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Localization phenomena permeate many branches of physics playing a fundamental role on dynamical processes evolving on heterogeneous networks. These localization analyses are frequently grounded, for example, on eigenvectors of adjacency or…

Physics and Society · Physics 2020-11-24 Diogo H. Silva , Silvio C. Ferreira

Various approaches and measures from network analysis have been applied to granular and particulate networks to gain insights into their structural, transport, failure-propagation and other systems-level properties. In this article, we…

Soft Condensed Matter · Physics 2019-11-06 Silvia Nauer , Lucas Böttcher , Mason A. Porter

We study the localization transition in the integer quantum Hall effect as described by the network model of quantum percolation. Starting from a path integral representation of transport Green's functions for the network model, which…

Mesoscale and Nanoscale Physics · Physics 2009-10-28 J. Kondev , J. B. Marston

We consider nanonodes randomly distributed in a circular area and characterize the received signal strength when a pair of these nodes employ molecular communication. Two communication methods are investigated, namely free diffusion and…

Emerging Technologies · Computer Science 2018-01-29 Rafay Iqbal Ansari , Chrysostomos Chrysostomou , Taqwa Saeed , Marios Lestas , Andreas Pitsillides

The transport properties on the two-dimensional surface of coupled multilayer heterostructures are studied in the integer quantum Hall states. We emphasize the criticality of the surface state and the phase coherent transport properties in…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Vasiliki Plerou , Ziqiang Wang

The distributional reinforcement learning (RL) approach advocates for representing the complete probability distribution of the random return instead of only modelling its expectation. A distributional RL algorithm may be characterised by…

Machine Learning · Computer Science 2023-03-20 Thibaut Théate , Antoine Wehenkel , Adrien Bolland , Gilles Louppe , Damien Ernst

The propagation of light through samples with random inhomogeneities can be described by way of transmission eigenchannels, which connect incoming and outgoing external propagating modes. Although the detailed structure of a disordered…

Disordered Systems and Neural Networks · Physics 2014-04-18 A. Peña , A. Girschik , F. Libisch , S. Rotter , A. A. Chabanov

Local percolation probabilities are used to characterize the connectivity in porous and heterogeneous media. Together with local porosity distributions they allow to predict transport properties \cite{hil91d}. While local porosity…

Condensed Matter · Physics 2015-06-25 R. Hilfer , T. Rag , B. Virgi

We have developed new methods to calculate dispersion curves (analytically in the simpler cases) from which we are able to derive the spatial distribution of electron and current densities. We investigate the case where the magnetic field…

Condensed Matter · Physics 2009-10-28 E. Hofstetter , J. M. C. Taylor , A. MacKinnon

The diffusion of electronic wave packets in one-dimensional systems with on-site, binary disorder is numerically investigated within the framework of a single-band tight-binding model. Fractal properties are incorporated by assuming that…

Disordered Systems and Neural Networks · Physics 2008-07-07 P. R. Wells , J. d'Albuquerque e Castro , S. L. A. de Queiroz

This article deals with transport properties of one dimensional Brownian diffusion under the influence of a correlated quenched random force, distributed as a two-level Poisson process. We find in particular that large time scaling laws of…

Condensed Matter · Physics 2009-10-28 Cecile MONTHUS

In large-scale quantum networks, quantum repeaters provide an efficient method to distribute entangled states among selected nodes for realizing long-distance and complicated quantum communications. However, extending quantum repeater…

Quantum Physics · Physics 2025-01-10 Tianen Chen , Yun Shang , Chitong Chen , Heng Fan

Transmission of the scalar field through the random medium, represented by the system of randomly distributed dielectric cylinders is calculated numerically. System is mapped to the problem of electronic transport in disordered…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 P. Markos , C. M. Soukoulis

We study entanglement distribution in quantum complex networks where nodes are connected by bipartite entangled states. These networks are characterized by a complex structure, which dramatically affects how information is transmitted…

Quantum Physics · Physics 2011-05-18 Martí Cuquet , John Calsamiglia

Statistical properties of coherent radiation propagating in a quasi - 1D random media is studied in the framework of random matrix theory. Distribution functions for the total transmission coefficient and the angular transmission…

Condensed Matter · Physics 2009-10-28 Eugene Kogan , Moshe Kaveh

We study the critical behavior of various geometrical and transport properties of percolation in 6 dimensions. By employing field theory and renormalization group methods we analyze fluctuation induced logarithmic corrections to scaling up…

Statistical Mechanics · Physics 2009-11-10 Olaf Stenull , Hans-Karl Janssen

Three-dimensional random electron systems undergo quantum phase transitions and show rich phase diagrams. Examples of the phases are the band gap insulator, Anderson insulator, strong and weak topological insulators, Weyl semimetal, and…

Disordered Systems and Neural Networks · Physics 2017-03-16 Tomi Ohtsuki , Tomoki Ohtsuki

We present an exact mathematical framework able to describe site-percolation transitions in real multiplex networks. Specifically, we consider the average percolation diagram valid over an infinite number of random configurations where…

Physics and Society · Physics 2016-12-21 Ginestra Bianconi , Filippo Radicchi

Random matrix theory of the transition strengths is applied to transport in the strongly localized regime. The crossover distribution function between the different ensembles is derived and used to predict quantitatively the {\sl universal}…

Condensed Matter · Physics 2009-10-22 Y. Meir , O. Entin-Wohlman

As a surrogate for computationally intensive meso-scale simulation of woven composites, this article presents Recurrent Neural Network (RNN) models. Leveraging the power of transfer learning, the initialization challenges and sparse data…

Materials Science · Physics 2024-07-08 Ehsan Ghane , Martin Fagerström , Mohsen Mirkhalaf