Tensor network approach to momentum-resolved spectroscopy in non-periodic super-moir\'e systems
Anouar Moustaj, Yitao Sun, Tiago V. C. Ant\~ao, and Jose L. Lado

TL;DR
This paper introduces a tensor network methodology for calculating momentum-resolved spectral functions in large, non-periodic super-moiré systems, enabling detailed analysis of their electronic structures at an atomistic level.
Contribution
The authors develop a novel tensor network approach that encodes large super-moiré problems as auxiliary quantum many-body problems, allowing efficient computation of spectral functions.
Findings
Successfully applied to 1D and 2D super-moiré systems.
Enabled imaging of position-dependent electronic structures and minigaps.
Applicable to systems with non-uniform strain and quasicrystalline patterns.
Abstract
Computing spectral functions in large, non-periodic super-moir\'e systems remains an open problem due to the exceptionally large system size that must be considered. Here, we establish a tensor network methodology that allows computing momentum-resolved spectral functions of non-interacting and interacting super-moir\'e systems at an atomistic level. Our methodology relies on encoding an exponentially large tight-binding problem as an auxiliary quantum many-body problem, solved with a many-body kernel polynomial tensor network algorithm combined with a quantum Fourier transform tensor network. We demonstrate the method for one and two-dimensional super-moir\'e systems, including super-moir\'e with non-uniform strain, interactions treated at the mean-field level, and quasicrystalline super-moir\'e patterns. Furthermore, we demonstrate that our methodology allows us to compute…
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