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A generalized Newton iteration for computing the solution of the inverse Henderson problem
Applied Mathematics in Science and Engineering ( IF 1.9 ) Pub Date : 2020-01-16 , DOI: 10.1080/17415977.2019.1710504
Fabrice Delbary 1 , Martin Hanke 1 , Dmitry Ivanizki 1
Affiliation  

ABSTRACT We develop a generalized Newton scheme called IHNC (inverse hypernetted-chain iteration) for the construction of effective pair potentials for systems of interacting point-like particles. The construction is realized in such a way that the distribution of the particles matches a given radial distribution function. The IHNC iteration uses the hypernetted-chain integral equation for an approximate evaluation of the inverse of the Jacobian of the forward operator. In contrast to the full Newton method realized in the Inverse Monte Carlo (IMC) scheme, the IHNC algorithm requires only a single molecular dynamics computation of the radial distribution function per iteration step and no further expensive cross-correlations. Numerical experiments are shown to demonstrate that the method is as efficient as the IMC scheme, and that it easily allows to incorporate thermodynamical constraints.

中文翻译:

用于计算逆亨德森问题的解的广义牛顿迭代

摘要 我们开发了一种称为 IHNC(逆超网状链迭代)的广义牛顿方案,用于为相互作用的点状粒子系统构建有效的对势。该结构以粒子的分布与给定的径向分布函数相匹配的方式实现。IHNC 迭代使用超网状链积分方程来近似评估前向算子的雅可比矩阵的倒数。与在逆蒙特卡罗 (IMC) 方案中实现的完整牛顿法相比,IHNC 算法只需要对每个迭代步骤的径向分布函数进行单个分子动力学计算,无需进一步昂贵的互相关。数值实验表明,该方法与 IMC 方案一样有效,
更新日期:2020-01-16
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