Center for Advanced Mathematics in Energy Research Applications, Computational Research Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA.
Acta Crystallogr D Struct Biol. 2020 Aug 1;76(Pt 8):736-750. doi: 10.1107/S2059798320008372. Epub 2020 Jul 27.
Intensity-based likelihood functions in crystallographic applications have the potential to enhance the quality of structures derived from marginal diffraction data. Their usage, however, is complicated by the ability to efficiently compute these target functions. Here, a numerical quadrature is developed that allows the rapid evaluation of intensity-based likelihood functions in crystallographic applications. By using a sequence of change-of-variable transformations, including a nonlinear domain-compression operation, an accurate, robust and efficient quadrature is constructed. The approach is flexible and can incorporate different noise models with relative ease.
基于强度的似然函数在晶体学应用中具有提高从边缘衍射数据得出的结构质量的潜力。然而，由于能够有效地计算这些目标函数，它们的使用变得复杂。这里开发了一种数值求积法，允许在晶体学应用中快速评估基于强度的似然函数。通过使用一系列变量变换，包括非线性域压缩操作，构建了一个准确、鲁棒和高效的求积法。该方法具有灵活性，可以相对容易地结合不同的噪声模型。
