The precursor of the critical transitions in majority vote model with the noise feedback from the vote layer

IF 2.2 3区 物理与天体物理 Q2 MECHANICS Journal of Statistical Mechanics: Theory and Experiment Pub Date : 2024-08-15 DOI:10.1088/1742-5468/ad6426
Wei Liu, Jincheng Wang, Fangfang Wang, Kai Qi, Zengru Di
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Abstract

In this paper, we investigate phase transitions in the majority-vote model coupled with noise layers of different structures. We examine the square lattice and random-regular networks, as well as their combinations, for both vote layers and noise layers. Our findings reveal the presence of independent third-order transitions in all cases and dependent third-order transitions when critical transitions occur. This suggests that dependent third-order transitions may serve as precursors to critical transitions in non-equilibrium systems. Furthermore, we observe that when the structure of vote layers is decentralized, the coupling between the vote layer and the noise layer leads to the absence of critical phenomena.
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多数票模型中的临界转换前兆,以及来自投票层的噪声反馈
在本文中,我们研究了与不同结构的噪声层相结合的多数票模型中的相变。我们研究了方格网络和随机规则网络,以及它们在投票层和噪声层的组合。我们的研究结果表明,在所有情况下都存在独立三阶转换,而在发生临界转换时则存在从属三阶转换。这表明,在非平衡系统中,从属三阶转换可能是临界转换的前兆。此外,我们还观察到,当投票层结构分散时,投票层和噪声层之间的耦合会导致临界现象的缺失。
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来源期刊
CiteScore
4.50
自引率
12.50%
发文量
210
审稿时长
1.0 months
期刊介绍: JSTAT is targeted to a broad community interested in different aspects of statistical physics, which are roughly defined by the fields represented in the conferences called ''Statistical Physics''. Submissions from experimentalists working on all the topics which have some ''connection to statistical physics are also strongly encouraged. The journal covers different topics which correspond to the following keyword sections. 1. Quantum statistical physics, condensed matter, integrable systems Scientific Directors: Eduardo Fradkin and Giuseppe Mussardo 2. Classical statistical mechanics, equilibrium and non-equilibrium Scientific Directors: David Mukamel, Matteo Marsili and Giuseppe Mussardo 3. Disordered systems, classical and quantum Scientific Directors: Eduardo Fradkin and Riccardo Zecchina 4. Interdisciplinary statistical mechanics Scientific Directors: Matteo Marsili and Riccardo Zecchina 5. Biological modelling and information Scientific Directors: Matteo Marsili, William Bialek and Riccardo Zecchina
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