• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

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.

DOI:10.1103/PhysRevE.105.064803
PMID:35854512
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。

相似文献

1
Height distributions in interface growth: The role of the averaging process.界面生长中的高度分布:平均过程的作用。
Phys Rev E. 2022 Jun;105(6-1):064803. doi: 10.1103/PhysRevE.105.064803.
2
Kardar-Parisi-Zhang growth on square domains that enlarge nonlinearly in time.在随时间非线性扩展的方形区域上的 Kardar-Parisi-Zhang 增长。
Phys Rev E. 2022 May;105(5-1):054804. doi: 10.1103/PhysRevE.105.054804.
3
Geometry dependence in linear interface growth.线性界面生长中的几何依赖性。
Phys Rev E. 2019 Oct;100(4-1):042107. doi: 10.1103/PhysRevE.100.042107.
4
One-point height fluctuations and two-point correlators of (2+1) cylindrical KPZ systems.(2 + 1) 圆柱型KPZ系统的单点高度涨落与两点关联函数
Phys Rev E. 2023 Jun;107(6-1):064140. doi: 10.1103/PhysRevE.107.064140.
5
Circular Kardar-Parisi-Zhang interfaces evolving out of the plane.从平面演化而来的圆形 Kardar-Parisi-Zhang 界面。
Phys Rev E. 2019 Mar;99(3-1):032140. doi: 10.1103/PhysRevE.99.032140.
6
Width and extremal height distributions of fluctuating interfaces with window boundary conditions.具有窗口边界条件的涨落界面的宽度和极值高度分布。
Phys Rev E. 2016 Jan;93(1):012801. doi: 10.1103/PhysRevE.93.012801. Epub 2016 Jan 7.
7
Dimensional crossover in Kardar-Parisi-Zhang growth.Kardar-Parisi-Zhang生长中的维度交叉
Phys Rev E. 2024 Apr;109(4):L042102. doi: 10.1103/PhysRevE.109.L042102.
8
Universal fluctuations in Kardar-Parisi-Zhang growth on one-dimensional flat substrates.一维平坦基底上 Kardar-Parisi-Zhang 生长的普遍涨落
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jan;85(1 Pt 1):010601. doi: 10.1103/PhysRevE.85.010601. Epub 2012 Jan 18.
9
Universality and dependence on initial conditions in the class of the nonlinear molecular beam epitaxy equation.非线性分子束外延方程类中的普遍性及对初始条件的依赖性。
Phys Rev E. 2016 Nov;94(5-1):050801. doi: 10.1103/PhysRevE.94.050801. Epub 2016 Nov 28.
10
Kardar-Parisi-Zhang universality class in (2+1) dimensions: universal geometry-dependent distributions and finite-time corrections.二维加一维空间中的 Kardar-Parisi-Zhang 普适类:依赖几何的普适分布和有限时间修正
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Apr;87(4):040102. doi: 10.1103/PhysRevE.87.040102. Epub 2013 Apr 22.