High-efficiency quantum Monte Carlo algorithm for extracting entanglement entropy in interacting fermion systems

Fuente: arXiv
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Main Authors: Jiang, Weilun, Pan, Gaopei, Wang, Zhe, Mao, Bin-Bin, Shen, Heng, Yan, Zheng
Format: Preprint
Published: 2024
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author Jiang, Weilun
Pan, Gaopei
Wang, Zhe
Mao, Bin-Bin
Shen, Heng
Yan, Zheng
author_facet Jiang, Weilun
Pan, Gaopei
Wang, Zhe
Mao, Bin-Bin
Shen, Heng
Yan, Zheng
contents The entanglement entropy probing novel phases and phase transitions numerically via quantum Monte Carlo has made great achievements in large-scale interacting spin/boson systems. In contrast, the numerical exploration in interacting fermion systems is rare, even though fermion systems attract more attentions in condensed matter. The fundamental restrictions is that the computational cost of fermion quantum Monte Carlo ($\sim βN^3$) is much higher than that of spin/boson ($\sim βN$). Here, $N$ is the total number of sites and $β$ is the inverse temperature or projection length. To tackle this problem, we propose a fermionic quantum Monte Carlo algorithm based on the incremental technique along physical parameters, which greatly improves the efficiency of extracting entanglement entropy. We benchmark the developed algorithm by calculating the scaling behavior of the entanglement entropy in a two-dimensional square lattice Hubbard model. The obtained phase diagram including Fermi surface and Goldstone modes validates the correctness of the algorithm. Remarkably, our method shows the high-efficiency with respect to the existing algorithms, while keeping the high computation precision. We proceed to apply this algorithm to explore the scaling behavior of the entanglement entropy and particularly its derivative at Gross-Neveu criticality. Our results elucidate that such critical behavior can be quantified by the correlation length exponent.
format Preprint
id arxiv_https___arxiv_org_abs_2409_20009
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle High-efficiency quantum Monte Carlo algorithm for extracting entanglement entropy in interacting fermion systems
Jiang, Weilun
Pan, Gaopei
Wang, Zhe
Mao, Bin-Bin
Shen, Heng
Yan, Zheng
Statistical Mechanics
Strongly Correlated Electrons
Quantum Physics
The entanglement entropy probing novel phases and phase transitions numerically via quantum Monte Carlo has made great achievements in large-scale interacting spin/boson systems. In contrast, the numerical exploration in interacting fermion systems is rare, even though fermion systems attract more attentions in condensed matter. The fundamental restrictions is that the computational cost of fermion quantum Monte Carlo ($\sim βN^3$) is much higher than that of spin/boson ($\sim βN$). Here, $N$ is the total number of sites and $β$ is the inverse temperature or projection length. To tackle this problem, we propose a fermionic quantum Monte Carlo algorithm based on the incremental technique along physical parameters, which greatly improves the efficiency of extracting entanglement entropy. We benchmark the developed algorithm by calculating the scaling behavior of the entanglement entropy in a two-dimensional square lattice Hubbard model. The obtained phase diagram including Fermi surface and Goldstone modes validates the correctness of the algorithm. Remarkably, our method shows the high-efficiency with respect to the existing algorithms, while keeping the high computation precision. We proceed to apply this algorithm to explore the scaling behavior of the entanglement entropy and particularly its derivative at Gross-Neveu criticality. Our results elucidate that such critical behavior can be quantified by the correlation length exponent.
title High-efficiency quantum Monte Carlo algorithm for extracting entanglement entropy in interacting fermion systems
topic Statistical Mechanics
Strongly Correlated Electrons
Quantum Physics
url https://arxiv.org/abs/2409.20009