English
Related papers

Related papers: Particle-based plasma simulation using a graph neu…

200 papers

Astrophysical observations suggest that magnetic reconnection in relativistic plasmas plays an important role in the acceleration of energetic particles. Modeling this accurately requires numerical schemes capable of addressing large scales…

Plasma Physics · Physics 2025-09-16 K. M. Schoeffler , F. Bacchini , K. Kormann , B. Eichmann , M. E. Innocenti

Machine learning is applied to investigate the phase transition of two-dimensional complex plasmas. The Langevin dynamics simulation is employed to prepare particle suspensions in various thermodynamic states. Based on the resulted particle…

Plasma Physics · Physics 2023-07-25 He Huang , Vladimir Nosenko , Han-Xiao Huang-Fu , Hubertus M. Thomas , Cheng-Ran Du

Computer aided engineering of multi-time-scale plasma systems which exhibit a quasi-steady state solution are challenging due to the large number of time steps required to reach convergence. Machine learning techniques combined with…

Plasma Physics · Physics 2025-10-03 Andrew T. Powis , Domenica Corona Rivera , Alexander Khrabry , Igor D. Kaganovich

We propose a scheme to calculate the reduced plasma frequency of a cylindrical-shaped electron beam flowing inside of a cylindrical tunnel, based on results obtained from Particle-in-cell (PIC) simulations. In PIC simulations, we modulate…

Plasma Physics · Physics 2022-11-23 Tarek Mealy , Robert Marosi , Filippo Capolino

Topological analysis of the magnetic field in simulated plasmas allows the study of various physical phenomena in a wide range of settings. One such application is magnetic reconnection, a phenomenon related to the dynamics of the magnetic…

An electron or electron-positron beam streaming through a plasma is notoriously prone to micro-instabilities. For a dilute ultrarelativistic infinite beam, the dominant instability is a mixed mode between longitudinal two-stream and…

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

We present a simple and computationally efficient coarse-grained and solvent-free model for simulating lipid bilayer membranes. In order to be used in concert with particle-based reaction-diffusion simulations, the model is purely based on…

Biological Physics · Physics 2018-01-31 Mohsen Sadeghi , Thomas R. Weikl , Frank Noé

Supernova remnant (SNR) blast shells can reach the flow speed $v_s = 0.1 c$ and shocks form at its front. Instabilities driven by shock-reflected ion beams heat the plasma in the foreshock, which may inject particles into diffusive…

Astrophysics · Physics 2017-08-02 M. E. Dieckmann , A. Meli , P. K. Shukla , L. O. C. Drury , A. Mastichiadis

Particle-in-Cell (PIC) simulation codes have wide applicability to first-principles modeling of multidimensional nonlinear plasma phenomena, including wake-field accelerators. This review addresses both finite difference and pseudo-spectral…

Plasma Physics · Physics 2014-08-07 Brendan B. Godfrey

Physics-based simulation of mesh based domains remains a challenging task. State-of-the-art techniques can produce realistic results but require expert knowledge. A major bottleneck in many approaches is the step of integrating a potential…

Graphics · Computer Science 2023-11-07 Oshri Halimi , Egor Larionov , Zohar Barzelay , Philipp Herholz , Tuur Stuyck

A promising approach to improve climate-model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data-driven. However, neural networks (NNs) often lead…

Atmospheric and Oceanic Physics · Physics 2021-04-07 Janni Yuval , Paul A. O'Gorman , Chris N. Hill

A constant intensity beam that propagates into a stationary plasma results in a bump-on-tail feature in velocity space. This results in an instability that transfers kinetic energy from the plasma to the electric field. We show that there…

Plasma Physics · Physics 2024-11-26 Lukas Einkemmer

1.5D PIC, relativistic, fully electromagnetic (EM) simulations are used to model EM wave emission generation in the context of solar type III radio bursts. The model studies generation of EM waves by a super-thermal, hot beam of electrons…

Solar and Stellar Astrophysics · Physics 2011-06-10 D. Tsiklauri

In this paper the influence of large-scale decreasing and increasing gradients of the density of magnetized plasma on the relaxation process of a continuously injected relativistic electron beam with an energy of 611 keV ($v_b=0.9c$) and a…

Plasma Physics · Physics 2022-08-30 Vladimir Annenkov , Evgeniia Volchok

Representing the electrodynamics of relativistically drifting particle ensembles in discrete, co-propagating Galilean coordinates enables the derivation of a Particle-in-Cell algorithm that is intrinsically free of the Numerical Cherenkov…

The change of the distribution function of electron-positron pair beams determines whether GeV photons can be produced as secondary radiation from TeV photons. We will discuss the instabilities driven by pair beams. The system of a thermal…

High Energy Astrophysical Phenomena · Physics 2016-01-13 Andreas Kempf , Patrick Kilian , Felix Spanier

At the core of some of the most important problems in plasma physics -- from controlled nuclear fusion to the acceleration of cosmic rays -- is the challenge to describe nonlinear, multi-scale plasma dynamics. The development of reduced…

Plasma Physics · Physics 2022-09-13 E. Paulo Alves , Frederico Fiuza

A possible solution to the unexplained high intensity hard x-ray (HXR) emission observable during solar flares was investigated via 3D fully relativistic, electromagnetic particle-in-cell (PIC) simulations with realistic ion to electron…

Solar and Stellar Astrophysics · Physics 2014-04-09 R. Pechhacker , D. Tsiklauri

This work presents the use of graph learning for the prediction of multi-step experimental outcomes for applications across experimental research, including material science, chemistry, and biology. The viability of geometric learning for…

Machine Learning · Computer Science 2024-08-13 Amanda A. Volk , Robert W. Epps , Jeffrey G. Ethier , Luke A. Baldwin
‹ Prev 1 3 4 5 6 7 10 Next ›