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Network equilibrium models represent a versatile tool for the analysis of interconnected objects and their relationships. They have been widely employed in both science and engineering to study the behavior of complex systems under various…

Adaptation and Self-Organizing Systems · Physics 2024-10-31 Omar Aloui , David Orden , Nizar Bel Hadj Ali , Landolf Rhode-Barbarigos

We study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a…

Neurons and Cognition · Quantitative Biology 2010-07-30 Ilan Breskin , Jordi Soriano , Elisha Moses , Tsvi Tlusty

Generic coarse-grained models are designed such that they are (i) simple and (ii) computationally efficient. They do not aim at representing particular materials, but classes of materials, hence they can offer insight into universal…

Soft Condensed Matter · Physics 2009-02-25 Friederike Schmid

Electrochemical phenomena in biology often unfold in confined geometries where micrometer- to millimeter-scale domains coexist with nanometer-scale interfacial diffuse charge layers. We analyze a model lipid membrane-electrolyte system…

Soft Condensed Matter · Physics 2025-08-20 Joshua B. Fernandes , Hyeongjoo Row , Kranthi K. Mandadapu , Karthik Shekhar

Networks of stiff fibers govern the elasticity of biological structures such as the extracellular matrix of collagen. These networks are known to stiffen nonlinearly under shear or extensional strain. Recently, it has been shown that such…

Soft Condensed Matter · Physics 2024-02-01 Sihan Chen , Tomer Markovich , Fred C. MacKintosh

We introduce a theoretical approach based on scattering theory and total energy methods that treats transport non-linearities, conformational changes and charging effects in molecular wires in a unified way. We apply this approach to…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Eldon Emberly , George Kirczenow

Starting from the working hypothesis that both physics and the corresponding mathematics have to be described by means of discrete concepts on the Planck scale, one of the many problems one has to face in this enterprise is to find the…

High Energy Physics - Theory · Physics 2008-11-26 Manfred Requardt

Deep neural networks are widely known for their remarkable effectiveness across various tasks, with the consensus that deeper networks implicitly learn more complex data representations. This paper shows that sufficiently deep networks…

Machine Learning · Computer Science 2023-10-31 Wojciech Masarczyk , Mateusz Ostaszewski , Ehsan Imani , Razvan Pascanu , Piotr Miłoś , Tomasz Trzciński

Bi-isotropic media, which include isotropic chiral media and Tellegen media as special cases, are the most general form of linear isotropic media where the electric displacement and the magnetic induction are related to both the electric…

Optics · Physics 2016-05-04 Seulong Kim , Kihong Kim

We study Maxwell's equations in random media with small fluctuations of the electric permittivity. We consider a setup where the waves propagate toward a preferred direction, called range. We decompose the electromagnetic wave field in…

Analysis of PDEs · Mathematics 2016-01-05 Liliana Borcea , Josselin Garnier

We investigate the outflux of ions through the channels in a cell membrane. The channels undergo an open/close cycle according to a periodic schedule. Our study is based both on theoretical considerations relying on homogenization theory,…

Analysis of PDEs · Mathematics 2014-11-21 D. Andreucci , D. Bellaveglia , E. N. M. Cirillo

Networks provide a skeleton for the spread of contagions, like, information, ideas, behaviors and diseases. Many times networks over which contagions diffuse are unobserved and need to be inferred. Here we apply survival theory to develop…

Social and Information Networks · Computer Science 2013-05-17 Manuel Gomez Rodriguez , Jure Leskovec , Bernhard Schoelkopf

In this work, we investigate the detailed theory of the supercoupling, anomalous tunneling effect, and field confinement originally identified in [M. Silveirinha, N. Engheta, Phys. Rev. Lett. 97, 157403, (2006)], where we demonstrated the…

Materials Science · Physics 2009-11-13 Mario Silveirinha , Nader Engheta

We analyze the propagation of gravitational waves in a medium containing bounded subsystems ("molecules"), able to induce significant Macroscopic Gravity effects. We establish a precise constitutive relation between the average quadrupole…

General Relativity and Quantum Cosmology · Physics 2019-07-26 Giovanni Montani , Fabio Moretti

Complex networks are ubiquitous: a cell, the human brain, a group of people and the Internet are all examples of interconnected many-body systems characterized by macroscopic properties that cannot be trivially deduced from those of their…

In this paper, it is proved that the continuity of the tangential components of the average electric and magnetic fields is insufficient to describe the reflection of plane waves by a set of thin parallel wires embedded in a dielectric host…

Materials Science · Physics 2009-11-11 Mario G. Silveirinha

We give an explicit formula for the membrane potential of cells in terms of the intracellular and extracellular ionic concentrations, and derive equations for the ionic currents that flow through channels, exchangers and electrogenic pumps…

Biological Physics · Physics 2007-05-23 Lars Petter Endresen , Kevin Hall

This work proposes a novel outer bound for the Gaussian cognitive interference channel in strong interference at the primary receiver based on the capacity of a multi-antenna broadcast channel with degraded message set. It then shows that…

Information Theory · Computer Science 2015-03-19 Stefano Rini , Daniela Tuninetti , Natasha Devroye

A method for extending traditional plasma transport theories into the strong coupling regime is presented. Like traditional theories, this is based on a binary scattering approximation, but where physics associated with many body…

Plasma Physics · Physics 2014-05-09 Scott Baalrud , Jerome Daligault

Deep neural network architectures often consist of repetitive structural elements. We introduce an approach that reveals these patterns and can be broadly applied to the study of deep learning. Similarly to how a power strip helps untangle…

Statistical Mechanics · Physics 2025-07-03 Donghee Lee , Hye-Sung Lee , Jaeok Yi