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The relaxation dynamics of correlated electron transport (ET) along molecular chains is studied based on a substantially improved numerically exact path integral Monte Carlo (PIMC) approach. As archetypical model we consider a Hubbard chain…

Statistical Mechanics · Physics 2009-11-11 L. Muehlbacher , J. Ankerhold , A. Komnik

Many biological processes are supported by special molecules, called motor proteins or molecular motors, that transport cellular cargoes along linear protein filaments and can reversibly associate to their tracks. Stimulated by these…

Statistical Mechanics · Physics 2021-11-17 Akriti Jindal , Anatoly B. Kolomeisky , Arvind Kumar Gupta

We derive the system of equations that allows to include non-equilibrium correlations of filling numbers into the theory of the hopping transport. The system includes the correlations of arbitrary order in a universal way and can be cut at…

Disordered Systems and Neural Networks · Physics 2019-07-31 A. V. Shumilin , Y. M. Beltukov

Associative memory, a form of content-addressable memory, facilitates information storage and retrieval in many biological and physical systems. In statistical mechanics models, associative memory at equilibrium is represented through…

Disordered Systems and Neural Networks · Physics 2022-03-08 Agnish Kumar Behera , Madan Rao , Srikanth Sastry , Suriyanarayanan Vaikuntanathan

Discrete dynamics arise naturally in systems with broken temporal translation symmetry and are typically described by first-order recurrence relations representing classical or quantum Markov chains. When memory effects induced by hidden…

Statistical Mechanics · Physics 2025-10-31 Hugues Meyer , Kay Brandner

In this paper, we consider a class of convection-diffusion equations with memory effects. These equations arise as a result of homogenization or upscaling of linear transport equations in heterogeneous media and play an important role in…

Numerical Analysis · Mathematics 2022-04-04 Yalchin Efendiev , Wing Tat Leung , Wenyuan Li , Sai-Mang Pun , Petr N. Vabishchevich

Complex quantum networks are powerful tools in the modeling of transport phenomena, particularly for biological systems, and enable the study of emergent phenomena in many-body quantum systems. High connectivity and long-range interactions…

Gravitational and electromagnetic interactions are Hamiltonian systems with forces between pairs of particles. We propose an alternative: Hamiltonian dynamics with triplet interactions between point particles. Our system has a potential…

Chaotic Dynamics · Physics 2025-07-22 J. D. Meiss

Natural phenomena frequently involve a very large number of interacting molecules moving in confined regions of space. Cellular transport by motor proteins is an example of such collective behavior. We derive a deterministic compartmental…

Subcellular Processes · Quantitative Biology 2017-11-01 Yoram Zarai , Michael Margaliot , Anatoly B. Kolomeisky

Evidently, some relaxation dynamics, e.g. exponential decays, are much more common in nature than others. Recently there have been attempts to explain this observation on the basis of ``typicality of perturbations'' with respect to their…

Quantum Physics · Physics 2020-04-29 Robin Heveling , Lars Knipschild , Jochen Gemmer

Quantifying the interaction between a system of interest and its ambient conditions, the memory effect links the states of two distinct Hamiltonians: one for the target system and one for the environment. In this paper, we propose the…

Computational Physics · Physics 2026-02-25 Heeyuen Koh , Shigeo Maruyama

We consider two mutually interacting fermionic particle species on a one-dimensional lattice and study how the mass ratio $\eta$ between the two species affects the (equilibration) dynamics of the particles. Focussing on the regime of…

Strongly Correlated Electrons · Physics 2020-07-27 Tjark Heitmann , Jonas Richter , Thomas Dahm , Robin Steinigeweg

Transport in Hamiltonian systems with weak chaotic perturbations has been much studied in the past. In this paper, we introduce a new class of problems: transport in Hamiltonian systems with slowly changing phase space structure that are…

Chaotic Dynamics · Physics 2019-10-02 Freddy Bouchet , Eric Woillez

A link between memory effects in quantum kinetic equations and nonequilibrium correlations associated with the energy conservation is investigated. In order that the energy be conserved by an approximate collision integral, the one-particle…

Statistical Mechanics · Physics 2007-05-23 V. G. Morozov , Gerd Ropke

The transport phenomena of a nonequilibrium lattice gas system are investigated. We consider a simple system that consists of two particles interacting repulsively and the potential forces acting on these particles. Under an external…

Soft Condensed Matter · Physics 2009-11-11 Akinori Awazu

One of the defining traits of quantum mechanics is the uncertainty principle which was originally expressed in terms of the standard deviation of two observables. Alternatively, it can be formulated using entropic measures, and can also be…

Quantum Physics · Physics 2015-09-30 Göktuğ Karpat , Jyrki Piilo , Sabrina Maniscalco

We study coupled transport in the nonequilibrium stationary state of a model consisting of independent random walkers, moving along a one-dimensional channel, which carry a conserved energy-like quantity, with density and temperature…

Statistical Mechanics · Physics 2009-08-11 Hernán Larralde , David P. Sanders

We present the results of a detailed study of energy correlations at steady state for a 1-D model of coupled energy and matter transport. Our aim is to discover -- via theoretical arguments, conjectures, and numerical simulations -- how…

Statistical Mechanics · Physics 2007-05-23 Kevin K. Lin , Lai-Sang Young

We propose a conservative two-dimensional particle model in which particles carry a continuous and classical spin. The model includes standard ferromagnetic interactions between spins of two different particles, and a nonstandard coupling…

The classic paradigms for learning and memory recall focus on strengths of synaptic couplings and how these can be modulated to encode memories. In a previous paper [A. K. Behera, M. Rao, S. Sastry, and S. Vaikuntanathan, Physical Review X…

Disordered Systems and Neural Networks · Physics 2024-10-10 Agnish Kumar Behera , Matthew Du , Uday Jagadisan , Srikanth Sastry , Madan Rao , Suriyanarayanan Vaikuntanathan