A computational method is presented which is capable to obtain low lying energy structures of topological amorphous systems. The method merges a differential mutation genetic algorithm with simulated annealing. This is done by incorporating a thermal selection criterion, which makes it possible to reliably obtain low lying minima with just a small population size and is suitable for multimodal structural optimization. The method is tested on the structural optimization of amorphous graphene from unbiased atomic starting configurations. With just a population size of six systems, energetically very low structures are obtained. While each of the structures represents a distinctly different arrangement of the atoms, their properties, such as energy, distribution of rings, radial distribution function, coordination number, and distribution of bond angles, are very similar.

中文翻译：

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用于大原子系统结构优化的热驱动差分突变方法

提出了一种能够获得拓扑非晶系统低能结构的计算方法。该方法将差分突变遗传算法与模拟退火融合在一起。这可以通过合并热选择标准来完成，该选择标准可以仅以较小的人口规模可靠地获得低洼的最小值，并且适用于多峰结构优化。通过无偏原子起始构型对无定形石墨烯的结构优化进行了测试。仅用六个系统的人口规模，就可以获得在能量上非常低的结构。虽然每个结构都代表一个截然不同的原子排列，但是它们的性质（例如能量，环的分布，径向分布函数，配位数，