我们展示了一种张量网络方法,用于实空间的贝瑟-萨尔佩特哈密顿量,使我们能够访问一个具有10^18维的哈密顿量的能谱,并使我们能够直接计算超过十亿个晶格站点的束缚激发能谱函数,其能力远远超过传统方法。我们的方法结合了实空间贝瑟-萨尔佩特哈密顿量的张量网络编码与切比雪夫张量网络算法。这种策略避免了显式存储哈密顿量,同时在广泛不同的长度尺度上保持完整的实空间分辨率。我们为一维和二维超摩尔系统演示了我们的方法,实现了在十亿规模系统中激发态能谱中原子和介观结构的同时分辨率,展示了激子子带的形成和摩尔诱导的空间限制。我们的结果建立了一种实空间方法,使模拟大规模准晶体和超摩尔量子物质中的激发物理成为可能。

英文摘要:

Computing excitonic spectra in quasicrystal and super-moiré systems constitutes a formidable challenge due to the exceptional size of the excitonic Hilbert space. Here, we demonstrate a tensor-network method for the real-space Bethe-Salpeter Hamiltonian, allowing us to access the spectra of an excitonic $10^{18}$-dimensional Hamiltonian, and enabling the direct computation of bound-exciton spectral functions for systems exceeding one billion lattice sites, several orders of magnitude beyond the capabilities of conventional approaches. Our method combines a tensor-network encoding of the real-space Bethe-Salpeter Hamiltonian with a Chebyshev tensor network algorithm. This strategy bypasses explicit storage of the Hamiltonian while preserving full real-space resolution across widely different length scales. We demonstrate our methodology for one- and two-dimensional super-moiré systems, achieving the simultaneous resolution of atomistic and mesoscopic structures in the excitonic spectra in billion-size systems, showing exciton miniband formation and moiré-induced spatial confinement. Our results establish a real-space methodology enabling the simulation of excitonic physics in large-scale quasicrystal and super-moiré quantum matter.

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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