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The accurate prediction of occurrence and strength of kinetic instabilities in plasmas remains a significant challenge in nuclear fusion research. To accurately capture the plasmas dynamics one is required to solve the Vlasov equation for…

Plasma Physics · Physics 2024-04-30 Rostislav-Paul Wilhelm , Jan Eifert , Manuel Torrilhon

Global Sensitivity Analysis (GSA) is the study of the influence of any given inputs on the outputs of a model. In the context of engineering design, GSA has been widely used to understand both individual and collective contributions of…

Machine Learning · Statistics 2024-03-06 Yigitcan Comlek , Liwei Wang , Wei Chen

The Vlasov-Poisson system describes the time evolution of a plasma in the so-called collisionless regime. The investigation of a high-temperature plasma that is influenced by an exterior magnetic field is one of the most significant aspects…

Optimization and Control · Mathematics 2024-07-11 Jan Bartsch , Patrik Knopf , Stefania Scheurer , Jörg Weber

A collisionless plasma is modeled by the Vlasov-Poisson system in three space dimensions. A fixed background of positive charge, which is independent of time and space, is assumed. The situation in which mobile negative ions balance the…

Analysis of PDEs · Mathematics 2015-05-14 Stephen Pankavich

In statistical applications, it is common to encounter parameters supported on a varying or unknown dimensional space. Examples include the fused lasso regression, the matrix recovery under an unknown low rank, etc. Despite the ease of…

Methodology · Statistics 2022-10-04 Maoran Xu , Hua Zhou , Yujie Hu , Leo L. Duan

Many collective systems exist in nature far from equilibrium, ranging from cellular sheets up to flocks of birds. These systems reflect a form of active matter, whereby individual material components have internal energy. Under specific…

Soft Condensed Matter · Physics 2023-04-17 Namid R. Stillman , Silke Henkes , Roberto Mayor , Gilles Louppe

In this paper, we propose a novel sequential data-driven method for dealing with equilibrium based chemical simulations, which can be seen as a specific machine learning approach called active learning. The underlying idea of our approach…

Machine Learning · Statistics 2024-01-26 Mary Savino , Céline Lévy-Leduc , Marc Leconte , Benoit Cochepin

The stability of an expanding parton plasma is analyzed within quasi-particle models. The effective mass of the parton is calculated self-consistently from a gap equation which is either obtained from the Nambu Jona-Lasinio Lagrangian or…

Nuclear Theory · Physics 2007-05-23 P. Bozek , Y. B. He , J. Huefner

Sensitivity analysis (SA) is a procedure for studying how sensitive are the output results of large-scale mathematical models to some uncertainties of the input data. The models are described as a system of partial differential equations.…

Numerical Analysis · Mathematics 2017-01-20 Ivan Dimov , Rayna Georgieva

The paper presents a review of dynamic stabilization mechanisms for plasma instabilities. One of the dynamic stabilization mechanisms for plasma instability was proposed in the papers [Phys. Plasmas 19, 024503(2012) and references therein],…

Plasma Physics · Physics 2019-02-20 S. Kawata , T. Karino , Y. J. Gu

This article presents an overview of quasineutral limits in plasma models. Starting from the Vlasov-Poisson system, it explains the role of the Debye length, the emergence of a kinetic incompressibility constraint, and the stability issues…

Analysis of PDEs · Mathematics 2026-05-28 Mikaela Iacobelli

In many fields of science, comprehensive and realistic computational models are available nowadays. Often, the respective numerical calculations call for the use of powerful supercomputers, and therefore only a limited number of cases can…

Computational Physics · Physics 2022-11-22 Ionut-Gabriel Farcas , Gabriele Merlo , Frank Jenko

The Hessian method is widely applied in the global analysis of parton distribution functions (PDFs), which uses a set of orthogonal eigenvectors to give predictions of a physical observable. Its uncertainty is estimated based on the…

High Energy Physics - Phenomenology · Physics 2025-09-12 Wenxiao Zhan , Siqi Yang , Minghui Liu , Liang Han , Daniel Stump , C. -P. Yuan

We study the possibility of controlling kinetic plasma instabilities by using lasers to apply external electromagnetic fields. We derive the dispersion relation for the corresponding mathematical description, a reduced Vlasov--Maxwell…

Plasma Physics · Physics 2025-09-30 Nicolas Crouseilles , Lukas Einkemmer , Qin Li , Uri Shumlak , Yukun Yue

We investigate active learning in Gaussian Process state-space models (GPSSM). Our problem is to actively steer the system through latent states by determining its inputs such that the underlying dynamics can be optimally learned by a…

Machine Learning · Computer Science 2021-08-03 Hon Sum Alec Yu , Dingling Yao , Christoph Zimmer , Marc Toussaint , Duy Nguyen-Tuong

Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e., not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected…

Physics and Society · Physics 2022-08-18 Maria Yliruka , Stefano Moret , Nilay Shah

Numerical diffusion is introduced by any numerical scheme as soon as small scales fluctuations, generated during the dynamical evolution of a collisionless plasma, become comparable to the grid size. Here we investigate the role of…

Plasma Physics · Physics 2007-05-23 Laura Galeotti , Francesco Califano

We consider linear stability of steady states of 1(1/2) and 3D Vlasov-Maxwell systems for collisionless plasmas. The linearized systems can be written as separable Hamiltonian systems with constraints. By using a general theory for…

Analysis of PDEs · Mathematics 2021-07-28 Zhiwu Lin

Sphere packings are essential to the development of physical models for powders, composite materials, and the atomic structure of the liquid state. There is a strong scientific need to be able to assess the fit of packing models to data,…

Methodology · Statistics 2009-10-31 Jeffrey Picka

The power-flow sensitivity coefficients (PFSCs) are widely used in the power system for expressing linearized dependencies between the controlled (i.e., the nodal voltages, lines currents) and control variables (e.g., active and reactive…

Systems and Control · Electrical Eng. & Systems 2023-12-18 Rahul Gupta
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