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When studying out-of-equilibrium systems, one often excites the dynamics in some degrees of freedom while removing the excitation in others through damping. In order for the system to converge to a statistical steady state, the dynamics…

Probability · Mathematics 2025-03-26 David P. Herzog , Jonathan C. Mattingly

We present here for the first time a unifying perspective for the lack of equipartition in non-linear ordered systems and the low temperature phase-space fragmentation in disordered systems. We demonstrate that they are just two…

Statistical Mechanics · Physics 2021-02-08 Giacomo Gradenigo , Fabrizio Antenucci , Luca Leuzzi

Random matrix theory yields valuable insights into the universal features of quantum many-body chaotic systems. Although all-to-all interactions are traditionally studied, many interesting dynamical questions, such as transport of a…

Statistical Mechanics · Physics 2025-08-13 Klée Pollock , Jonathan D. Kroth , Nathan Pagliaroli , Thomas Iadecola , Jonathon Riddell

We present a low-energy effective theory to describe the localization-delocalization transition, which occurs for wave functions of electrons and holes injected individually by a voltage pulse with noninteger flux quantum. We find that the…

Mesoscale and Nanoscale Physics · Physics 2025-04-08 Y. Yin

This thesis is devoted to the application of random matrix theory to the study of random surfaces, both discrete and continuous; special emphasis is placed on surface boundaries and the associated boundary conditions in this formalism. In…

Mathematical Physics · Physics 2016-03-04 Benjamin Niedner

The one-dimensional random trap model with a power-law distribution of mean sojourn times exhibits a phenomenon of dynamical localization in the case where diffusion is anomalous: The probability to find two independent walkers at the same…

Data Analysis, Statistics and Probability · Physics 2015-03-03 Franziska Flegel , Igor M. Sokolov

We consider a one-dimensional system of interacting bosons in a random potential. At zero temperature, it can be either in the superfluid or in the insulating phase. We study the transition at weak disorder and moderate interaction. Using a…

In the present work, we investigated the correlation-induced localization-delocalization transition in the one-dimensional tight-binding model with fractal disorder. We obtained a phase transition diagram from localized to extended states…

Disordered Systems and Neural Networks · Physics 2015-08-26 Hiroaki S. Yamada

Deterministic models for radiation transport describe the density of radiation particles moving through a background material. In radiation therapy applications, the phase space of this density is composed of energy, spatial position and…

Numerical Analysis · Mathematics 2021-11-16 Jonas Kusch , Pia Stammer

Low dimensional quasiperiodic systems exhibit localization transitions by turning all quantum states localized after a critical quasidisorder. While certain systems with modified or constrained quasiperiodic potential undergo multiple…

Quantum Gases · Physics 2022-06-14 Ashirbad Padhan , Mrinal Kanti Giri , Suman Mondal , Tapan Mishra

The distribution function of local amplitudes of single-particle states in disordered conductors is calculated on the basis of the supersymmetric $\sigma$-model approach using a saddle-point solution of its reduced version. Although the…

Condensed Matter · Physics 2009-10-28 Vladimir I. Fal'ko , K. Efetov

We have been investigating the problem of the Anderson localization in a disordered one dimensional tight-binding model. The disorder is created by the interaction of mobile particles with other species, immobilized at random positions. We…

Quantum Gases · Physics 2016-11-23 Jan Major

Reentrant localization has recently been observed in systems with quasi-periodic nearest-neighbor hopping, where the interplay between dimerized hopping and staggered disorder is identified as the driving mechanism. However, the robustness…

Disordered Systems and Neural Networks · Physics 2024-12-19 Pei-Jie Chang , Qi-Bo Zeng , Jinghui Pi , Dong Ruan , Gui-Lu Long

We develop an analytical theory for diffusive random lasers by coupling the transport theory of the disordered medium to the semiclassical laser rate equations, accounting for (coherent) stimulated and (incoherent) spontaneous emission.…

Disordered Systems and Neural Networks · Physics 2012-03-27 R. Frank , A. Lubatsch , J. Kroha

In condensed-matter, level statistics has long been used to characterize the phases of a disordered system. We provide evidence within the context of a simple model that in a disordered large-N gauge theory with a gravity dual, there exist…

High Energy Physics - Theory · Physics 2012-06-12 Omid Saremi

We study the transport and localization properties of scalar vibrations on a lattice with random bond strength by means of the transfer matrix method. This model has been recently suggested as a means to investigate the vibrations and heat…

Disordered Systems and Neural Networks · Physics 2007-05-23 Omri Gat , Zeev Olami

The Strong Disorder RG approach for random systems has been extended in many new directions since our previous review of 2005 [Phys. Rep. 412, 277]. The aim of the present colloquium paper is thus to give an overview of these various recent…

Disordered Systems and Neural Networks · Physics 2018-11-26 Ferenc Iglói , Cécile Monthus

The simplified model of first-order transition in a media with frozen long-range transition-temperature disorder is considered. It exhibits the smearing of the transition due to appearance of the intermediate inhomogeneous phase with…

Disordered Systems and Neural Networks · Physics 2009-11-10 P. N. Timonin

We consider systems of particles hopping stochastically on $d$-dimensional lattices with space-dependent probabilities. We map the master equation onto an evolution equation in a Fock space where the dynamics are given by a quantum…

Condensed Matter · Physics 2007-05-23 Gunter Schuetz , Sven Sandow

Unsupervised learning aims at the discovery of hidden structure that drives the observations in the real world. It is essential for success in modern machine learning. Latent variable models are versatile in unsupervised learning and have…

Machine Learning · Computer Science 2016-06-13 Furong Huang
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