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Monolithic neural networks that make use of a single set of weights to learn useful representations for downstream tasks explicitly dismiss the compositional nature of data generation processes. This characteristic exists in data where…

Computer Vision and Pattern Recognition · Computer Science 2023-06-05 Hamed Damirchi , Forest Agostinelli , Pooyan Jamshidi

Surface probes such as scanning tunneling microscopy (STM) have detected complex patterns at the nanoscale, indicative of electronic inhomogeneity, in a variety of high temperature superconductors. In cuprates, the pattern formation is…

Superconductivity · Physics 2011-03-22 B. Phillabaum , E. W. Carlson , K. A. Dahmen

The simplest prescription for building a patterned structure from its constituents is to add particles, one at a time, to an appropriate template. However, self-organizing molecular and colloidal systems in nature can evolve in much more…

Statistical Mechanics · Physics 2009-04-07 Stephen Whitelam , Edward H. Feng , Michael F. Hagan , Phillip L. Geissler

We consider chaotic dynamics of a system of two coupled ring resonators with a linear gain and a nonlinear absorption. Such a structure can be implemented in various settings including microresonator nanostructures, polariton condensates,…

We have analyzed the interplay between noise and periodic spatial modulations in bistable systems outside equilibrium and found that noise is able to increase the spatial order of the system, giving rise to periodic patterns which otherwise…

Statistical Mechanics · Physics 2016-08-15 J. M. G. Vilar , J. M. Rubí

Compositional generalization, the ability to recognize familiar parts in novel contexts, is a defining property of intelligent systems. Although modern models are trained on massive datasets, they still cover only a tiny fraction of the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Arnas Uselis , Andrea Dittadi , Seong Joon Oh

A highly degenerate family of states [proposed in PRB 63, 134503 (2001)] is proven to really minimize the Hamiltonian of the fully frustrated XY model on a dice lattice. The harmonic fluctuations are shown to be no consequence for the…

Superconductivity · Physics 2009-11-10 S. E. Korshunov

Many typical nanoscale structures consist of dielectric nanoparticles with an inevitable oxide-generated coating around them. Depending on the fabrication techniques, these coatings may not be homogeneous, and their distortion can cause…

Optics · Physics 2023-11-27 Ricardo Martin Abraham-Ekeroth , Marcelo Fabian Lester

Most mechanical resonators are treated as simple linear oscillators. Nonlinearity in the resonance behavior of nanoelectromechanical systems (NEMS) has only lately attracted significant interest. Most recently, cubic-order nonlinearity has…

Mesoscale and Nanoscale Physics · Physics 2017-03-10 Madhav Kumar , Bhaskar Choubey , Harish Bhaskaran

Flat-space physics is highly constrained by basic principles such as Lorentz invariance, locality, unitarity and causality. This is neatly seen in the structure of scattering amplitudes. For processes occurring in an expanding background we…

High Energy Physics - Theory · Physics 2022-03-31 Paolo Benincasa

Component systems - ensembles of realizations built from a shared repertoire of modular parts - are ubiquitous in biological, ecological, technological, and socio-cultural domains. From genomes to texts, cities, and software, these systems…

The ability of deep neural networks to learn hierarchical features is widely regarded as a key mechanism underlying their success in high-dimensional learning. Existing theory partially supports this view by establishing approximation rates…

Machine Learning · Statistics 2026-05-26 Shuo Huang , Lorenzo Fiorito , Lorenzo Rosasco , Tomaso Poggio

We use soft x-ray vector-ptychographic tomography to determine the three-dimensional magnetization field in superparamagnetic nanoparticles self-assembled at the liquid-liquid interface and reveal the magnetic order induced by layered…

The lattice gas model of condensation in a heterogeneous pore system, represented by a random graph of cells, is studied using an exact analytical solution. A binary mixture of pore cells with different coordination numbers is shown to…

Statistical Mechanics · Physics 2014-08-26 Thomas P. Handford , Alexander Dear , Francisco J. Pérez-Reche , Sergei N. Taraskin

Neural networks are very powerful learning systems, but they do not readily generalize from one task to the other. This is partly due to the fact that they do not learn in a compositional way, that is, by discovering skills that are shared…

Artificial Intelligence · Computer Science 2018-07-27 Adam Liška , Germán Kruszewski , Marco Baroni

Naturally occuring or man-made systems displaying periodic spatial modulations of their properties on a nanoscale constitute superlattices. Such modulated structures are important both as prototypes of simple nanotechnological devices and…

Strongly Correlated Electrons · Physics 2009-11-11 N. A. Lima , A. L. Malvezzi , K. Capelle

Modular organization characterizes many complex networks occurring in nature, including the brain. In this paper we show that modular structure may be responsible for increasing the robustness of certain dynamical states of such systems. In…

Disordered Systems and Neural Networks · Physics 2015-05-27 Neeraj Pradhan , Subinay Dasgupta , Sitabhra Sinha

Nonlinear dynamical systems possessing reflection symmetry have an invariant subspace in the phase space. The dynamics within the invariant subspace can be random or chaotic. As a system parameter changes, the motion transverse to the…

Chaotic Dynamics · Physics 2007-05-23 Changsong Zhou , C. -H. Lai

Spontaneous pattern formation in a variety of spatially extended nonlinear system always occurs through a modulation instability: homogeneous state of the system becomes unstable with respect to growing modulation modes. Therefore, the…

Pattern Formation and Solitons · Physics 2015-08-25 S. Kumar , R. Herrero , M. Botey , K. Staliunas

Motivated by recent neutron scattering experiments on the cuprate superconductors, we present a phenomenological framework describing the dynamics of collective spin excitations coupled to charge/bond order fluctuations. Our quantum lattice…

Strongly Correlated Electrons · Physics 2007-05-23 Matthias Vojta , Subir Sachdev