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We present a non-iterative algorithm, FloatStepper, for coupling the motion of a rigid body and an incompressible fluid in computational fluid dynamics (CFD) simulations. The purpose of the algorithm is to remove the so-called added mass…

Fluid Dynamics · Physics 2024-04-22 Johan Roenby , Sithik Aliyar , Henrik Bredmose

Molecular dynamics (MD) simulations play a crucial role in resolving the underlying conformational dynamics of molecular systems. However, their capability to correctly reproduce and predict dynamics in agreement with experiments is limited…

Chemical Physics · Physics 2025-05-19 Ivan Gilardoni , Valerio Piomponi , Thorben Fröhlking , Giovanni Bussi

Dissipative Particle Dynamics (DPD) is a popular simulation model for investigating hydrodynamic behavior of systems with non-negligible equilibrium thermal fluctuations. DPD employs soft core repulsive interactions between the system…

Statistical Mechanics · Physics 2016-03-23 Oded Farago , Niels Grønbech-Jensen

Time-domain simulations are crucial for ensuring power system stability and avoiding critical scenarios that could lead to blackouts. The next-generation power systems require a significant increase in the computational cost and complexity…

Systems and Control · Electrical Eng. & Systems 2025-06-26 Ignasi Ventura Nadal , Jochen Stiasny , Spyros Chatzivasileiadis

The particle-in-cell numerical method of plasma physics balances a trade-off between computational cost and intrinsic noise. Inference on data produced by these simulations generally consists of binning the data to recover the particle…

Plasma Physics · Physics 2022-02-03 John Donaghy , Kai Germaschewski

We describe a parallelised version of the MOLDY molecular dynamics program. This Fortran code is aimed at systems which may be described by short-range potentials and specifically those which may be addressed with the embedded atom method.…

Materials Science · Physics 2015-05-28 GJ Ackland , K D'Mellow , SL Daraszewicz , DJ Hepburn , M Uhrin , K. Stratford

We present a data-driven pipeline for model building that combines interpretable machine learning, hydrodynamic theories, and microscopic models. The goal is to uncover the underlying processes governing nonlinear dynamics experiments. We…

Soft Condensed Matter · Physics 2024-04-22 Jonathan Colen , Alexis Poncet , Denis Bartolo , Vincenzo Vitelli

We investigate the properties of an impurity immersed in an ensemble of spin-polarized fermions confined in a tight quantum wire. We use a non-perturbative variational approach that accounts for virtual transverse excitations and…

Quantum Gases · Physics 2025-09-08 Lovro Anto Barišić , Giuliano Orso , Frédéric Chevy , Kris Van Houcke

We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized Poisson Boltzmann equation, for molecules represented as non-overlapping spherical cavities.…

Biomolecules · Quantitative Biology 2016-09-27 Lisa E. Feldberg , David H. Brookes , Eng-Hui Yap , Elizabeth Jurrus , Nathan Baker , Teresa Head-Gordon

A multifidelity method for the nonlinear propagation of uncertainties in the presence of stochastic accelerations is presented. The proposed algorithm treats the uncertainty propagation (UP) problem by separating the propagation of the…

Numerical Analysis · Mathematics 2025-08-19 Alberto Fossà , Roberto Armellin , Emmanuel Delande , Francesco Sanfedino

The main objective of this paper is a study of the asymptotic behavior of distributional solutions to the one-dimensional repulsive pressureless Euler-Poisson system. The system is a model for the dynamics of a mass distribution evolving on…

Analysis of PDEs · Mathematics 2026-05-08 Nicholas Biglin , Joseph Crachiola , Jack Curtis , Thomas Kunz , Omkar Maralappanavar , Adrian Tudorascu

Open quantum systems host a wide range of intriguing phenomena, yet their simulation on well-controlled quantum devices is challenging, owing to the exponential growth of the Hilbert space and the inherently non-unitary nature of the…

Deep learning has achieved great success in modeling dynamical systems, providing data-driven simulators to predict complex phenomena, even without known governing equations. However, existing models have two major limitations: their narrow…

Machine Learning · Computer Science 2024-10-16 Razmik Arman Khosrovian , Takaharu Yaguchi , Hiroaki Yoshimura , Takashi Matsubara

In a recent paper we have shown how to learn controllers for unknown linear systems using finite-sized noisy data by solving linear matrix inequalities. In this note we extend this approach to deal with unknown nonlinear polynomial systems…

Optimization and Control · Mathematics 2020-11-17 Meichen Guo , Claudio De Persis , Pietro Tesi

A new Bayesian software package for the analysis of pulsar timing data is presented in the form of TempoNest which allows for the robust determination of the non-linear pulsar timing solution simultaneously with a range of additional…

Instrumentation and Methods for Astrophysics · Physics 2013-12-04 Lindley Lentati , Paul Alexander , Michael P. Hobson , Farhan Feroz , Rutger van Haasteren , Kejia Lee , Ryan M. Shannon

This article presents new algorithms for massively parallel granular dynamics simulations on distributed memory architectures using a domain partitioning approach. Collisions are modelled with hard contacts in order to hide their…

Computational Engineering, Finance, and Science · Computer Science 2015-01-26 Tobias Preclik , Ulrich Rüde

The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic…

Plasma Physics · Physics 2021-06-14 Alexander Engel , Graeme Smith , Scott E. Parker

Identification of the particle interaction potential is a challenging and important task in dusty plasma, colloids, and smart materials as it allows the characterization of structure formation and helps predict phase transitions. With the…

A new open source tool for fluid simulation of multi-component plasmas is presented, based on a flexible software design that is applicable to scientific simulations in a wide range of fields. This design enables the same code to be…

Plasma Physics · Physics 2023-06-21 Ben Dudson , Mike Kryjak , Hasan Muhammed , Peter Hill , John Omotani

Recent developments in vortex particle methods for simulating three-dimensional incompressible flows are presented. A lightweight, dynamic Large-Eddy Simulation model is tested, featuring a dynamic procedure that relies solely on Lagrangian…

Fluid Dynamics · Physics 2026-01-13 Flavio A. C. Martins , Alexander van Zuijlen , Carlos J. Simao Ferreira