利用无监督机器学习方法识别二维复杂等离子体中的熔化线

Hu-Sheng Li , He Huang , Wei Yang , Cheng-Ran Du
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引用次数: 0

摘要

机器学习方法已广泛应用于复杂等离子体的研究。本文基于朗之万动力学仿真结果,证明了无监督卷积神经网络可以应用于二维复杂等离子体的熔点计算。训练样本不需要标记。所得到的熔化线与六阶参数分析和监督机器学习方法得到的结果一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of the melting line in the two-dimensional complex plasmas using an unsupervised machine learning method

Machine learning methods have been widely used in the investigations of the complex plasmas. In this paper, we demonstrate that the unsupervised convolutional neural network can be applied to obtain the melting line in the two-dimensional complex plasmas based on the Langevin dynamics simulation results. The training samples do not need to be labeled. The resulting melting line coincides with those obtained by the analysis of hexatic order parameter and supervised machine learning method.

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