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arXiv 2602.02460cond-mat.stat-mech
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二维铁磁性自旋-3/2伊辛模型的解法:通过簇生长方法

Resolution of the Two-Dimensional Ferromagnetic Spin-3/2 Ising Model via Cluster Growth

Universidade Federal do Amazonas(亚马孙联邦大学)

J. Roberto Viana, Octavio D. Rodriguez Salmon, Minos A. Neto, Griffith Mendonça, F. Dinóla Neto

AI总结:

通过分层簇生长方法,高效解决二维铁磁性自旋-3/2伊辛模型,再现关键实验特征并计算熵值。

摘要:

我们提出了一种基于分层簇生长过程的计算方法,以高效地解决自旋-3/2伊辛模型。该方法通过迭代构建大小为$N_g$的有限磁性簇,从而避免了配分函数的指数复杂度($4^{N}$)。在生成$g+1$的站点有效自旋状态由生成$g$的簇的局部磁化决定。这种方法与有效场理论有共同的概念基础,允许研究实际上非常大的系统大小$N = N_0 (N_g)^{g}$。我们将该形式应用于在蜂窝晶格上的铁磁性自旋-3/2伊辛模型,模拟单层CrI$_3$,这是一个典型的二维伊辛磁体。该模型通过实验转变温度($T_{c} \simeq 45$ K)进行校准,成功再现了关键的实验特征:磁化率$m(T)$的温度依赖性,包括其拐点,以及比热$ c_v(T) $的宽峰。我们还计算了熵$s(T)$,发现低温下的残余值与系统的双重简并性一致。我们的结果表明,这种分层簇方法为研究复杂磁性系统提供了一个定量准确且计算高效的框架。

英文摘要:

We propose a computational methodology based on a hierarchical cluster growth process to solve spin-3/2 Ising models efficiently. The method circumvents the exponential complexity (\(4^{N}\)) of the canonical ensemble partition function by iteratively constructing finite magnetic clusters of size \(N_g\), where the effective spin state of a site in generation \(g+1\) is determined by the local magnetization of a cluster from generation \(g\). This approach, which shares conceptual ground with effective field theories, allows the study of systems of effectively very large size \(N = N_0 (N_g)^{g}\). We apply the formalism to the ferromagnetic spin-3/2 Ising model on a honeycomb lattice, modeling the monolayer CrI$_3$, a prototypical two-dimensional Ising magnet. The model, calibrated using the experimental transition temperature (\(T_{c} \simeq 45\) K), successfully reproduces key experimental features: the temperature dependence of the magnetization \(m(T)\), including its inflection point, and the broadened peak in the specific heat \(c_v(T)\). We also compute the entropy \(s(T)\), finding a finite residual value at low temperatures consistent with the system's double degeneracy. Our results demonstrate that this hierarchical cluster method provides a quantitatively accurate and computationally efficient framework for studying complex magnetic systems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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