Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”
Comment on “Pushing the frontiers of density functionals by solving the fractional electron problem”
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对“通过解决分数电子问题推动密度泛函的前沿”的评论
作者：
Igor S. Gerasimov;Timofey V. Losev;Evgeny Yu Epifanov;Irina Rudenko;I. Bushmarinov;Alexander A Ryabov;P. Zhilyaev;M. Medvedev
柯克帕特里克等人。 （报告，2021 年 12 月 9 日，第 1385 页）在分数电荷 (FC) 和分数自旋 (FS) 系统上训练了基于神经网络的 DFT 函数 DM21，他们声称它对于表现出强相关性的化学系统具有出色的准确性。在这里，我们证明 DM21 概括此类系统行为的能力并不来自已发布的结果，需要重新审视。描述
Kirkpatrick et al. (Reports, 9 December 2021, p. 1385) trained a neural network–based DFT functional, DM21, on fractional-charge (FC) and fractional-spin (FS) systems, and they claim that it has outstanding accuracy for chemical systems exhibiting strong correlation. Here, we show that the ability of DM21 to generalize the behavior of such systems does not follow from the published results and requires revisiting. Description