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Determining whether two graphs are structurally identical is a fundamental problem with applications spanning mathematics, computer science, chemistry, and network science. Despite decades of study, graph isomorphism remains a challenging…

Computational Physics · Physics 2026-04-10 Sara Najem , Amer E. Mouawad

A graph is a powerful concept for representation of relations between pairs of entities. Data with underlying graph structure can be found across many disciplines and there is a natural desire for understanding such data better. Deep…

Machine Learning · Computer Science 2019-01-25 Martin Simonovsky

The first goal of this article is to study the validity of the Zwanzig model for liquid crystals to predict transitions to inhomogeneous phases (like smectic and columnar) and the way polydispersity affects these transitions. The second…

Soft Condensed Matter · Physics 2009-11-10 Yuri Martinez-Raton , Jose A. Cuesta

Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of the fluid with the rock on the interfaces. Conventional high-fidelity numerical models…

Zeolites, as representative porous materials, possess intricate three-dimensional frameworks that endow them with high surface areas and remarkable catalytic properties. There are a few factors that give a huge influence on the catalytic…

Materials Science · Physics 2025-04-25 Enci Zhang , Zhuoya Dong , Xubin Han , Jianhua Zhang , Yanhang Ma , Huaidong Jiang

Graph diffusion models have emerged as state-of-the-art techniques in graph generation; yet, integrating domain knowledge into these models remains challenging. Domain knowledge is particularly important in real-world scenarios, where…

Machine Learning · Computer Science 2024-12-09 Manuel Madeira , Clement Vignac , Dorina Thanou , Pascal Frossard

The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially state-of-the-art diffusion models, offer the promise of modeling complex data…

We constructed a simple but effective model to predict the layered intergrowth structures by combining the self-assembly phenomenon in confined space and the sandwich configuration of layered materials. In this model, a two-dimensional…

Superconductivity · Physics 2022-04-06 Hao Jiang , HuiXiang Chen , GuangHan Cao

We demonstrate that graphs embedded on surfaces are a powerful and practical tool to generate, characterize and simulate networks with a broad range of properties. Remarkably, the study of topologically embedded graphs is non-restrictive…

Other Condensed Matter · Physics 2015-03-19 Tomaso Aste , Ruggero Gramatica , T. Di Matteo

We introduce a new model of indeterminacy in graphs: instead of specifying all the edges of the graph, the input contains all triples of vertices that form a connected subgraph. In general, different (labelled) graphs may have the same set…

Discrete Mathematics · Computer Science 2023-03-14 Paul Bastide , Linda Cook , Jeff Erickson , Carla Groenland , Marc van Kreveld , Isja Mannens , Jordi L. Vermeulen

Multiplex graphs, characterised by their layered structure, exhibit informative interdependencies within layers that are crucial for understanding complex network dynamics. Quantifying the interaction and shared information among these…

Statistics Theory · Mathematics 2024-05-24 Anda Skeja , Sofia C. Olhede

A permutation graph is a graph whose edges are given by inversions of a permutation. We study the Abelian sandpile model (ASM) on such graphs. We exhibit a bijection between recurrent configurations of the ASM on permutation graphs and the…

Combinatorics · Mathematics 2018-10-08 Mark Dukes , Thomas Selig , Jason P. Smith , Einar Steingrimsson

Much of our understanding of complex structures is based on simplification: for example, metal-organic frameworks are often discussed in the context of "nodes" and "linkers", allowing for a qualitative comparison with simpler inorganic…

Materials Science · Physics 2020-05-21 Thomas C. Nicholas , Andrew L. Goodwin , Volker L. Deringer

It has recently been observed by Zuiddam that finite graphs form a preordered commutative semiring under the graph homomorphism preorder together with join and disjunctive product as addition and multiplication, respectively. This led to a…

Combinatorics · Mathematics 2021-10-28 Tobias Fritz

We use a combined phase-field/lattice-Boltzmann scheme [D. Medvedev, K. Kassner, Phys. Rev. E {\bf 72}, 056703 (2005)] to simulate non-facetted crystal growth from an undercooled melt in external flows. Selected growth parameters are…

Materials Science · Physics 2009-11-11 Dmitry Medvedev , Thomas Fischaleck , Klaus Kassner

Graph generation has emerged as a critical task in fields ranging from drug discovery to circuit design. Contemporary approaches, notably diffusion and flow-based models, have achieved solid graph generative performance through constructing…

Machine Learning · Computer Science 2026-03-06 Keyue Jiang , Jiahao Cui , Xiaowen Dong , Laura Toni

Modeling the spontaneous evolution of morphology in natural systems and its preservation by proportionate growth remains a major scientific challenge. Yet, it is conceivable that if the basic mechanisms of growth and the coupled kinetic…

Soft Condensed Matter · Physics 2020-12-30 Virginia von Streng , Rami Abi-Akl , Bianca Giovanardi , Tal Cohen

We discuss a link between graph theory and geometry that arises when considering graph dynamical systems with odd interactions. The equilibrium set in such systems is not a collection of isolated points, but rather a union of manifolds,…

Dynamical Systems · Mathematics 2024-08-28 Davide Sclosa

Transition graphs capture the memory and sequential response of multistable media, by specifying their evolution under external driving. Microscopically, collections of bistable elements, or hysterons, provide a powerful model for these…

Soft Condensed Matter · Physics 2025-11-27 Margot H. Teunisse , Martin van Hecke

Data with geometric structure is ubiquitous in machine learning often arising from fundamental symmetries in a domain, such as permutation-invariance in graphs and translation-invariance in images. Group-convolutional architectures, which…

Machine Learning · Computer Science 2024-10-10 Bobak T. Kiani , Lukas Fesser , Melanie Weber