发表机构
Dokuz Eylül University; Karabük University; Presidency University（德古塞九月大学; 卡拉布克大学; 总统大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
通过大规模蒙特卡洛模拟，发现随机键无序显著削弱三态Potts模型的临界慢化，动态指数从0.54降至0.24，但静态普适类不变，且可观测量缺乏自平均性。
AI 中文摘要
我们利用Wolff和Swendsen--Wang簇算法进行大规模蒙特卡洛模拟，研究二维随机键三态Potts模型的动态临界行为。在依赖于无序的临界温度下，我们计算了积分和指数自相关时间，并通过有限尺寸标度提取了动态临界指数$z$。键无序显著削弱了临界慢化，动态指数从纯系统中的$z \approx 0.54$降至强无序下的$z \approx 0.24$。通过对Wolff簇尺寸的有限尺寸标度，我们得到$\gamma/\nu \approx 1.73$，其中$\gamma$和$\nu$分别是磁化率和关联长度指数，这与二维三态Potts模型的普适类一致。这些结果表明，键无序强烈影响临界动力学，但底层静态普适类保持不变。此外，包括比热和自相关时间在内的静态和动态可观测量均表现出缺乏自平均性。
英文摘要
We study the dynamic critical behavior of the two-dimensional random-bond three-state Potts model using large-scale Monte Carlo simulations with the Wolff and Swendsen--Wang cluster algorithms. At the disorder-dependent critical temperature, we compute integrated and exponential autocorrelation times and extract the dynamic critical exponent $z$ via finite-size scaling. Critical slowing down is significantly weakened by bond randomness, with the dynamic exponent decreasing from $z \approx 0.54$ in the pure system to $z \approx 0.24$ at strong disorder. From the finite-size scaling of the Wolff cluster size, we obtain $γ/ν\approx 1.73$, where $γ$ and $ν$ are the susceptibility and correlation-length exponents, respectively, consistent with the universality class of the two-dimensional three-state Potts model. These results indicate that bond randomness strongly affects the critical dynamics but leaves the underlying static universality class unchanged. Furthermore, both static and dynamic observables, including the specific heat and the autocorrelation times, show a lack of self-averaging.
Comments17 pages, 6 figures
Journal refPhysical Review E, 114, 034102 (2026)
