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Using the supersymmetry technique, we study the localization-delocalization transition in quasi-one-dimensional non-Hermitian systems with a direction. In contrast to chains, our model captures the diffusive character of carriers' motion at…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. V. Kolesnikov , K. B. Efetov

The relaxation process of a diffusive ring becomes under-damped if the bias (so called affinity) exceeds a critical threshold value, aka delocalization transition. This is related to the spectral properties of the pertinent stochastic…

Statistical Mechanics · Physics 2016-07-05 Daniel Hurowitz , Doron Cohen

Considering a "random walk in a random environment" in a topologically closed circuit, we explore the implications of the percolation and sliding transitions for its relaxation modes. A complementary question regarding the "delocalization"…

Statistical Mechanics · Physics 2016-03-11 Daniel Hurowitz , Doron Cohen

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

An active network is a prototype model in non-equilibrium statistical mechanics. It can represent, for example, a system with particles that have a self-propulsion mechanism. Each node of the network specifies a possible location of a…

Statistical Mechanics · Physics 2018-07-13 Dekel Shapira , Dganit Meidan , Doron Cohen

Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the dynamics of stochastic gradient descent over diagonal linear…

Machine Learning · Computer Science 2021-12-08 Scott Pesme , Loucas Pillaud-Vivien , Nicolas Flammarion

Deep unrolling, or unfolding, is an emerging learning-to-optimize method that unrolls a truncated iterative algorithm in the layers of a trainable neural network. However, the convergence guarantees and generalizability of the unrolled…

Machine Learning · Computer Science 2024-12-02 Samar Hadou , Navid NaderiAlizadeh , Alejandro Ribeiro

We introduce a new approach to analyse the global structure of electronic states in quasi-1D models in terms of the dynamics of a system of parametric oscillators with time-dependent stochastic couplings. We thus extend to quasi-1D models…

Disordered Systems and Neural Networks · Physics 2009-11-11 L. Tessieri , F. M. Izrailev

In one dimension, any disorder is traditionally believed to localize all states. We show that this paradigm breaks down under hyperuniform disorder, which suppresses long-wavelength fluctuations and interpolates between random and periodic…

Disordered Systems and Neural Networks · Physics 2025-09-30 Junmo Jeon , Harukuni Ikeda , Shiro Sakai

We study the delocalisation transition which takes places in one-dimensional disordered systems when the random potential exhibits specific long-range correlations. We consider the case of weak disorder; using a systematic perturbative…

Disordered Systems and Neural Networks · Physics 2007-05-23 L. Tessieri

Deterministic and stochastic Boolean network models are build for the dynamics of negative feedback loops of the p53 pathways. It is shown that the main function of the negative feedback in the p53 pathways is to keep p53 at a low steady…

Molecular Networks · Quantitative Biology 2009-04-16 Hao Ge , Min Qian

Understanding the behavior of stochastic gradient methods is a central problem in modern machine learning. Recent work has highlighted diagonal linear networks as a simplified yet expressive setting for analyzing the optimization and…

Optimization and Control · Mathematics 2026-05-19 Begoña García Malaxechebarría , Courtney Paquette , Maryam Fazel , Dmitriy Drusvyatskiy

This paper is concerned with the study of scalability in nonlinear heterogeneous networks affected by communication delays and disturbances. After formalizing the notion of scalability, we give two sufficient conditions to assess this…

Systems and Control · Electrical Eng. & Systems 2022-07-15 Shihao Xie , Giovanni Russo , Richard Middleton

We study the effects of nonzero time delays in stochastic synchronization problems with linear couplings in complex networks. We consider two types of time delays: transmission delays between interacting nodes and local delays at each node…

Statistical Mechanics · Physics 2012-12-03 D. Hunt , B. K. Szymanski , G. Korniss

An examination of the properties of many-electron conduction through spin-degenerate systems can lead to situations where increasing the bias voltage applied to the system is predicted to decrease the current flowing through it, for the…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Guy Cohen , Eran Rabani

Elastic effects in a model of disordered nematic elastomers are numerically investigated in two dimensions. Networks crosslinked in the isotropic phase exhibit unusual soft mechanical response against stretching. It arises from gradual…

Soft Condensed Matter · Physics 2009-10-31 Nariya Uchida

Transport in complex networks can describe a variety of natural and human-engineered processes including biological, societal and technological ones. However, how the properties of the source and drain nodes can affect transport subject to…

Statistical Mechanics · Physics 2023-10-19 Geoffroy Berthelot , Liubov Tupikina , Min-Yeong Kang , Jérôme Dedecker , Denis S. Grebenkov

A weakly disordered quasi-one-dimensional tight-binding hopping model with $N$ rows is considered. The probability distribution of the Landauer conductance is calculated exactly in the middle of the band, $\epsilon=0$, and it is shown that…

Disordered Systems and Neural Networks · Physics 2009-10-31 P. W. Brouwer , C. Mudry , B. D. Simons , A. Altland

The decay of current autocorrelation functions is investigated for quantum systems featuring strong 'interactions'. Here, the term interaction refers to that part of the Hamiltonian causing the (major) decay of the current. On the time…

Statistical Mechanics · Physics 2011-07-27 Robin Steinigeweg

In this paper, a nonlinear system aiming at reducing the signal transmission rate in a networked control system is constructed by adding nonlinear constraints to a linear feedback control system. Its stability is investigated in detail. It…

Chaotic Dynamics · Physics 2015-06-19 Guofeng Zhang , Tongwen Chen
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