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20072026
most citedModels and algorithms for the next generation of glass transition studies

339 citations · 2.3k across the 38 of their papers we have counts for

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25 papers · 1 filter

cond-mat.stat-mech2025

Interpretability of linear regression models of glassy dynamics

Anand Sharma, Chen Liu, Misaki Ozawa +1

Data-driven models can accurately describe and predict the dynamical properties of glass-forming liquids from structural data. Accurate predictions, however, do not guarantee an un…

cond-mat.stat-mech2024

Glassy dynamics and crystalline local order in two-dimensional amorphous silica

Marco Dirindin, Daniele Coslovich

We reassess the modeling of amorphous silica bilayers as a two-dimensional classical system whose particles interact with an effective pairwise potential. We show that it is possib…

cond-mat.stat-mech2022★ 37 cited

Dimensionality reduction of local structure in glassy binary mixtures

Daniele Coslovich, Robert L. Jack, Joris Paret

We consider unsupervised learning methods for characterizing the disordered microscopic structure of supercooled liquids and glasses. Specifically, we perform dimensionality reduct…

cond-mat.stat-mech2022★ 4 cited

Revisiting the single-saddle model for the -relaxation of supercooled liquids

Daniele Coslovich, Atsushi Ikeda

The dynamics of glass-forming liquids display several outstanding features, such as two-step relaxation and dynamic heterogeneities, which are difficult to predict quantitatively f…

cond-mat.stat-mech2020★ 9 cited

Spatial structure of unstable normal modes in a glass-forming liquid

Masanari Shimada, Daniele Coslovich, Hideyuki Mizuno +1

The phenomenology of glass-forming liquids is often described in terms of their underlying, high-dimensional potential energy surface. In particular, the statistics of stationary p…

cond-mat.stat-mech2020★ 72 cited

Assessing the structural heterogeneity of supercooled liquids through community inference

Joris Paret, Robert L. Jack, Daniele Coslovich

We present an information-theoretic approach inspired by distributional clustering to assess the structural heterogeneity of particulate systems. Our method identifies communities…