English
Related papers

Related papers: Modeling Disordered Quantum Systems with Dynamical…

200 papers

An exactly solvable model for the rewiring dynamics of weighted, directed networks is introduced. Simulations indicate that the model exhibits two types of condensation: (i) a phase in which, for each node, a finite fraction of its total…

Statistical Mechanics · Physics 2009-11-11 A. G. Angel , T. Hanney , M. R. Evans

We study the diffusion of monochromatic classical waves in a disordered acoustic medium by scattering theory. In order to avoid artifacts associated with mathematical point scatterers, we model the randomness by small but finite insertions.…

Disordered Systems and Neural Networks · Physics 2009-11-11 Sijmen Gerritsen , Gerrit E. W. Bauer

First we present an approach to formulate unbalanced three-phase power flow problems for general networks that explicitly separates device models and network models. A device model consists of (i) an internal model and (ii) a conversion…

Optimization and Control · Mathematics 2022-07-27 Steven H. Low

The overdamped dynamics of a charged particle driven by an uniform electric field through a random sequence of scatterers in one dimension is investigated. Analytic expressions of the mean velocity and of the velocity power spectrum are…

Chaotic Dynamics · Physics 2009-11-07 H. Kunz , R. Livi , A. Suto

Electromagnetic wave propagation through complex inhomogeneous walls introduces significant distortions to through-wall radar signatures. Estimation of wall thickness, dielectric, and conductivity profiles may enable wall effects to be…

Signal Processing · Electrical Eng. & Systems 2026-02-13 Kainat Yasmeen , Shobha Sundar Ram

We present a model of dissipative transport in the fractional quantum Hall regime. Our model takes account of tunneling through saddle points in the effective potential for excitations created by impurities. We predict the temperature range…

Mesoscale and Nanoscale Physics · Physics 2011-03-28 N. d'Ambrumenil , B. I. Halperin , R. H. Morf

We theoretically study the dynamical phase diagram of the Dicke model in both classical and quantum limits using large, experimentally relevant system sizes. Our analysis elucidates that the model features dynamical critical points that are…

Quantum Physics · Physics 2021-06-09 R. J. Lewis-Swan , S. R. Muleady , D. Barberena , J. J. Bollinger , A. M. Rey

Diffusion models are important in tissue engineering as they enable an understanding of molecular delivery to cells in tissue constructs. As three-dimensional (3D) tissue constructs become larger, more intricate, and more clinically…

Tissues and Organs · Quantitative Biology 2015-12-22 Richard J. McMurtrey

The impact of quenched disorder on deterministic diffusion in chaotic dynamical systems is studied. As a simple example, we consider piecewise linear maps on the line. In computer simulations we find a complicated scenario of multiple…

Chaotic Dynamics · Physics 2009-11-07 R. Klages

Quantum coherence and phase transitions are studied in a finite one-dimensional Bose--Hubbard model using exact diagonalization under thermal fluctuations, a Stark potential, and disorder. The condensate fraction, superfluid fraction,…

The introduction of quantum concepts is increasingly making its way into generative machine learning models. However, while there are various implementations of quantum Generative Adversarial Networks, the integration of quantum elements…

Time-resolved photoemission spectroscopy provides a unique and direct way to explore the real-time nonequilibrium dynamics of electrons and holes. The formal theory of the spectral function evolution requires inclusion of electronic…

Materials Science · Physics 2025-05-09 Thomas Blommel , Enrico Perfetto , Gianluca Stefanucci , Vojtěch Vlček

The Schwinger Model from Quantum Electrodynamics (QED) has long served as a valuable simplified model for exploring key physical phenomena in Quantum Chromodynamics (QCD)-a field rich with fundamental insights but is substantially more…

Quantum Physics · Physics 2025-09-25 Ao-Ning Wang , Min-Quan He , Z. D. Wang

We use a neural network ansatz originally designed for the variational optimization of quantum systems to study dynamical large deviations in classical ones. We obtain the scaled cumulant-generating function for the dynamical activity of…

Statistical Mechanics · Physics 2021-09-22 Corneel Casert , Tom Vieijra , Stephen Whitelam , Isaac Tamblyn

A fully-convolutional neural-network model is used to predict the streamwise velocity fields at several wall-normal locations by taking as input the streamwise and spanwise wall-shear-stress planes in a turbulent open channel flow. The…

Fluid Dynamics · Physics 2020-08-26 L. Guastoni , M. P. Encinar , P. Schlatter , H. Azizpour , R. Vinuesa

We consider network models of quantum localisation in which a particle with a two-component wave function propagates through the nodes and along the edges of an arbitrary directed graph, subject to a random SU(2) rotation on each edge it…

Mathematical Physics · Physics 2009-11-10 John Cardy

Spectral functions are central to link experimental probes to theoretical models in condensed matter physics. However, performing exact numerical calculations for interacting quantum matter has remained a key challenge especially beyond one…

Strongly Correlated Electrons · Physics 2023-08-03 Tiago Mendes-Santos , Markus Schmitt , Markus Heyl

We study the dynamics of a generalization of quantum coin walk on the line which is a natural model for a diffusion modified by quantum or interference effects. In particular, our results provide surprisingly simple explanations to…

Quantum Physics · Physics 2007-05-23 A. Wojcik , T. Luczak , P. Kurzynski , A. Grudka , M. Bednarska

Disordered spatial networks describe structures and interactions across multiple length scales. The scattering and interference of waves within these networks result in structural phase transitions, localization, diffusion, and band gaps.…

Disordered Systems and Neural Networks · Physics 2026-05-07 Florin Hemmann , Vincent Glauser , Ullrich Steiner , Matthias Saba

Machine-learned regression models represent a promising tool to implement accurate and computationally affordable energy-density functionals to solve quantum many-body problems via density functional theory. However, while they can easily…

Computational Physics · Physics 2022-11-08 Emanuele Costa , Giuseppe Scriva , Rosario Fazio , Sebastiano Pilati