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We have developed different network approaches to analyze complex patterns of frictional interfaces (contact area developments). Network theory is a fundamental tool for the modern understanding of complex systems in which, by a simple…

General Physics · Physics 2012-01-04 H. O. Ghaffari , R. P. Young

Recent optical-potential studies of the phenomenology of kaonic atoms are reviewed. It is shown that the data can be fitted by a complex optical potential with either a relatively shallow attractive component (about -50 MeV at…

Nuclear Theory · Physics 2009-11-07 Avraham Gal

Entangled networks are ubiquitous in tissues, polymers, and fabrics. However, their mechanics remain insufficiently understood due to the complexity of the topological constraints at the network level. Here, we develop a mathematical…

Soft Condensed Matter · Physics 2025-09-23 Juntao Huang , Jiabin Liu , Shaoting Lin

We explore the robustness of complex networks against physical damage. We focus on spatially embedded network models and datasets where links are physical objects or physically transfer some quantity, which can be disrupted at any point…

Statistical Mechanics · Physics 2024-12-13 Luka Blagojević , Ivan Bonamassa , Márton Pósfai

We provide a phenomenological formula which describes the low-frequency optical absorption of charge carriers in disordered systems with localization. This allows to extract, from experimental data on the optical conductivity, the relevant…

Materials Science · Physics 2015-06-19 Simone Fratini , Sergio Ciuchi , Didier Mayou

It is known from both experiments and molecular dynamics simulations that chemically patterning a solid surface has an effect on the flow of an adjacent liquid. This fact is in stark contrast with predictions of classical fluid mechanics…

Fluid Dynamics · Physics 2012-02-17 J. E. Sprittles , Y. D. Shikhmurzaev

A theoretical model for understanding the formation of interfacial thin films is presented, which combines density functional theory calculations for interface energies with thermodynamic modeling techniques for multicomponent bulk systems.…

Materials Science · Physics 2012-02-22 Sven A. E. Johansson , Göran Wahnström

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases…

Quantitative Methods · Quantitative Biology 2022-10-18 August George , Doo Nam Kim , Trevor Moser , Ian T. Gildea , James E. Evans , Margaret S. Cheung

We describe a method for modeling the geometry of porous materials. The approach enables the independent selection of crucial parameters, including porosity, pore size distribution, pore shape, and connectivity. Consequently, it can…

Materials Science · Physics 2024-04-19 Felix Buchele , Patric Müller , Michael Blank , Thorsten Pöschel

We study the geometrical characteristic of quasi-static fractures in disordered media, using iterated conformal maps to determine the evolution of the fracture pattern. This method allows an efficient and accurate solution of the Lam\'e…

Statistical Mechanics · Physics 2009-11-07 Felipe Barra , H. George E. Hentschel , Anders Levermann , Itamar Procaccia

Hierarchical networks are attracting a renewal interest for modelling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the…

Disordered Systems and Neural Networks · Physics 2016-01-26 Elena Agliari , Adriano Barra , Andrea Galluzzi , Francesco Guerra , Daniele Tantari , Flavia Tavani

This contribution extends linear models for feature vectors to sublinear models for graphs and analyzes their properties. The results are (i) a geometric interpretation of sublinear classifiers, (ii) a generic learning rule based on the…

Machine Learning · Computer Science 2014-03-11 Brijnesh J. Jain

In the past two decades, significant advances have been made in understanding the structural and functional properties of biological networks, via graph-theoretic analysis. In general, most graph-theoretic studies are conducted in the…

Physics and Society · Physics 2013-10-21 Michelle Rudolph-Lilith , Lyle E. Muller

Topological data analysis is an emerging mathematical concept for characterizing shapes in multi-scale data. In this field, persistence diagrams are widely used as a descriptor of the input data, and can distinguish robust and noisy…

Machine Learning · Statistics 2017-06-13 Genki Kusano , Kenji Fukumizu , Yasuaki Hiraoka

Failure trajectories, identifying the probable failure zones, and damage statistics are some of the key quantities of relevance in brittle fracture applications. High-fidelity numerical solvers that reliably estimate these relevant…

Machine Learning · Computer Science 2022-02-16 Somdatta Goswami , Minglang Yin , Yue Yu , George Karniadakis

The efforts associated with parametrization of continuum-based models for crystal plasticity are a significant obstacle for the routine use of these models in materials science and engineering. While phenomenological constitutive…

Materials Science · Physics 2025-02-18 Nikhil Prabhu , Martin Diehl

Recently, simple conditions for well-behaved-ness of anisotropic Voronoi diagrams have been proposed. While these conditions ensure well-behaved-ness of two types of practical anisotropic Voronoi diagrams, as well as the geodesic-distance…

Computational Geometry · Computer Science 2012-03-27 Guillermo D. Canas

For thin films of superfluid adsorbed on a disordered substrate, we derive the equation of motion for a vortex in the presence of a random potential within a mean field (Hartree) description of the condensate. The compressible nature of the…

Statistical Mechanics · Physics 2009-10-31 H. H. Lee , J. M. F. Gunn

Weak antilocalization measurements has become a standard tool for studying quantum coherent transport in topological materials. It is often used to extract information about number of conducting channels and dephasing length of topological…

Mesoscale and Nanoscale Physics · Physics 2018-12-21 K. Dybko , G. P. Mazur , W. Wolkanowicz , M. Szot , P. Dziawa , J. Z. Domagala , M. Wiater , T. Wojtowicz , G. Grabecki , T. Story

We investigate the effective properties (conductivity, diffusivity and elastic moduli) of model random composite media derived from Gaussian random fields and overlapping hollow spheres. The morphologies generated in the models exhibit low…

Disordered Systems and Neural Networks · Physics 2009-10-31 Anthony Roberts , Mark Knackstedt
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