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Nanoscale electronics and novel fabrication technologies bear unique opportunities for self-assembling multi-billion component systems in a largely random manner, which would likely lower fabrication costs significantly compared to a…

Disordered Systems and Neural Networks · Physics 2007-05-23 Christof Teuscher

Branched flow is a universal phenomenon in which treebranch-like filaments form through traveling waves or particle flows in irregular mediums. Branched flow of high-current relativistic electron beams (REBs) has been recently discovered…

Plasma Physics · Physics 2023-12-18 K. Jiang , T. W. Huang , R. Li , C. T. Zhou

Following our recent theoretical and experimental results that show how zero-permittivity metamaterials may provide anomalous tunneling and energy squeezing through ultranarrow waveguide channels, here we report an experimental…

Materials Science · Physics 2009-11-13 Brian Edwards , Andrea Alu , Mario G. Silveirinha , Nader Engheta

The flow around a symmetric aerofoil (NACA 0012) with an array of flexible flaplets attached to the trailing edge has been investigated at Reynolds numbers of 100,000 - 150,000 by using High-Speed Time-Resolved Particle Image Velocimetry…

Fluid Dynamics · Physics 2018-08-29 Edward Talboys , Christoph Bruecker

Rectified Linear Units (ReLUs) have been shown to ameliorate the vanishing gradient problem, allow for efficient backpropagation, and empirically promote sparsity in the learned parameters. They have led to state-of-the-art results in a…

Machine Learning · Computer Science 2016-05-30 Xingyuan Pan , Vivek Srikumar

The quest for wave channeling and manipulation has driven a strong research effort on topological and architected materials, capable of propagating localized electromagnetical or mechanical signals. With reference to an elastic structural…

Classical Physics · Physics 2019-02-20 G. Bordiga , L. Cabras , A. Piccolroaz , D. Bigoni

Efforts to modulate the electronic properties of atomically thin crystalline nanoribbons requires precise control over their morphology. Here, we perform atomistic simulations on freestanding graphene nanoribbons (GNRs) to first identify…

Mesoscale and Nanoscale Physics · Physics 2011-07-21 Hailong Wang , Moneesh Upmanyu

We consider the slow and athermal deformations of amorphous solids and show how the ensuing sequence of discrete plastic rearrangements can be mapped onto a directed network. The network topology reveals a set of highly connected regions…

Soft Condensed Matter · Physics 2019-11-06 Muhittin Mungan , Srikanth Sastry , Karin Dahmen , Ido Regev

Electron transmission through semiconductor superlattices is studied with transfer matrix method and resonance theory. The formation of electron band-pass transmission is ascribed to the coupling of different modes in those semiconductor…

Mesoscale and Nanoscale Physics · Physics 2022-05-10 Xiaoguang Luo , Jian Shi , Yaoming Zhang , Ziang Niu , Dongpeng Miao , Huiru Mi , Wei Huang

Understanding the dynamics of neural networks in different width regimes is crucial for improving their training and performance. We present an exact solution for the learning dynamics of a one-hidden-layer linear network, with…

Machine Learning · Computer Science 2025-02-24 Yizhou Xu , Liu Ziyin

Solutions of wormlike micelles can form cross-linked networks on microscopic length scales. The unique mechanical properties of these complex fluids are driven by the interplay between the network structure and dynamics which are…

The proper design of DNA sequences allows for the formation of well defined supramolecular units with controlled interactions via a consecution of self-assembling processes. Here, we benefit from the controlled DNA self-assembly to…

Soft Condensed Matter · Physics 2018-02-14 Javier Fernandez-Castanon , Francesca Bomboi , Francesco Sciortino

This paper investigates the ability of finite samples to identify two-layer irreducible shallow networks with various nonlinear activation functions, including rectified linear units (ReLU) and analytic functions such as the logistic…

Machine Learning · Computer Science 2025-03-18 Yu Xia , Zhiqiang Xu

We propose a new neural network design paradigm Reversible Column Network (RevCol). The main body of RevCol is composed of multiple copies of subnetworks, named columns respectively, between which multi-level reversible connections are…

Computer Vision and Pattern Recognition · Computer Science 2023-02-02 Yuxuan Cai , Yizhuang Zhou , Qi Han , Jianjian Sun , Xiangwen Kong , Jun Li , Xiangyu Zhang

The mechanics of complex soft matter often cannot be understood in the classical physical frame of flexible polymers or rigid rods. The underlying constituents are semiflexible polymers, whose finite bending stiffness ($\kappa$) leads to…

This work attempts to interpret modern deep (convolutional) networks from the principles of rate reduction and (shift) invariant classification. We show that the basic iterative gradient ascent scheme for optimizing the rate reduction of…

Machine Learning · Computer Science 2020-10-30 Kwan Ho Ryan Chan , Yaodong Yu , Chong You , Haozhi Qi , John Wright , Yi Ma

Band theory provides the foundation for understanding electronic structure in crystalline materials, but its reliance on exact translational symmetry limits its applicability to systems with defects, disorder, incommensurate modulations, or…

Materials Science · Physics 2026-05-08 Christopher A. Bairnsfather , Ralph M. Kaufmann , Terry A. Loring , Alexander Cerjan

By means of Langevin dynamics simulations, we investigate the gel formation of randomly functionalized polymers in solution, with the ability to form both intra- and intermolecular reversible bonds. Under highly dilute conditions, these…

Soft Condensed Matter · Physics 2021-09-15 Maud Formanek , Lorenzo Rovigatti , Emanuela Zaccarelli , Francesco Sciortino , Angel J. Moreno

The formation of water-in-oil-in-water (W/O/W) double emulsions can be well-controlled through an organized self-emulsification mechanism in the presence of rigid bottlebrush amphiphilic block copolymers. Nanoscale water droplets with…

Applied Physics · Physics 2020-06-11 Xi Chen , Xiao Yang , DongPo Song , Yuesheng Li

Multiple scales coexist in complex networks. However, the small world property makes them strongly entangled. This turns the elucidation of length scales and symmetries a defiant challenge. Here, we define a geometric renormalization group…

Disordered Systems and Neural Networks · Physics 2018-07-04 Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano
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