Machine learning glass caging order parameters with an artificial nested neural network
文献类型：期刊论文
| 作者 | Zhang, Kaihua; Li, Xinyang3,4; Jin, Yuliang1,3,4 ; Jiang, Ying5
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| 刊名 | SOFT MATTER
 |
| 出版日期 | 2022 |
| 卷号 | 18期号:33页码:6270-6277 |
| 关键词 | LIQUIDS TRANSITIONS |
| ISSN号 | 1744-683X |
| DOI | 10.1039/d2sm00310d |
| 英文摘要 | Around a glass transition, the dynamics of a supercooled liquid dramatically slow down, exhibited by caging of particles, while the structural changes remain subtle. Alternative to recent machine learning studies searching for structural predictors of glassy dynamics, here we propose to learn directly particle caging features defined purely according to dynamics. We focus on three transitions in a simulated hard sphere glass model, the melting of ultra-stable glasses, the Gardner transition and the liquid to ordinary glass transition. Implementing the machine learning algorithm based on a two-level nested neural network, we attain not only appropriate caging order parameters for all three transitions, but also a phase classification for input samples. A finite-size scaling analysis of the phase classification results identifies the order of melting (first) and Gardner (second) transitions. A false positive is avoided, as the liquid to glass transition is indicated as a crossover, rather than a phase transition with a well-defined transition point. This study paves the way to a generic approach for learning dynamical features in glassy systems, with a minimum requirement of system-specific knowledge. |
| 学科主题 | Chemistry ; Materials Science ; Physics ; Polymer Science |
| 语种 | 英语 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/27790]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China 2.Beihang Univ, Ctr Soft Matter Phys & Its Applicat, Beijing 100191, Peoples R China 3.Beihang Univ, Sch Chem, Beijing 100191, Peoples R China 4.Chinese Acad Sci, Inst Theoret Phys, CAS Key Lab Theoret Phys, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Wenzhou Inst, Wenzhou 325000, Zhejiang, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Kaihua,Li, Xinyang,Jin, Yuliang,et al. Machine learning glass caging order parameters with an artificial nested neural network[J]. SOFT MATTER,2022,18(33):6270-6277. |
| APA | Zhang, Kaihua,Li, Xinyang,Jin, Yuliang,&Jiang, Ying.(2022).Machine learning glass caging order parameters with an artificial nested neural network.SOFT MATTER,18(33),6270-6277. |
| MLA | Zhang, Kaihua,et al."Machine learning glass caging order parameters with an artificial nested neural network".SOFT MATTER 18.33(2022):6270-6277. |
入库方式： OAI收割
来源：理论物理研究所
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