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In areas such as computer software and hardware, manufacturing systems, and transportation, engineers encounter networks with arbitrarily large numbers of isomorphic subprocesses. Parameterized systems provide a framework for modeling such…

Formal Languages and Automata Theory · Computer Science 2016-10-03 M. H. Zibaeenejad , J. G. Thistle

Topological phases of matter are often understood and predicted with the help of crystal symmetries, although they don't rely on them to exist. In this chapter we review how topological phases have been recently shown to emerge in amorphous…

Disordered Systems and Neural Networks · Physics 2022-08-23 Adolfo G. Grushin

The emergence of synchronization in a network of coupled oscillators is a fascinating topic in various scientific disciplines. A coupled oscillator network is characterized by a population of heterogeneous oscillators and a graph describing…

Optimization and Control · Mathematics 2015-06-05 Florian Dörfler , Michael Chertkov , Francesco Bullo

We construct families of symmetric, antisymmetric, and asymmetric solitary modes in one-dimensional bichromatic lattices with the second-harmonic-generating ($\chi ^{(2)}$) nonlinearity concentrated at a pair of sites placed at distance…

Pattern Formation and Solitons · Physics 2013-07-17 V. A. Brazhnyi , B. A. Malomed

Positioned between crystalline solids and liquids, disordered many-particle systems which are stealthy and hyperuniform represent new states of matter that are endowed with novel physical and thermodynamic properties. Such stealthy and…

Statistical Mechanics · Physics 2016-02-10 Eli Chertkov , Robert A. DiStasio , Ge Zhang , Roberto Car , Salvatore Torquato

The negatively charged silicon vacancy ($\mathrm{V_{Si}^-}$) in silicon carbide is a well-studied point defect for quantum applications. At the same time, a closer inspection of ensemble photoluminescence and electron paramagnetic resonance…

Due to their ability to recognize complex patterns, neural networks can drive a paradigm shift in the analysis of materials science data. Here, we introduce ARISE, a crystal-structure identification method based on Bayesian deep learning.…

Materials Science · Physics 2021-11-09 Andreas Leitherer , Angelo Ziletti , Luca M. Ghiringhelli

Nonparametric detection of existence of an anomalous structure over a network is investigated. Nodes corresponding to the anomalous structure (if one exists) receive samples generated by a distribution q, which is different from a…

Machine Learning · Statistics 2017-10-11 Shaofeng Zou , Yingbin Liang , H. Vincent Poor

Strongly correlated phases of matter are often described in terms of straightforward electronic patterns. This has so far been the basis for studying the Fermi-Hubbard model realized with ultracold atoms. Here, we show that artificial…

A scenario has recently been reported in which in order to stabilize complete synchronization of an oscillator network---a symmetric state---the symmetry of the system itself has to be broken by making the oscillators nonidentical. But how…

Adaptation and Self-Organizing Systems · Physics 2017-06-20 Yuanzhao Zhang , Takashi Nishikawa , Adilson E. Motter

Unraveling the structural factors influencing the dynamics of amorphous solids is crucial. While deep learning aids in navigating these complexities, transparency issues persist. Inspired by the successful application of prototype neural…

Soft Condensed Matter · Physics 2024-03-19 Xiao Jiang , Zean Tian , Kenli Li , Wangyu Hu

The most profound effect of disorder on the elastic response of solids is the nonaffinity of local displacements whereby the atoms (particles, network junctions) do not simply follow the macroscopic strain, as they do in perfect crystals,…

Soft Condensed Matter · Physics 2012-01-12 Alessio Zaccone , Jamie R. Blundell , Eugene M. Terentjev

A simulation study demonstrates that localization can arise as the result of the breakdown of stable quasi-crystal-like atomic configurations. Samples produced at elevated quench rates and via more energetic processes contain a lower…

Materials Science · Physics 2007-05-23 Yunfeng Shi , Michael L. Falk

We have extended our experimentally constrained molecular relaxation technique (P. Biswas {\it et al}, Phys. Rev. B {\bf 71} 54204 (2005)) to hydrogenated amorphous silicon: a 540-atom model with 7.4 % hydrogen and a 611-atom model with 22…

Materials Science · Physics 2009-11-13 Parthapratim Biswas , Raymond Atta-Fynn , David A. Drabold

We investigate the dependence of the structural phase transitions in an infinite quasi-one-dimensional system of repulsively interacting particles on the profile of the confining channel. Three different functional expressions for the…

Mesoscale and Nanoscale Physics · Physics 2014-09-19 J. E. Galván-Moya , V. R. Misko , F. M. Peeters

In this work and the supporting Parts II [2] and III [3], we provide a rather detailed analysis of the stability and performance of asynchronous strategies for solving distributed optimization and adaptation problems over networks. We…

Systems and Control · Computer Science 2014-12-17 Xiaochuan Zhao , Ali H. Sayed

In this paper the amorphous/solid to disorder liquid structural phase transitions of an anomalous confined fluid is analyzed using their local fractal dimension. The model is a system of particles interacting through a two length scales…

Soft Condensed Matter · Physics 2016-02-17 Elsa M. de la Calleja-Mora , Leandro B. Krott , Marcia C. Barbosa

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features…

Data Analysis, Statistics and Probability · Physics 2017-10-05 Paweł Oświȩcimka , Lorenzo Livi , Stanisław Drożdż

The behaviour of many real-world phenomena can be modelled by nonlinear dynamical systems whereby a latent system state is observed through a filter. We are interested in interacting subsystems of this form, which we model by a set of…

Machine Learning · Computer Science 2017-02-20 Oliver M. Cliff , Mikhail Prokopenko , Robert Fitch

Architected materials achieve unique mechanical properties through precisely engineered microstructures that minimize material usage. However, a key challenge of low-density materials is balancing high stiffness with stable deformability up…

Materials Science · Physics 2024-09-20 Matheus I. N. Rosa , Konstantinos Karapiperis , Kaoutar Radi , Dennis M. Kochmann