arXiv Open Access 2024

Selecting Relevant Structural Features for Glassy Dynamics by Information Imbalance

Anand Sharma Chen Liu Misaki Ozawa

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Abstrak

We investigate numerically the identification of relevant structural features that contribute to the dynamical heterogeneity in a model glass-forming liquid. By employing the recently proposed information imbalance technique, we select these features from a range of physically motivated descriptors. This selection process is performed in a supervised manner (using both dynamical and structural data) and an unsupervised manner (using only structural data). We then apply the selected features to predict future dynamics using a machine learning technique. Finally, we discuss the potential applications of this approach in identifying the dominant mechanisms governing the glassy slow dynamics.

Topik & Kata Kunci

cond-mat.soft cond-mat.dis-nn

Penulis (3)

Anand Sharma

Chen Liu

Misaki Ozawa

Format Sitasi

APA MLA BibTeX

Sharma, A., Liu, C., Ozawa, M. (2024). Selecting Relevant Structural Features for Glassy Dynamics by Information Imbalance. https://arxiv.org/abs/2408.12705

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓