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Related papers: Exploring helical dynamos with machine learning

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Accretion disc turbulence along with its effect on large-scale magnetic fields plays an important role in understanding disc evolution in general, and the launching of astrophysical jets in particular. Motivated by enabling a comprehensive…

High Energy Astrophysical Phenomena · Physics 2022-04-06 Oliver Gressel , Martin E. Pessah

Magnetised plasma turbulence pervades the universe and is likely to play an important role in a variety of astrophysical settings. Magnetohydrodynamics (MHD) provides the simplest theoretical framework in which phenomenological models for…

Plasma Physics · Physics 2012-07-23 Joanne Mason , Jean C. Perez , Stanislav Boldyrev , Fausto Cattaneo

A hybrid physics-machine learning modeling framework is proposed for the surface vehicles' maneuvering motions to address the modeling capability and stability in the presence of environmental disturbances. From a deep learning perspective,…

Robotics · Computer Science 2025-03-27 Zihao Wang , Jian Cheng , Liang Xu , Lizhu Hao , Yan Peng

It is shown, using results of numerical simulations, and geophysical and solar observations, that the transition from deterministic chaos to hard turbulence in the magnetic field generated by the small-scale MHD dynamos occurs through a…

Fluid Dynamics · Physics 2024-06-26 A. Bershadskii

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation…

Machine Learning · Computer Science 2025-11-11 Minghan Chu , Weicheng Qian

We consider the problem of incompressible, forced, nonhelical, homogeneous, isotropic MHD turbulence with no mean magnetic field. This problem is essentially different from the case with externally imposed uniform mean field. There is no…

Astrophysics · Physics 2008-11-26 A. A. Schekochihin , S. C. Cowley , S. F. Taylor , J. L. Maron , J. C. McWilliams

Local shearing box simulations of stratified magneto rotational turbulence invariably exhibit cyclic field patterns which propagate away from the disc midplane. A common explanation for this is magnetic buoyancy. The recent analysis by Shi…

Earth and Planetary Astrophysics · Physics 2015-05-18 Oliver Gressel

Helical turbulence is thought to provide the key to the generation of large-scale magnetic fields. Turbulence also generically leads to rapidly growing small-scale magnetic fields correlated on the turbulence scales. These two processes are…

Astrophysics · Physics 2008-11-26 Kandaswamy Subramanian

We study a simple magnetohydrodynamical approach in which hydrodynamics and MHD turbulence are coupled in a shell model, with given dynamo constrains in the large scales. We consider the case of a low Prandtl number fluid for which the…

Earth and Planetary Astrophysics · Physics 2015-05-13 Roberto Benzi , Jean-Francois Pinton

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the Multiscale…

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes…

Turbulence plays an important role in astrophysical phenomena, including core-collapse supernovae (CCSN), but current simulations must rely on subgrid models since direct numerical simulation (DNS) is too expensive. Unfortunately, existing…

Computational Physics · Physics 2022-11-30 Platon I. Karpov , Chengkun Huang , Iskandar Sitdikov , Chris L. Fryer , Stan Woosley , Ghanshyam Pilania

A three-dimensional numerical computation of magnetohydrodynamic dynamo behavior is described. The dynamo is mechanically forced with a driving term of the Taylor-Green type. The magnetic field development is followed from negligibly small…

Astrophysics · Physics 2007-05-23 P. D. Mininni , Y. Ponty , D. C. Montgomery , J. -F. Pinton , H. Politano , A. Pouquet

Large eddy simulations (LES) of a lattice Boltzmann magnetohydrodynamic (LB-MHD) model are performed for the unstable magnetized Kelvin-Helmholtz jet instability. This algorithm is an extension of Ansumali et. al. (2004) to MHD in which one…

Plasma Physics · Physics 2018-01-18 Christopher Flint , George Vahala

We present numerical simulations of the growth and saturation of the Kelvin-Helmholtz instability in a compressible fluid layer with and without a weak magnetic field. In the absence of a magnetic field, the instability generates a single…

Astrophysics · Physics 2009-11-13 M. L. Palotti , F. Heitsch , E. G. Zweibel , Y. -M. Huang

Electron magnetohydrodynamic (EMHD) turbulence in two dimensions is studied via high-resolution numerical simulations with a normal diffusivity. The resulting energy spectra asymptotically approach a $k^{-5/2}$ law with increasing $R_B$,…

Plasma Physics · Physics 2009-05-01 C. J. Wareing , R. Hollerbach

We show that a recently proposed [J. Fleischer and P.H. Diamond, {\em Phys. Rev. E}{\bf 58}, R2709 (1998)] one-dimensional Burgers-like model for magnetohydrodynamics (MHD) is in effect identical to existing models for drifting lines and…

Condensed Matter · Physics 2009-10-31 Abhik Basu , Jayanta K Bhattacharjee , Sriram Ramaswamy

Magnetic helicity is an invariant of ideal magnetohydrodynamics (MHD) that encodes information on the topology of magnetic field lines. It has long been appreciated that magnetic topology is an important constraint for the evolution of…

Solar and Stellar Astrophysics · Physics 2020-09-25 David MacTaggart , Chris Prior

In space and astrophysical plasmas, like in planetary magnetospheres, as that of Mercury,energetic electrons are often found near current sheets (CSs), which hints at electron acceleration by magnetic reconnection. Unfortunately, electron…

Plasma Physics · Physics 2018-07-04 X. Zhou , J. Buechner , F. Widmer , P. A. Munoz

Machine-learning (ML) force fields enable large-scale simulations with near-first-principles accuracy at substantially reduced computational cost. Recent work has extended ML force-field approaches to adiabatic dynamical simulations of…

Strongly Correlated Electrons · Physics 2026-01-08 Yunhao Fan , Gia-Wei Chern
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