High-efficiency quantum Monte Carlo algorithm for extracting entanglement entropy in interacting fermion systems
Weilun Jiang, Gaopei Pan, Zhe Wang, Bin-Bin Mao, Heng Shen, and Zheng Yan

TL;DR
This paper introduces a highly efficient quantum Monte Carlo algorithm for calculating entanglement entropy in interacting fermion systems, enabling detailed analysis of phase transitions and critical behavior with improved computational performance.
Contribution
The paper presents a novel fermionic quantum Monte Carlo algorithm based on incremental techniques that significantly enhances efficiency in entanglement entropy calculations for fermion systems.
Findings
Validated the algorithm on the 2D Hubbard model
Mapped the phase diagram including Fermi surface and Goldstone modes
Analyzed entanglement entropy behavior at Gross-Neveu criticality
Abstract
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 () is much higher than that of spin/boson (). Here, is the total number of sites and 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…
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Taxonomy
TopicsQuantum many-body systems
