对具有时间相关噪声的表面生长进行的广泛数值模拟。
Extensive numerical simulations of surface growth with temporally correlated noise.
作者信息
Song Tianshu, Xia Hui
机构信息
School of Materials Science and Physics, China University of Mining and Technology, Xuzhou 221116, China.
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China.
出版信息
Phys Rev E. 2021 Jan;103(1-1):012121. doi: 10.1103/PhysRevE.103.012121.
Surface growth processes can be significantly affected by long-range temporal correlations. In this work, we perform extensive numerical simulations of a (1+1)- and (2+1)-dimensional ballistic deposition (BD) model driven by temporally correlated noise, which is regarded as the temporal correlated Kardar-Parisi-Zhang universality class. Our results are compared with the existing theoretical predictions and numerical simulations. When the temporal correlation exponent is above a certain threshold, BD surfaces develop gradually faceted patterns. We find that the temporal correlated BD system displays nontrivial dynamic properties, and the characteristic roughness exponents satisfy α≃α_{loc}<α_{s} in (1+1) dimensions, which is beyond the existing dynamic scaling classifications.
表面生长过程会受到长程时间相关性的显著影响。在这项工作中，我们对由时间相关噪声驱动的（1 + 1）维和（2 + 1）维弹道沉积（BD）模型进行了广泛的数值模拟，该模型被视为时间相关的 Kardar-Parisi-Zhang 普适类。我们的结果与现有的理论预测和数值模拟进行了比较。当时间相关指数高于某个阈值时，BD 表面会逐渐形成多面体形貌。我们发现时间相关的 BD 系统表现出非平凡的动力学性质，并且在（1 + 1）维中特征粗糙度指数满足α≃α_loc < α_s，这超出了现有的动态标度分类。
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