Uncertainty quantification for classical effective potentials: an extension to potfit
Uncertainty quantification for classical effective potentials: an extension to potfit
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经典有效势的不确定性量化：potfit 的扩展
DOI：
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发表时间：
2018
影响因子：
1.8
通讯作者：
P. Brommer
中科院分区：
文献类型：
--
作者：
S. Longbottom;P. Brommer
有效势是经典分子动力学（MD）模拟的重要组成部分。用一个包含少得多的参数的有效势场或力场来表示原子构型的复杂能量图景，其结果人们知之甚少。概率势系综方法已在potfit力匹配程序中实现。这将不确定性量化引入原子间势产生过程。有效势的不确定性通过MD传播，以获得感兴趣的数量（QoI）的不确定性，这是模型预测的置信度的度量。我们证明了技术，使用三个潜在的镍：两个简单的对电位，Lennard-Jones和莫尔斯，和一个本地密度依赖嵌入原子方法的潜力。一个潜在的合奏适合密度泛函理论（DFT）的参考数据构建每个潜在的晶格常数，弹性常数和热膨胀计算的不确定性。我们定量地说明了不良的模型选择和拟合的情况下，突出了计算量的不确定性。这表明，我们的方法可以捕捉到的潜在的生成过程中产生的QoI的误差的影响，而不诉诸与实验或DFT，这是一个重要的部分，以评估MD模拟的预测能力进行比较。
Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. Little is understood of the consequences of representing the complex energy landscape of an atomic configuration by an effective potential or force field containing considerably fewer parameters. The probabilistic potential ensemble method has been implemented in the potfit force matching code. This introduces uncertainty quantification into the interatomic potential generation process. Uncertainties in the effective potential are propagated through MD to obtain uncertainties in quantities of interest (QoI), which are a measure of the confidence in the model predictions. We demonstrate the technique using three potentials for nickel: two simple pair potentials, Lennard-Jones and Morse, and a local density dependent embedded atom method potential. A potential ensemble fit to density functional theory (DFT) reference data is constructed for each potential to calculate the uncertainties in lattice constants, elastic constants and thermal expansion. We quantitatively illustrate the cases of poor model selection and fit, highlighted by the uncertainties in the quantities calculated. This shows that our method can capture the effects of the error incurred in QoI resulting from the potential generation process without resorting to comparison with experiment or DFT, which is an essential part to assess the predictive power of MD simulations.
密度泛函理论中具有不确定性量化能力的交换相关函数的开发
影响因子：
4.1
作者：
Aldegunde M
通讯作者：
Aldegunde M