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The interest in non-Markovian dynamics within the complex systems community has recently blossomed, due to a new wealth of time-resolved data pointing out the bursty dynamics of many natural and human interactions, manifested in an…

Statistical Mechanics · Physics 2019-04-25 Antoine Moinet , Michele Starnini , Romualdo Pastor-Satorras

We study the transport properties of continuous-time quantum walks (CTQW) over finite two-dimensional structures with a given number of randomly placed bonds and with different aspect ratios (AR). Here, we focus on the transport from, say,…

Quantum Physics · Physics 2015-06-17 Anastasiia Anishchenko , Alexander Blumen , Oliver Muelken

Random walks provide a simple conventional model to describe various transport processes, for example propagation of heat or diffusion of matter through a medium. However, in many practical cases the medium is highly irregular due to…

Probability · Mathematics 2019-06-10 L. V. Bogachev

Discriminative Random Walks (DRWs) are a simple yet powerful tool for semi-supervised node classification, but their theoretical foundations remain fragmentary. We revisit DRWs through the lens of information geometry, treating the family…

Machine Learning · Statistics 2026-02-10 Masanari Kimura

The continuous time random walk (CTRW) underlies many fundamental processes in non-equilibrium statistical physics. When the jump length of CTRW obeys a power-law distribution, its corresponding Fokker-Planck equation has space fractional…

Numerical Analysis · Mathematics 2017-06-28 Yanyan Yu , Weihua Deng , Yujiang Wu

In co-manipulative continuum robots (CCRs), multiple continuum arms cooperate by grasping a common flexible object, forming a closed-chain deformable mechanical system. The closed-chain coupling induces strong dynamic interactions and…

Robotics · Computer Science 2026-04-07 Rana Danesh , Farrokh Janabi-Sharifi , Farhad Aghili

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

Reactive transport in saturated/unsaturated porous media is numerically upscaled to the space-time scale of a hypothetical measurement through coarse-grained space-time (CGST) averages. The reactive transport is modeled at the fine-grained…

Numerical Analysis · Mathematics 2023-03-30 Nicolae Suciu , Florin A. Radu , Iuliu S. Pop

In recent years, several experiments highlighted a new type of diffusion anomaly, which was called Brownian yet non-Gaussian diffusion. In systems displaying this behavior, the mean squared displacement of the diffusing particles grows…

Statistical Mechanics · Physics 2023-08-01 Adrian Pacheco-Pozo , Igor M. Sokolov

Continuous time quantum walks (CTQW) do not necessarily perform better than their classical counterparts, the continuous time random walks (CTRW). For one special graph, where a recent analysis showed that in a particular direction of…

Quantum Physics · Physics 2009-11-10 Oliver Muelken , Alexander Blumen

Continuous Time Random Walk models (CTRW) of anomalous diffusion are studied, where the anomalous exponent $\beta(x) \in (0,1)$ varies in space. This type of situation occurs e.g. in biophysics, where the density of the intracellular matrix…

Statistical Mechanics · Physics 2018-03-13 Peter Straka

We study the dynamics of a deterministic walk confined in a narrow two-dimensional space randomly filled with point-like targets. At each step, the walker visits the nearest target not previously visited. Complex dynamics is observed at…

Disordered Systems and Neural Networks · Physics 2009-11-13 Denis Boyer

Many theoretical treatments of transport in heterogeneous Darcy flows consider advection only. When local-scale dispersion is neglected, flux-weighting persists over time; mean Lagrangian and Eulerian flow velocity distributions relate…

Fluid Dynamics · Physics 2024-07-25 Lian Zhou , Scott K. Hansen

In recent years a huge interdisciplinary field has emerged which is devoted to the complex dynamics of anomalous transport with long-time memory and non-markovian features. It was found that the framework of fractional calculus and its…

Probability · Mathematics 2022-04-27 Thomas M. Michelitsch , Federico Polito , Alejandro P. Riascos

We present a hybrid approach to groundwater transport modeling, "CTRW-on-a-streamline", that allows continuous-time random walk (CTRW) particle tracking on large-scale, explicitly-delineated heterogeneous groundwater velocity fields. The…

Computational Physics · Physics 2020-12-02 Scott K. Hansen , Brian Berkowitz

In this paper, we introduce a novel framework using inhomogeneous Branching Random Walks (BRWs) to model growth processes, specifically introducing genealogy-dependence in branching rates and displacement distributions to model phenomena…

Populations and Evolution · Quantitative Biology 2025-12-11 Lauren Ajax , Beatrice Durham , Pratima Hebbar , Cade Johnson , Jiayi Zhang

Gated recurrent units (GRUs) are specialized memory elements for building recurrent neural networks. Despite their incredible success on various tasks, including extracting dynamics underlying neural data, little is understood about the…

Machine Learning · Computer Science 2021-07-30 Ian D. Jordan , Piotr Aleksander Sokol , Il Memming Park

We develop a time domain random walk approach for conservative solute transport in heterogeneous media where medium properties vary over a distribution of length scales. The spatial transition lengths are equal to the heterogeneity length…

Fluid Dynamics · Physics 2018-09-05 Tomás Aquino , Marco Dentz

When greedy search algorithms encounter a local minima or plateau, the search typically devolves into a breadth-first search (BrFS), or a local search technique is used in an attempt to find a way out. In this work, we formally analyze the…

Artificial Intelligence · Computer Science 2024-06-25 Daniel Platnick , Richard Anthony Valenzano

Cyclic and randomized stepsizes are widely used in the deep learning practice and can often outperform standard stepsize choices such as constant stepsize in SGD. Despite their empirical success, not much is currently known about when and…

Machine Learning · Statistics 2023-08-30 Mert Gürbüzbalaban , Yuanhan Hu , Umut Şimşekli , Lingjiong Zhu
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