论文标题
通过数量级来扩展非晶材料的晶格动力学
Scaling up the lattice dynamics of amorphous materials by orders of magnitude
论文作者
论文摘要
我们将粘弹性的非植入理论推广到与任意化学复杂性的大型，更采样的系统一起使用。 Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic resolution, we propose an extension of the Kernel Polynomial Method (KPM) for the computation of the vibrational density of states (VDOS) and the eigenmodes, including the $Γ$-correlator of the affine force-field, which is a key ingredient of lattice-dynamic calculations of viscoelasticity.我们表明，结果很好地融合到通过Hessian（动力学）矩阵的直接对角线化（DD）获得的溶液。众所周知，DD方法对$ n = 10^4 $原子或更大的系统的计算要求非常高。取而代之的是，此处开发的毕马威（KPM）方法允许人们对真实材料的晶格动态计算，最高$ 10^6 $原子，并具有$ n $的计算时间和内存消耗的更有利的（线性）缩放。
We generalise the non-affine theory of viscoelasticity for use with large, well-sampled systems of arbitrary chemical complexity. Having in mind predictions of mechanical and vibrational properties of amorphous systems with atomistic resolution, we propose an extension of the Kernel Polynomial Method (KPM) for the computation of the vibrational density of states (VDOS) and the eigenmodes, including the $Γ$-correlator of the affine force-field, which is a key ingredient of lattice-dynamic calculations of viscoelasticity. We show that the results converge well to the solution obtained by direct diagonalization (DD) of the Hessian (dynamical) matrix. As is well known, the DD approach has prohibitively high computational requirements for systems with $N=10^4$ atoms or larger. Instead, the KPM approach developed here allows one to scale up lattice dynamic calculations of real materials up to $10^6$ atoms, with a hugely more favorable (linear) scaling of computation time and memory consumption with $N$.
