Bipartite reweight-annealing algorithm to extract large-scale data of entanglement entropy and its derivative in high precision

• URL: http://arxiv.org/abs/2406.05324v5
• Date: Wed, 20 Nov 2024 07:06:26 GMT
• Title: Bipartite reweight-annealing algorithm to extract large-scale data of entanglement entropy and its derivative in high precision
• Authors: Zhe Wang, Zhiyan Wang, Yi-Ming Ding, Bin-Bin Mao, Zheng Yan,
• Abstract summary: We propose a quantum Monte Carlo (QMC) scheme able to extract large-scale data of entanglement entropy (EE) and its derivative. We show the feasibility of using EE and its derivative to find phase transition points and to probe novel phases.
• Score: 5.671578795886005
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a quantum Monte Carlo (QMC) scheme able to extract large-scale data of entanglement entropy (EE) and its derivative with high precision and low technical barrier. We avoid directly computing the overlap of two partition functions within different spacetime manifolds and instead obtain them separately via reweight-annealing scheme. The incremental process can be designed along the path of real physical parameters in this frame, and all intermediates are EEs of corresponding parameters, so the algorithm efficiency is improved by more than $10^4$ of times. The calculation of EE becomes much cheaper and simpler. It opens a way to numerically detect the novel phases and phase transitions by scanning EE in a wide parameter-region in two and higher dimensional systems. We then show the feasibility of using EE and its derivative to find phase transition points and to probe novel phases.

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