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We present a coarse-graining strategy for reducing the number of particle species in mixtures to achieve a simpler system with higher diffusion while preserving the total particle number and characteristic dynamic features. As a system of…

Soft Condensed Matter · Physics 2020-09-16 Thomas Heinemann , YounJoon Jung

In an effort to better understand collisionless relaxation processes in gravitational systems, we investigate one-dimensional models. Taking advantage of a Hermite-Legendre expansion of relevant distribution functions, we present analytical…

Astrophysics of Galaxies · Physics 2019-06-12 Eric I. Barnes , Robert J. Ragan

Coarse-grained descriptions can be used to account for physical processes in which information is lost or not entirely accessible. In this paper, we start by proposing a connection between effective, coarse-grained descriptions of quantum…

Mathematical approaches from dynamical systems theory are used in a range of fields. This includes biology where they are used to describe processes such as protein-protein interaction and gene regulatory networks. As such networks increase…

Numerical Analysis · Mathematics 2020-11-05 Edgar Herrera-Delgado , James Briscoe , Peter Sollich

Modeling of DNA-protein interactions is a complex process involving many important time and length scales. This can be facilitated through the use of coarse-grained models which reduce the number of degrees of freedom and allow efficient…

Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this traditional approach is mathematically cumbersome and only…

We develop a general framework for the discussion of detailed balance and analyse its microscopic background. We find that there should be two additions to the well-known $T$- or $PT$-invariance of the microscopic laws of motion: 1.…

Statistical Mechanics · Physics 2014-10-09 A. N. Gorban

We consider linear reaction systems with slow and fast reactions, which can be interpreted as master equations or Kolmogorov forward equations for Markov processes on a finite state space. We investigate their limit behavior if the fast…

Mathematical Physics · Physics 2021-06-23 Alexander Mielke , Artur Stephan

Slow dynamic nonlinearity is ubiquitous amongst brittle materials, such as rocks and concrete, with cracked microstructures. A defining feature of the behavior is the logarithmic-in-time recovery of stiffness after a mechanical…

Soft Condensed Matter · Physics 2020-01-15 John Y. Yoritomo , Richard L. Weaver

Networks are a widely used and efficient paradigm to model real-world systems where basic units interact pairwise. Many body interactions are often at play, and cannot be modelled by resorting to binary exchanges. In this work, we consider…

Adaptation and Self-Organizing Systems · Physics 2020-06-03 Timoteo Carletti , Duccio Fanelli , Sara Nicoletti

We present a theoretical approach to scale the artificially fast dynamics of simulated coarse-grained polymer liquids down to its realistic value. As coarse-graining affects entropy and dissipation, two factors enter the rescaling:…

Soft Condensed Matter · Physics 2015-05-27 I. Y. Lyubimov , J. McCarty , A. Clark , M. G. Guenza

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done…

Computational Physics · Physics 2022-11-30 Kirill Shmilovich , Marc Stieffenhofer , Nicholas E. Charron , Moritz Hoffmann

Very often, models in biology, chemistry, physics, and engineering are systems of polynomial or power-law ordinary differential equations, arising from a reaction network. Such dynamical systems can be generated by many different reaction…

Dynamical Systems · Mathematics 2020-01-01 Gheorghe Craciun , Jiaxin Jin , Polly Y. Yu

High-dimensional recordings of dynamical processes are often characterized by a much smaller set of effective variables, evolving on low-dimensional manifolds. Identifying these latent dynamics requires solving two intertwined problems:…

Machine Learning · Computer Science 2026-01-21 Manuel Hinz , Maximilian Mauel , Patrick Seifner , David Berghaus , Kostadin Cvejoski , Ramses J. Sanchez

We describe a phase transition that gives rise to structurally non-trivial states in a two-dimensional ordered network of particles connected by harmonic bonds. Monte Carlo simulations reveal that the network supports, apart from the…

Soft Condensed Matter · Physics 2017-04-05 Saswati Ganguly , Jürgen Horbach , Peter Sollich , Parswa Nath , Smarajit Karmakar , Surajit Sengupta

The study of granular crystals, metamaterials that consist of closely packed arrays of particles that interact elastically, is a vibrant area of research that combines ideas from disciplines such as materials science, nonlinear dynamics,…

Pattern Formation and Solitons · Physics 2017-10-11 C. Chong , Mason A. Porter , P. G. Kevrekidis , C. Daraio

Mechanically induced folding of passive cross-linkers is a fundamental biological phenomenon. A typical example is a conformational change in myosin II responsible for the power-stroke in skeletal muscles. In this paper we present an…

Biological Physics · Physics 2017-09-14 Matthieu Caruel , Jean-Marc Allain , Lev Truskinovsky

The dynamic properties of a classical tracer particle in a random, disordered medium are investigated close to the localization transition. For Lorentz models obeying Newtonian and diffusive motion at the microscale, we have performed…

Soft Condensed Matter · Physics 2008-04-29 Felix Höfling , Tobias Munk , Erwin Frey , Thomas Franosch

Mass action type deterministic kinetic models of ion channels are usually constructed in such a way as to obey the principle of detailed balance (or, microscopic reversibility) for two reasons: first, the authors aspire to have models…

Molecular Networks · Quantitative Biology 2011-09-21 I. Nagy , J. Tóth

We explore the dynamics of a tracer in an active particle harmonic chain, investigating the influence of interactions. Our analysis involves calculating mean-squared displacements (MSD) and space-time correlations through Green's function…

Statistical Mechanics · Physics 2026-04-07 Subhajit Paul , Abhishek Dhar , Debasish Chaudhuri
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