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Soft matter systems are common in nature and make up nearly all the essential components necessary for life, from cells to the organelles within those cells. The ability of these soft materials to deform is crucial for the proper…

Soft Condensed Matter · Physics 2025-12-02 Padmanabha Bose , Smarajit Karmakar

The current work extends the well established approach of Kocks and Mecking by a more realistic description of strain-hardening using an original dislocation density law with a revisited physical understanding of dynamic recovery, without…

Materials Science · Physics 2012-02-28 O. Bouaziz

We present a novel theoretical formulation for performing quantum dynamics in terms of moments within the single-particle description. By expressing the quantum dynamics in terms of increasing orders of moments, instead of single-particle…

Chemical Physics · Physics 2024-01-12 Nicholas Boyer , Christopher Shepard , Ruiyi Zhou , Jianhang Xu , Yosuke Kanai

We present a scaled particle density functional study of two-dimensional binary mixtures of hard convex particles with one or both species being ellipses. In particular, we divide our study into two parts. The first part is devoted to the…

Soft Condensed Matter · Physics 2022-06-07 Yuri Martinez-Raton

Many-body systems relaxing to equilibrium can exhibit complex dynamics even if their steady state is trivial. At low temperatures or high densities their evolution is often dominated by steric hindrances affecting particle motion [1,2,3].…

Statistical Mechanics · Physics 2016-05-10 M. M. Valado , C. Simonelli , M. D. Hoogerland , I. Lesanovsky , J. P. Garrahan , E. Arimondo , D. Ciampini , O. Morsch

Particle filtering is a powerful approximation method that applies to state estimation in nonlinear and non-Gaussian dynamical state-space models. Unfortunately, the approximation error depends exponentially on the system dimension. This…

Optimization and Control · Mathematics 2014-07-02 Francesco Bertoli , Adrian N. Bishop

Common time-explicit numerical methods for kinetic simulations of plasmas in the low-collisions limit fall into two classes of algorithms: momentum conserving and energy conserving. Each has certain drawbacks. The PIC algorithm does not…

Plasma Physics · Physics 2015-06-11 E. G. Evstatiev , B. A. Shadwick

In equilibrium, the collective behaviour of particles interacting via steep, short-ranged potentials is well captured by the virial expansion of the free energy at low density. Here, we extend this approach beyond equilibrium to the case of…

Soft Condensed Matter · Physics 2023-06-21 Yuting Irene Li , Rosalba Garcia-Millan , Michael E. Cates , Étienne Fodor

A generalization of the ABC model, a one-dimensional model of a driven system of three particle species with local dynamics, is introduced, in which the model evolves under either (i) density-conserving or (ii) nonconserving dynamics. For…

Statistical Mechanics · Physics 2015-05-19 A. Lederhendler , D. Mukamel

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

The dynamics of nonlinear conservation laws have long posed fascinating problems. With the introduction of some nonlinearity, e.g. Burgers' equation, discontinuous behavior in the solutions is exhibited, even for smooth initial data. The…

Analysis of PDEs · Mathematics 2017-08-24 Carey Caginalp

Diffusive transport of particles or, more generally, small objects is a ubiquitous feature of physical and chemical reaction systems. In configurations containing confining walls or constrictions transport is controlled both by the…

Statistical Mechanics · Physics 2009-01-22 P. Sekhar Burada , Peter Hanggi , Fabio Marchesoni , Gerhard Schmid , Peter Talkner

The imbalanced Hubbard model features a transition between dynamic regimes depending on the mass ratio and coupling strength between two different particle species. A slowdown of the lighter particle transport can be attributed to an…

Statistical Mechanics · Physics 2025-07-23 Mirko Daumann , Thomas Dahm

In particle-in-cell simulations and some other statistical computations, the representation of modelled distributions with tracked macro-particles can become locally excessive. Merging or resampling dense clusters or highly-populated phase…

Computational Physics · Physics 2020-12-21 Arkady Gonoskov

Studies on random packing of bidispersive particles have shown that such systems can capture the underlying behavior of more complex phenomena found in physics and materials engineering. In industry, bidispersive particles are used to allow…

Statistical Mechanics · Physics 2020-10-22 Carlos Handrey Araujo Ferraz

When very small particles are suspended in a fluid in motion, they tend to follow the flow. How such tracer particles are mixed, transported, and dispersed by turbulent flow has been successfully described by statistical models. Heavy…

Fluid Dynamics · Physics 2023-12-21 J. Bec , K. Gustavsson , B. Mehlig

We investigate a diffusive motion of a system of interacting Brownian particles in quasi-one-dimensional micropores. In particular, we consider a semi-infinite 1D geometry with a partially absorbing boundary and the hard-core inter-particle…

Statistical Mechanics · Physics 2012-03-06 Artem Ryabov , Petr Chvosta

Numerical simulation of numerous mm/cm-sized particles embedded in a gaseous disk has become an important tool in the study of planet formation and in understanding the dust distribution in observed protoplanetary disks. However, the mutual…

Instrumentation and Methods for Astrophysics · Physics 2016-06-22 Chao-Chin Yang , Anders Johansen

We investigate a new sampling scheme aimed at improving the performance of particle filters whenever (a) there is a significant mismatch between the assumed model dynamics and the actual system, or (b) the posterior probability tends to…

Computation · Statistics 2019-03-20 Ömer Deniz Akyıldız , Joaquín Míguez

Density tempering (also called density annealing) is a sequential Monte Carlo approach to Bayesian inference for general state models; it is an alternative to Markov chain Monte Carlo. When applied to state space models, it moves a…

Methodology · Statistics 2022-04-05 David Gunawan , Robert Kohn , Minh Ngoc Tran
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