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Time delay has been incorporated in models to reflect certain physical or biological meaning. The theory of delay differential equations (DDEs), which has seen extensive growth in the last seventy years or so, can be used to examine the…

Dynamical Systems · Mathematics 2022-09-20 Juancho A. Collera

We construct a reduced, data-driven, parameter dependent effective Stochastic Differential Equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian Dynamics Simulations. We use Diffusion Maps…

Augmenting mechanistic ordinary differential equation (ODE) models with machine-learnable structures is an novel approach to create highly accurate, low-dimensional models of engineering systems incorporating both expert knowledge and…

Dynamical Systems · Mathematics 2022-06-22 Sandor Beregi , David A. W. Barton , Djamel Rezgui , Simon A. Neild

The Dynamical Graph Grammar (DGG) formalism can describe complex system dynamics with graphs that are mapped into a master equation. An exact stochastic simulation algorithm may be used, but it is slow for large systems. To overcome this…

Quantitative Methods · Quantitative Biology 2024-07-16 Eric Medwedeff , Eric Mjolsness

Power flow analysis plays a fundamental and critical role in the energy management system (EMS). It is required to well accommodate large and complex power system. To achieve a high performance and accurate power flow analysis, a graph…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-20 Chen Yuan , Yi Lu , Wei Feng , Guangyi Liu , Renchang Dai , Yachen Tang , Zhiwei Wang

Discrete-time fractional-order dynamical systems (DT-FODS) have found innumerable applications in the context of modeling spatiotemporal behaviors associated with long-term memory. Applications include neurophysiological signals such as…

Optimization and Control · Mathematics 2021-10-05 Sarthak Chatterjee , Sérgio Pequito

Data-driven modeling of dynamical systems is a crucial area of machine learning. In many scenarios, a thorough understanding of the model's behavior becomes essential for practical applications. For instance, understanding the behavior of a…

Machine Learning · Computer Science 2025-04-14 Krzysztof Kacprzyk , Mihaela van der Schaar

Neural Operators (NOs) provide a powerful framework for computations involving physical laws that can be modelled by (integro-) partial differential equations (PDEs), directly learning maps between infinite-dimensional function spaces that…

Machine Learning · Computer Science 2025-09-18 Gianluca Fabiani , Hannes Vandecasteele , Somdatta Goswami , Constantinos Siettos , Ioannis G. Kevrekidis

Two-dimensional electronic spectroscopy (2DES) provides rich information about how the electronic states of molecules, proteins, and solid-state materials interact with each other and their surrounding environment. Atomistic molecular…

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and…

Equation-free approaches have been proposed in recent years for the computational study of multiscale phenomena in engineering problems where evolution equations for the coarse-grained, system-level behavior are not explicitly available. In…

Dynamical Systems · Mathematics 2007-05-23 Yu Zou , Ioannis G. Kevrekidis , Roger G. Ghanem

A filtered density function (FDF) model based on deep neural network (DNN), termed DNN-FDF, is introduced for large eddy simulation (LES) of turbulent flows involving conserved scalar transport. The primary objectives of this study are to…

Fluid Dynamics · Physics 2023-10-02 Shubhangi Bansude , Reza Sheikhi

The electrochemical reduction of atmospheric CO$_2$ into high-energy molecules with renewable energy is a promising avenue for energy storage that can take advantage of existing infrastructure especially in areas where sustainable…

Physical systems whose dynamics are governed by partial differential equations (PDEs) find applications in numerous fields, from engineering design to weather forecasting. The process of obtaining the solution from such PDEs may be…

Machine Learning · Computer Science 2022-09-21 Pratyush Bhatt , Yash Kumar , Azzeddine Soulaimani

Bifurcation analysis collects techniques for characterizing the dependence of certain classes of solutions of a dynamical system on variations in problem parameters. Common solution classes of interest include equilibria and periodic…

Dynamical Systems · Mathematics 2025-11-05 Harry Dankowicz , Jan Sieber

In complex physical systems, conventional differential equations often fall short in capturing non-local and memory effects, as they are limited to local dynamics and integer-order interactions. This study introduces a stepwise data-driven…

Computational Physics · Physics 2025-05-30 Xiangnan Yu , Hao Xu , Zhiping Mao , HongGuang Sun , Yong Zhang , Dongxiao Zhang , Yuntian Chen

Bifurcation theory is the usual analytic approach to study the parameter space of a dynamical system. Despite the great power of prediction of these techniques, fundamental limitations appear during the study of a given problem. Nonlinear…

Chaotic Dynamics · Physics 2023-10-02 Alexandre Wagemakers , Alvar Daza , Miguel A. F. Sanjuán

The dynamics of individual DNA molecules in semidilute solutions undergoing planar extensional flow is simulated using a multi-particle Brownian dynamics algorithm, which incorporates hydrodynamic and excluded volume interactions in the…

Soft Condensed Matter · Physics 2020-07-03 Chandi Sasmal , Kai-Wen Hsiao , Charles M. Schroeder , J. Ravi Prakash

Bifurcations mark qualitative changes of long-term behavior in dynamical systems and can often signal sudden ("hard") transitions or catastrophic events (divergences). Accurately locating them is critical not just for deeper understanding…

Machine Learning · Computer Science 2024-06-18 Yorgos M. Psarellis , Themistoklis P. Sapsis , Ioannis G. Kevrekidis

Externally driven dense packings of particles can exhibit nonlinear wave phenomena that are not described by effective medium theory or linearized approximate models. Such nontrivial wave responses can be exploited to design…

Soft Condensed Matter · Physics 2024-11-26 Atoosa Parsa , James Bagrow , Corey S. O'Hern , Rebecca Kramer-Bottiglio , Josh Bongard