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The theory of slow manifolds is an important tool in the study of deterministic dynamical systems, giving a practical method by which to reduce the number of relevant degrees of freedom in a model, thereby often resulting in a considerable…

Statistical Mechanics · Physics 2013-07-01 George W A Constable , Alan J McKane , Tim Rogers

We study classical stochastic systems with discrete states, coupled to switching external environments. For fast environmental processes we derive reduced dynamics for the system itself, focusing on corrections to the adiabatic limit of…

Statistical Mechanics · Physics 2019-03-27 Peter G. Hufton , Yen Ting Lin , Tobias Galla

An approach to analyse the properties of a particle system is to compare it with different processes to understand when one of them is larger than other ones. The main technique for that is coupling, which may not be easy to construct. We…

Probability · Mathematics 2011-02-22 Davide Borrello

Simulating percolation and critical phenomena of labelled species inside films composed of single-component linear homogeneous macromolecules using molecular Monte Carlo method in 3 dimensions, we study dependence of these conducting…

Soft Condensed Matter · Physics 2019-09-05 Yuki Norizoe , Hiroshi Morita

Proceeding from the concept of rational expectations, a new dynamic model of supply and demand in a single market with one supplier, one buyer, and one kind of commodity is developed. Unlike the cob-web dynamic theories with adaptive…

General Physics · Physics 2007-05-23 V. Granik , A. Granik

Search problems at various scales involve a searcher, be it a molecule before reaction or a foraging animal, which performs an intermittent motion. Here we analyze a generic model based on such type of intermittent motion, in which the…

Statistical Mechanics · Physics 2015-05-14 C. Loverdo , O. Bénichou , M. Moreau , R. Voituriez

Molecular dynamics is one of the most commonly used approaches for studying the dynamics and statistical distributions of many physical, chemical, and biological systems using atomistic or coarse-grained models. It is often the case,…

Computational Physics · Physics 2015-06-16 Ben Leimkuhler , Daniel T. Margul , Mark E. Tuckerman

A molecular understanding of how protein function is related to protein structure will require an ability to understand large conformational changes between multiple states. Unfortunately these states are often separated by high free energy…

Biological Physics · Physics 2011-08-08 Juan R. Perilla , Thomas B. Woolf

Molecular Dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively…

Biomolecules · Quantitative Biology 2023-07-20 Diego E. Kleiman , Hassan Nadeem , Diwakar Shukla

Traditional chemical kinetics may be inappropriate to describe chemical reactions in micro-domains involving only a small number of substrate and reactant molecules. Starting with the stochastic dynamics of the molecules, we derive a…

Mathematical Physics · Physics 2009-11-10 D. Holcman , Z. Schuss

We consider stochastic dynamical systems defined by differential equations with a uniform random time delay. The latter equations are shown to be equivalent to deterministic higher-order differential equations: for an $n$-th order equation…

Statistical Mechanics · Physics 2011-10-11 P. L. Krapivsky , J. M. Luck , K. Mallick

Stochasticity plays important roles in reaction systems. Vector fields of probability flux and velocity characterize time-varying and steady-state properties of these systems, including high probability paths, barriers, checkpoints among…

Molecular Networks · Quantitative Biology 2018-12-05 Anna Terebus , Chun Liu , Jie Liang

We use molecular dynamic to simulate the directional growth of binary mixtures. our results compare very well with analitical and experimental results. This opens up the possibility to probe growth situations which are difficult to reach…

Statistical Mechanics · Physics 2007-05-23 B. V. Costa , P. Z. Coura , O. N. Mesquita

Colloidal mixtures represent a versatile model system to study transport in complex environments. They allow for a systematic variation of the control parameters, namely size ratio, total volume fraction and composition. We study the…

We provide a numerical study of the macroscopic model of [3] derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodelling process is very fast, the…

Molecular recognition, which is essential in processing information in biological systems, takes place in a crowded noisy biochemical environment and requires the recognition of a specific target within a background of various similar…

Biomolecules · Quantitative Biology 2010-07-27 Yonatan Savir , Tsvi Tlusty

While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical…

Machine Learning · Statistics 2016-09-08 P. S. Koutsourelakis , Elias Bilionis

Studying systems where many individual bodies in motion interact with one another is a complex and interesting area. Simple mechanisms that may be determined for biological, chemical, or physical reasons can lead to astonishingly complex…

Quantitative Methods · Quantitative Biology 2023-01-03 Cameron McNamee , Renee Reijo Pera

We investigate the time evolution process of one selected (initially prepared by optical pumping) vibrational molecular state, coupled to all other intra-molecular vibrational states of the same molecule, and also to its environment.…

Mesoscale and Nanoscale Physics · Physics 2015-05-13 V. A. Benderskii , E. I. Kats

Predictive dynamical models for marine ecosystems are used for a variety of needs. Due to sparse measurements and limited understanding of the myriad of ocean processes, there is however significant uncertainty. There is model uncertainty…

Computational Engineering, Finance, and Science · Computer Science 2023-06-06 Abhinav Gupta , Pierre F. J. Lermusiaux