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界面生长中的高度分布:平均过程的作用。

Height distributions in interface growth: The role of the averaging process.

作者信息

Oliveira Tiago J

机构信息

Departamento de Física, Universidade Federal de Viçosa, 36570-900, Viçosa, Minas Gerais, Brazil.

出版信息

Phys Rev E. 2022 Jun;105(6-1):064803. doi: 10.1103/PhysRevE.105.064803.

Abstract

Height distributions (HDs) are key quantities to uncover universality and geometry-dependence in evolving interfaces. To quantitatively characterize HDs, one uses adimensional ratios of their first central moments (m_{n}) or cumulants (κ_{n}), especially the skewness S and kurtosis K, whose accurate estimate demands an averaging over all L^{d} points of the height profile at a given time, in translation-invariant interfaces, and over N independent samples. One way of doing this is by calculating m_{n}(t) [or κ_{n}(t)] for each sample and then carrying out an average of them for the N interfaces, with S and K being calculated only at the end. Another approach consists in directly calculating the ratios for each interface and, then, averaging the N values. It turns out, however, that S and K for the growth regime HDs display strong finite-size and -time effects when estimated from these "interface statistics," as already observed in some previous works and clearly shown here, through extensive simulations of several discrete growth models belonging to the EW and KPZ classes on one- and two-dimensional substrates of sizes L=const. and L∼t. Importantly, I demonstrate that with "1-point statistics," i.e., by calculating m_{n}(t) [or κ_{n}(t)] once for all NL^{d} heights together, these corrections become very weak, so that S and K attain values very close to the asymptotic ones already at short times and for small L's. However, I find that this "1-point" (1-pt) approach fails in uncovering the universality of the HDs in the steady-state regime (SSR) of systems whose average height, h[over ¯], is a fluctuating variable. In fact, as demonstrated here, in this regime the 1-pt height evolves as h(t)=hover ¯+s_{λ}A^{1/2}L^{α}ζ+⋯-where P(ζ) is the underlying SSR HD-and the fluctuations in h[over ¯] yield S_{1-pt}∼t^{-1/2} and K_{1-pt}∼t^{-1}. Nonetheless, by analyzing P(h-h[over ¯]), the cumulants of P(ζ) can be accurately determined. I also show that different, but universal, asymptotic values for S and K (related, so, to different HDs) can be found from the "interface statistics" in the SSR. This reveals the importance of employing the various complementary approaches to reliably determine the universality class of a given system through its different HDs.

摘要

高度分布(HDs)是揭示演化界面中的普遍性和几何依赖性的关键量。为了定量表征HDs,人们使用其第一中心矩((m_n))或累积量((\kappa_n))的无量纲比,特别是偏度(S)和峰度(K),其准确估计需要在给定时间对高度轮廓的所有(L^d)个点进行平均,在平移不变界面中,以及对(N)个独立样本进行平均。一种方法是为每个样本计算(m_n(t)) [或(\kappa_n(t))],然后对(N)个界面进行平均,仅在最后计算(S)和(K)。另一种方法是直接为每个界面计算这些比率,然后对(N)个值进行平均。然而,事实证明,从这些“界面统计”估计增长阶段HDs的(S)和(K)时,会显示出强烈的有限尺寸和时间效应,正如之前一些工作中已经观察到的,并且在此通过对属于EW和KPZ类的几个离散增长模型在尺寸为(L = const)和(L\sim t)的一维和二维衬底上进行广泛模拟清楚地表明了这一点。重要的是,我证明了通过“单点统计”,即一次性为所有(NL^d)个高度计算(m_n(t)) [或(\kappa_n(t))],这些修正变得非常微弱,因此(S)和(K)在短时间和小(L)时就已经非常接近渐近值。然而,我发现这种“单点”(1-pt)方法在揭示平均高度(\overline{h})是波动变量的系统的稳态区域(SSR)中HDs的普遍性方面失败了。事实上,正如在此所证明的,在这个区域中,单点高度的演化形式为(h(t)=\overline{h}(t)+s_{\lambda}A^{1/2}L^{\alpha}\zeta+\cdots),其中(P(\zeta))是潜在的SSR HD,并且(\overline{h})中的波动导致(S_{1-pt}\sim t^{-1/2})和(K_{1-pt}\sim t^{-1})。尽管如此,通过分析(P(h - \overline{h})),可以准确确定(P(\zeta))的累积量。我还表明,从SSR中的“界面统计”可以找到(S)和(K)的不同但普遍的渐近值(因此与不同的HDs相关)。这揭示了采用各种互补方法通过给定系统的不同HDs可靠地确定其普遍性类别的重要性。

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