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Metastable condensed matter typically fluctuates about local energy minima at the femtosecond time scale before transitioning between local minima after nanoseconds or microseconds. This vast scale separation limits the applicability of…

Computational Physics · Physics 2017-11-22 Brittan A Farmer , Mitchell Luskin , Petr Plecháč , Gideon Simpson

Behavior of the mixture of particles and dimers moving with different jump rates at reconstructed surfaces is described. Collective diffusion coefficient is calculated by the variational approach. Anisotropy of the collective particle…

Statistical Mechanics · Physics 2014-05-12 Marcin Mińkowski , Magdalena A. Załuska Kotur

This paper introduces LABurst, a general technique for identifying key moments, or moments of high impact, in social media streams without the need for domain-specific information or seed keywords. We leverage machine learning to model…

Social and Information Networks · Computer Science 2015-08-04 Cody Buntain , Jimmy Lin , Jennifer Golbeck

We study memory based random walk models to understand diffusive motion in crowded heterogeneous environment. The models considered are non-Markovian as the current move of the random walk models is determined by randomly selecting a move…

Statistical Mechanics · Physics 2018-08-01 Sabeeha Hasnain , Upendra Harbola , Pradipta Bandyopadhyay

Many disordered systems show a superdiffusive dynamics, intermediate between the diffusive one, typical of a classical stochastic process, and the so called ballistic behaviour, which is generally expected for the spreading in a quantum…

Mathematically modelling diffusive and advective transport of particles in heterogeneous layered media is important to many applications in computational, biological and medical physics. While deterministic continuum models of such…

Computational Physics · Physics 2024-09-16 Elliot J. Carr

When recording the movement of individual animals, cells or molecules one will often observe changes in their diffusive behaviour at certain points in time along their trajectory. In order to capture the different diffusive modes assembled…

Statistical Mechanics · Physics 2024-10-21 Henrik Seckler , Ralf Metzler

Heterogeneous dynamics commonly emerges in anomalous diffusion with intermittent transitions of diffusion states but proves challenging to identify using conventional statistical methods. To effectively capture these transient changes of…

Biological Physics · Physics 2024-01-24 Xiang Qu , Yi Hu , Wenjie Cai , Yang Xu , Hu Ke , Guolong Zhu , Zihan Huang

Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in…

Emerging Technologies · Computer Science 2018-12-14 Vahid Jamali , Arman Ahmadzadeh , Wayan Wicke , Adam Noel , Robert Schober

In the current work we present a new modelling approach for simulating meso-scopic phenomena related to lubrication of the piston ring-cylinder liner contact. Our geometry allows a variable confinement gap and a varying amount of lubricant…

Soft Condensed Matter · Physics 2016-12-28 Konstantinos Gkagkasa , Veerapandian Ponnuchamyb , Miljan Dašić , Igor Stanković

We perform extensive numerical simulations of a paradigmatic model glass former, the hard-sphere fluid with 10% polydispersity. We sample from the ensemble of trajectories with fixed observation time, whereby single trajectories are…

Statistical Mechanics · Physics 2020-01-28 Matteo Campo , Thomas Speck

We study colloidal particle dynamics of a model glass system using confocal and fluorescence microscopy as the sample evolves from a hard-sphere glass to a liquid with attractive interparticle interactions. The transition from hard-sphere…

Soft Condensed Matter · Physics 2015-05-13 Andrzej Latka , Yilong Han , Ahmed M. Alsayed , Andrew B. Schofield , A. G. Yodh , Piotr Habdas

Molecular representation learning has shown great success in advancing AI-based drug discovery. The core of many recent works is based on the fact that the 3D geometric structure of molecules provides essential information about their…

Machine Learning · Computer Science 2024-10-23 Jiying Zhang , Zijing Liu , Yu Wang , Yu Li

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the…

Fluid Dynamics · Physics 2021-01-28 Wai Hong Ronald Chan , Michael S. Dodd , Perry L. Johnson , Parviz Moin

Event-driven molecular dynamics is a valuable tool in condensed and soft matter physics when particles can be modeled as hard objects or more generally if their interaction potential can be modeled in a stepwise fashion. Hard spheres model…

Computational Physics · Physics 2015-05-19 Cristiano De Michele

Discovering nonlinear differential equations that describe system dynamics from empirical data is a fundamental challenge in contemporary science. Here, we propose a methodology to identify dynamical laws by integrating denoising techniques…

Machine Learning · Computer Science 2023-05-04 Kevin Egan , Weizhen Li , Rui Carvalho

We explore situations in which certain stochastic and high-dimensional deterministic systems behave effectively as low-dimensional dynamical systems. We define and study moment maps, maps on spaces of low-order moments of evolving…

Other Condensed Matter · Physics 2016-08-31 D. Barkley , I. G. Kevrekidis , A. M. Stuart

Modeling dynamical systems is important in many disciplines, e.g., control, robotics, or neurotechnology. Commonly the state of these systems is not directly observed, but only available through noisy and potentially high-dimensional…

Machine Learning · Statistics 2014-10-29 Niklas Wahlström , Thomas B. Schön , Marc Peter Deisenroth

We study the transport dynamics of matter-waves in the presence of disorder and nonlinearity. An atomic Bose-Einstein condensate that is localized in a quasiperiodic lattice in the absence of atom-atom interaction shows instead a slow…

Disordered Systems and Neural Networks · Physics 2015-02-27 E. Lucioni , B. Deissler , L. Tanzi , G. Roati , M. Modugno , M. Zaccanti , M. Larcher , F. Dalfovo , M. Inguscio , G. Modugno

Methods to extract information from the tracking of mobile objects/particles have broad interest in biological and physical sciences. Techniques based on simple criteria of proximity in time-consecutive snapshots are useful to identify the…

Data Analysis, Statistics and Probability · Physics 2015-03-13 M. Chertkov , L. Kroc , F. Krzakala , M. Vergassola , L. Zdeborová
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