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The dynamical properties and mechanical functions of amorphous materials are governed by their microscopic structures, particularly the elasticity of the interaction networks, which is generally complicated by structural heterogeneity. This…

Statistical Mechanics · Physics 2018-04-11 Le Yan

Using terahertz time domain spectroscopy we investigate the normal incidence transmission through periodically and randomly arranged planar split ring resonators (SRRs). Introduction of positional disorder in metamaterials has no effect on…

Optics · Physics 2015-05-14 Ranjan Singh , Xinchao Lu , Jianqiang Gu , Zhen Tian , Weili Zhang

Disordered (amorphous) materials, such as glasses, are emerging as promising candidates for applications within energy storage, nonlinear optics, and catalysis. Their lack of long-range order and complex short- and medium-range orderings,…

Materials Science · Physics 2025-09-18 Jonas A. Finkler , Yan Lin , Tao Du , Jilin Hu , Morten M. Smedskjaer

Heterogeneous k-core percolation is an extension of a percolation model which has interesting applications to the resilience of networks under random damage. In this model, the notion of node robustness is local, instead of global as in…

Disordered Systems and Neural Networks · Physics 2013-03-08 Davide Cellai , James P. Gleeson

Living systems maintain stable internal states despite environmental fluctuations. Absolute concentration robustness (ACR) is a striking homeostatic phenomenon in which the steady-state concentration of a species remains invariant despite…

Dynamical Systems · Mathematics 2025-11-04 Hyukpyo Hong , Diego Rojas La Luz , Gheorghe Craciun

We present an extension of the continuous damage fiber bundle model to describe the gradual degradation of highly heterogeneous materials under an increasing external load. Breaking of a fiber in the model is preceded by a sequence of…

Materials Science · Physics 2009-11-13 F. Raischel , F. Kun , H. J. Herrmann

Disorder, though naturally present in experimental samples and strongly influencing a wide range of material phenomena, remains underexplored in first-principles studies due to the computational cost of sampling the large supercell and…

Materials Science · Physics 2025-06-19 Zhenyao Fang , Ting-Wei Hsu , Qimin Yan

In this work, we build a generic architecture of Convolutional Neural Networks to discover empirical properties of neural networks. Our first contribution is to introduce a state-of-the-art framework that depends upon few hyper parameters…

Computer Vision and Pattern Recognition · Computer Science 2017-03-07 Edouard Oyallon

Random Boolean networks were introduced in 1969 by Kauffman as a model for gene regulation. By combining analytical arguments and efficient numerical simulations, we evaluate the properties of relevant components of critical random Boolean…

Disordered Systems and Neural Networks · Physics 2009-11-11 V. Kaufman , B. Drossel

We present an approach to approximating static properties of glasses without experimental inputs rooted in the first-principles random structure sampling. In our approach, the glassy system is represented by a collection (composite) of…

Materials Science · Physics 2025-10-02 Laszlo Wolf , Andrew Novick , Vladan Stevanović

Mixtures of bare atomic nuclei on a nearly uniform degenerate electron background are a realistic model of matter in the interior of white dwarfs. Despite tremendous progress in understanding their phase diagrams achieved mainly via…

Solar and Stellar Astrophysics · Physics 2025-04-17 D. A. Baiko

The Anderson model serves to study the absence of wave propagation in a medium in the presence of impurities, and is one of the most studied examples in the theory of quantum disordered systems. In these notes we give a review of the…

Mathematical Physics · Physics 2018-07-31 Constanza Rojas-Molina

An efficient numerical framework is presented for modeling viscoelasticity and permanent set of polymers. It is based on the hereditary integral form of transient network theory, in which polymer chains belong to distinct networks each with…

Computational Engineering, Finance, and Science · Computer Science 2025-06-27 Stephen T. Castonguay , Joshua B. Fernandes , Michael A. Puso , Sylvie Aubry

Classification, the process of assigning a label (or class) to an observation given its features, is a common task in many applications. Nonetheless in most real-life applications, the labels can not be fully explained by the observed…

Machine Learning · Statistics 2018-11-07 Johan Barthélemy , Morgane Dumont , Timoteo Carletti

This paper addresses a difficult inverse problem that involves the reconstruction of a three-dimensional model of tetrahedral amorphous semiconductors via inversion of diffraction data. By posing the material-structure determination as a…

Disordered Systems and Neural Networks · Physics 2019-12-06 Dil K. Limbu , Stephen R. Elliott , Raymond Atta-Fynn , Parthapratim Biswas

Analysis of large continuous-time stochastic systems is a computationally intensive task. In this work we focus on population models arising from chemical reaction networks (CRNs), which play a fundamental role in analysis and design of…

Systems and Control · Computer Science 2019-05-27 Milan Češka , Jan Křetínský

In the quest to produce quantum technology, superconducting networks, working at temperatures just above absolute zero, have arisen as one of the most promising physical implementations. The precise analysis and synthesis of such circuits…

Quantum Physics · Physics 2021-04-20 Adrian Parra-Rodriguez

A pulse of light, injected into a weakly disordered dielectric medium, typically, will leave its initial location in a short time, by diffusion. However, due to some rare configurations of disorder, there is a possibility of formation of…

Disordered Systems and Neural Networks · Physics 2018-03-21 V. M. Apalkov , M. E. Raikh , B. Shapiro

The elastic properties of materials derive from their electronic and atomic nature. However, simulating bulk materials fully at these scales is not feasible, so that typically homogenized continuum descriptions are used instead. A seamless…

Materials Science · Physics 2021-08-09 Jaber Rezaei Mianroodi , Shahed Rezaei , Nima H. Siboni , Bai-Xiang Xu , Dierk Raabe

Nondestructive detecting defects (NDD) in concrete structures have been explored for decades. Although limited successes were reported, major limitations still exist. The major limitations are the high noises to signal ratio created from…

Image and Video Processing · Electrical Eng. & Systems 2019-04-11 Chongsheng Cheng , Zhigang Shen
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