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A weak wave turbulence theory is developed for two-dimensional (2D) magnetohydrodynamics (MHD). We derive and analyze the kinetic equation describing the three-wave interactions of pseudo-Alfv\'en waves. Our analysis is greatly helped by…

等离子体物理 · 物理学 2015-06-12 Natalia Tronko , Sergey V. Nazarenko , Sebastien Galtier

We present a virtual element method (VEM) for the numerical approximation of the electromagnetics subsystem of the resistive magnetohydrodynamics (MHD) model in two spatial dimensions. The major advantages of the virtual element method…

数值分析 · 数学 2020-04-27 S. Naranjo Alvarez , V. A. Bokil , V. Gyrya , G. Manzini

Due to advances in computer hardware and new algorithms, it is now possible to perform highly accurate many-body simulations of realistic materials with all their intrinsic complications. The success of these simulations leaves us with a…

强关联电子 · 物理学 2018-05-14 Huihuo Zheng , Hitesh J. Changlani , Kiel T. Williams , Brian Busemeyer , Lucas K. Wagner

Many inverse problems in nuclear fusion and high-energy astrophysics research, such as the optimization of tokamak reactor geometries or the inference of black hole parameters from interferometric images, necessitate high-dimensional…

机器学习 · 计算机科学 2025-05-09 Jonathan Gorard , Ammar Hakim , Hong Qin , Kyle Parfrey , Shantenu Jha

The applicability of relativistic magnetohydrodynamics (RMHD) and its generalization to two-fluid models (including the Hall and inertial effects) is systematically investigated by using the method of dominant balance in the two-fluid…

等离子体物理 · 物理学 2024-12-10 Shuntaro Yoshino , Makoto Hirota , Yuji Hattori

In this paper we consider the one dimensional quantum hydrodynamics (QHD) system, with a genuine hydrodynamic approach. The global existence of weak solutions with large data has been obtained in [2, 3], in several space dimensions, by…

偏微分方程分析 · 数学 2021-01-26 Paolo Antonelli , Pierangelo Marcati , Hao Zheng

Bayesian inverse problems highly rely on efficient and effective inference methods for uncertainty quantification (UQ). Infinite-dimensional MCMC algorithms, directly defined on function spaces, are robust under refinement of physical…

统计计算 · 统计学 2019-05-22 Shiwei Lan

Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head-on. Therefore, developing reduced dimensionality representations that encapsulate…

量子物理 · 物理学 2024-07-09 Senwei Liang , Karol Kowalski , Chao Yang , Nicholas P. Bauman

Recurrent neural networks can be large and compute-intensive, yet many applications that benefit from RNNs run on small devices with very limited compute and storage capabilities while still having run-time constraints. As a result, there…

机器学习 · 计算机科学 2020-08-14 Urmish Thakker , Jesse Beu , Dibakar Gope , Ganesh Dasika , Matthew Mattina

Hall magnetohydrodynamics (MHD) properties near a two-dimensional (2D) X-type magnetic neutral line in the steady state are considered via heuristic and rigorous developments. Upon considering the steady-state as the asymptotic limit of the…

等离子体物理 · 物理学 2009-11-13 Bhimsen K. Shivamoggi

This paper considers magnetohydrodynamics (MHD) and some of its applications from the perspective of differential geometry, considering the dynamics of an ideal fluid flow and magnetic field on a general three-dimensional manifold, equipped…

流体动力学 · 物理学 2023-07-26 Andrew D. Gilbert , Jacques Vanneste

Dimensionality reduction, a form of compression, can simplify representations of information to increase efficiency and reveal general patterns. Yet, this simplification also forfeits information, thereby reducing representational capacity.…

A promising approach to investigating high-dimensional problems is to identify their intrinsically low-dimensional features, which can be achieved through recently developed techniques for effective low-dimensional representation of…

偏微分方程分析 · 数学 2025-06-02 Zeyu Jin , Ruo Li

In this tutorial, a derivation of magnetohydrodynamics (MHD) valid beyond the usual ideal gas approximation is presented. Non-equilibrium thermodynamics is used to obtain conservation equations and linear constitutive relations. When…

等离子体物理 · 物理学 2025-04-21 Jarett LeVan , Scott Baalrud

This paper presents an overview and introduction to Smoothed Particle Hydrodynamics and Magnetohydrodynamics in theory and in practice. Firstly, we give a basic grounding in the fundamentals of SPH, showing how the equations of motion and…

天体物理仪器与方法 · 物理学 2010-12-22 Daniel J. Price

An important task for many if not all the scientific domains is efficient knowledge integration, testing and codification. It is often solved with model construction in a controllable computational environment. In spite of that, the…

分子网络 · 定量生物学 2018-11-06 Emilia M. Wysocka , Valery Dzutsati , Tirthankar Bandyopadhyay , Laura Condon , Sahil Garg

World is looking for clean and renewable energy sources that do not pollute the environment, in an attempt to reduce greenhouse gas emissions that contribute to global warming. Wind energy has significant potential to not only reduce…

机器学习 · 计算机科学 2024-01-31 Alif Bin Abdul Qayyum , Xihaier Luo , Nathan M. Urban , Xiaoning Qian , Byung-Jun Yoon

This experimental study analyzes the relationship between the dimensionality of turbulence and the upscale or downscale nature of its energy transfers. We do so by forcing low-$Rm$ magnetohydrodynamic (MHD) turbulence in a confined channel,…

流体动力学 · 物理学 2018-06-12 N. T. Baker , A. Pothérat , L. Davoust , F. Debray

In this paper we propose a novel thermodynamically compatible finite volume scheme for the numerical solution of the equations of magnetohydrodynamics (MHD) in one and two space dimensions. As shown by Godunov in 1972, the MHD system can be…

数值分析 · 数学 2023-01-23 Saray Busto , Michael Dumbser

We provide a systematic derivation of boundary layer models in magnetohydrodynamics (MHD), through an asymptotic analysis of the incompressible MHD system. We recover classical linear models, related to the famous Hartmann and Shercliff…

偏微分方程分析 · 数学 2017-06-28 David Gerard-Varet , Marco Prestipino