Melting phenomena of self-organized magnetic structures investigated by variational autoencoder

IF 7.2 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
H.G. Yoon , D.B. Lee , S.M. Park , J.W. Choi , H.Y. Kwon , C. Won
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引用次数: 0

Abstract

The phase transition phenomenon is an important research topic in various physical studies. However, it is difficult to define the order parameters in many complex systems involving self-organized structures. We propose a method to define order parameters using a variational autoencoder network. To demonstrate these capabilities, we trained a deep learning network with a dataset composed of spin configurations in a chiral magnetic system at various temperatures. It removes thermal fluctuations from the input data and leaves the remaining structural information with a spin magnitude. We define an order parameter with magnitude of output spins and compare the results with those of conventional analysis. The comparison indicates similar results. Using the order parameter, the thermal properties of the chiral magnetic system were investigated by varying the physical parameters and data size.

利用变异自动编码器研究自组织磁性结构的熔化现象
相变现象是各种物理研究中的一个重要课题。然而,在许多涉及自组织结构的复杂系统中,很难定义阶次参数。我们提出了一种利用变异自动编码器网络定义阶次参数的方法。为了展示这些能力,我们用一个由不同温度下手性磁性系统中的自旋配置组成的数据集训练了一个深度学习网络。它消除了输入数据中的热波动,留下了带有自旋幅度的剩余结构信息。我们用输出自旋的大小定义了一个阶次参数,并将结果与传统分析进行了比较。比较结果表明两者类似。利用阶次参数,通过改变物理参数和数据大小,研究了手性磁性系统的热特性。
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来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
期刊介绍: The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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