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The statistics of edge-localised plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability…

Plasma Physics · Physics 2013-02-27 A. J. Webster , R. O. Dendy

The objective is to provide clear and well-motivated guidance to Machine Learning (ML) teams, founded on our experience in empirical turbulence modeling. Guidance is also needed for modeling outside ML. ML is not yet successful in…

Fluid Dynamics · Physics 2023-08-03 Philippe Spalart

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 will provide detailed arguments showing that the set of Maxwell equations, and the corresponding wave equations, do not properly describe the evolution of electromagnetic wave-fronts. We propose a nonlinear corrected version that is…

General Physics · Physics 2018-03-28 D. Funaro

We derive and study a simple 1D nonlinear model for Edge Localized Mode (ELM) cycles. The nonlinear dynamics of a resistive ballooning mode is modeled via a single nonlinear equation of the Ginzburg-Landau type with a radial frequency…

Plasma Physics · Physics 2016-07-20 M. Leconte , G. S. Yun , Y. M. Jeon

Some work in progress is announced, on the use of algebraic geometry, mostly concerning elliptic curve theory, to model turbulence. Attention is given to flows across the scales, on some convenient model space, and some current trials are…

Mathematical Physics · Physics 2012-01-04 Luís G. D. C. Borges

This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues, but also on the advantages and promises of machine learning methods applied…

Computational Engineering, Finance, and Science · Computer Science 2022-12-21 Andrea Beck , Marius Kurz

Electromigration, a significant lifetime reliability concern in highperformance integrated circuits, is projected to grow even more important in future heterogeneously integrated systems that will service higher current loads. Today, EM…

Hardware Architecture · Computer Science 2026-03-17 Sachin S. Sapatnekar

Exact MLE for generalized linear mixed models (GLMMs) is a long-standing problem unsolved until today. The proposed research solves the problem. In this problem, the main difficulty is caused by intractable integrals in the likelihood…

Methodology · Statistics 2024-10-14 Tonglin Zhang

Some recent methods, like the Empirical Mode Decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful for many applications, the main issue with this approach is…

Functional Analysis · Mathematics 2024-11-01 Jerome Gilles

More and more applications require early decisions, i.e. taken as soon as possible from partially observed data. However, the later a decision is made, the more its accuracy tends to improve, since the description of the problem to hand is…

Combining a generalized current in the set of Maxwell's equations offers a useful framework to address the complex phenomena of electromagnetic turbulence. The fluidic-electromagnetic analogy implies that diffraction is the analog…

Classical Physics · Physics 2022-02-15 Mario J. Pinheiro

Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…

Machine Learning · Computer Science 2013-01-30 Luis E. Ortiz , Leslie Pack Kaelbling

In recent years, a strong reduction of plasma turbulence in the presence of energetic particles has been reported in a number of magnetic confinement experiments and corresponding gyrokinetic simulations. While highly relevant to…

Plasma Physics · Physics 2020-01-08 A. Di Siena , T. Görler , E. Poli , A. Bañón Navarro , A. Biancalani , F. Jenko

We review the current status of research in MHD turbulence theory and numerical experiments and their applications to astrophysics and solar science. We introduce general tools for studying turbulence, basic turbulence models, MHD equations…

Astrophysics of Galaxies · Physics 2019-10-10 Andrey Beresnyak

The propagation of electromagnetic waves trapped within dielectric and magnetic layers is considered. The description within the three-dimensional theory is compared with the simplified analysis in two dimensions. Two distinct media…

Classical Physics · Physics 2018-05-23 Tomasz Radozycki , Piotr Bargiela

Pedestal modelling is crucial to predict the performance of future fusion devices. Current modelling efforts suffer either from a lack of kinetic physics, or an excess of computational complexity. To ameliorate these problems, we take a…

Plasma Physics · Physics 2018-06-06 Ian Abel , Axel Hallenbert

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift…

Machine Learning · Computer Science 2015-05-07 Adam Vaughan , Stanislav V. Bohac

The boundary element method (BEM) enables solving three-dimensional electromagnetic problems using a two-dimensional surface mesh, making it appealing for applications ranging from electrical interconnect analysis to the design of…

Numerical Analysis · Mathematics 2021-12-14 Shashwat Sharma , Piero Triverio

In this article we present a generalization of the electron localization function (ELF) that can be used to analyze time-dependent processes. The time-dependent ELF allows the time-resolved observation of the formation, the modulation, and…

Chemical Physics · Physics 2007-05-23 Tobias Burnus , Miguel A. L. Marques , Eberhard K. U. Gross
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