Publications associées à Linearized model Fokker-Planck collision operators for gyrokinetic simulations. II. Numerical implementation and tests

Publications associées (36)

Higher Equations of Motion for Boundary Liouville Conformal Field Theory from the Ward Identities

In this document we prove higher equations of motion at the level 2 for boundary Liouville Conformal Field Theory. As a corollary we present a new derivation of the Belavin–Polyakov–Zamolodchikov differential equations. Our method of proof does not rely on ...

Springer Science and Business Media LLC2025

Confined and Deconfined Spinon Excitations in the Rectangular-lattice Quantum Antiferromagnet

Henrik Moodysson Rønnow, Bruce Normand, Ellen Fogh, Noore Elahi Shaik

Fractionalization remains one of the most fascinating manifestations of strong interactions in quantum many-body systems. In quantum magnetism, the existence of spinons-collective magnetic excitations that behave as quasiparticles with fractional quantum n ...

AMER PHYSICAL SOC2025

Nonlinear simulation of plasma turbulence using a gyrokinetic moment-based approach

Antoine Cyril David Hoffmann

Plasma turbulence plays a fundamental role in determining the performances of magnetic confinement fusion devices, such as tokamaks. Advances in computer science, combined with the development of efficient physical models, have significantly improved our u ...

EPFL2024

The time-domain Cartesian multipole expansion of electromagnetic fields

Emanuela Radici, Farhad Rachidi-Haeri, Marcos Rubinstein, Nicolas Mora Parra, Elias Per Joachim Le Boudec

Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

Nature Publishing Group2024

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Mario Paolone, André Hodder, Simone Rametti, Lucien André Félicien Pierrejean

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

2024

Non-normal forms

Yves-Marie François Ducimetière

In this thesis, we propose to formally derive amplitude equations governing the weakly nonlinear evolution of non-normal dynamical systems, when they respond to harmonic or stochastic forcing, or to an initial condition. This approach reconciles the non-mo ...

EPFL2024

FENNECS: a novel particle-in-cell code for simulating the formation of magnetized non-neutral plasmas trapped by electrodes of complex geometries

Guillaume Michel Le Bars, Stefano Alberti, Jean-Philippe Hogge, Joaquim Loizu Cisquella, Jérémy Genoud, Francesco Romano

This paper presents the new 2D electrostatic particle -in -cell code FENNECS developed to study the formation of magnetized non -neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun desi ...

2024

Observation of Kekulé vortices around hydrogen adatoms in graphene

Oleg Yazyev, Yifei Guan

Fractional charges are one of the wonders of the fractional quantum Hall effect. Such objects are also anticipated in two-dimensional hexagonal lattices under time reversal symmetry-emerging as bound states of a rotating bond texture called a Kekule vortex ...

Nature Portfolio2024

Development of a high current density, high temperature superconducting cable for pulsed magnets

Kamil Sedlák, Manuel Holenstein, Markus Jenni

A low-AC loss Rare-earth barium copper oxide (REBCO) cable, based on the VIPER cable technology has been developed by commonwealth fusion systems for use in high-field, compact tokamaks. The new cable is composed of partitioned and transposed copper ‘petal ...

IOP Publishing Ltd2024

Modelling of energetic particle drive and damping effects on TAEs in AUG experiment with ECCD

Alexander Karpushov

The impact of electron cyclotron current drive (ECCD)-driven current on toroidicity-induced Alfven eigenmodes (TAEs) in experiments on the AUG tokamak is investigated numerically. The dynamical evolution of the plasma profiles and equilibria are modelled w ...

IOP Publishing Ltd2024

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Marco Picasso, Alexandre Caboussat, Alexandre Masserey, Julien Hess

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Academic Press Inc Elsevier Science2024

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Andrea Zanoni

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

Siam Publications2024

Extracting the speed of sound in quark-gluon plasma with ultrarelativistic lead-lead collisions at the LHC

Jan Steggemann, Konstantin Androsov, Anna Mascellani, Joanna Malgorzata Wanczyk

Ultrarelativistic nuclear collisions create a strongly interacting state of hot and dense quark-gluon matter that exhibits a remarkable collective flow behavior with minimal viscous dissipation. To gain deeper insights into its intrinsic nature and fundame ...

IOP Publishing Ltd2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

From low-rank retractions to dynamical low-rank approximation and back

Daniel Kressner, Axel Elie Joseph Séguin, Gianluca Ceruti

In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...

Springer2024

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Paride Passelli

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

EPFL2024

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Muhamed Barakovic, Marco Pizzolato

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

Wiley2024

Collective motion in a sheet of microswimmers

Viktor Skultéty

Self-propelled particles such as bacteria or algae swimming through a fluid are non-equilibrium systems where particle motility breaks microscopic detailed balance, often resulting in large-scale collective motion. Previous theoretical work has identified ...

Nature Portfolio2024

Roger F. Harrington and the Method of Moments: Part 2: Electrodynamics

Juan Ramon Mosig

The method of moments (MOM), as introduced by Roger F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (IE) formulations applied to both electrostatic (part 1) and electrodynamic or full-wave problem ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Maude Girardin, Marco Picasso, Alexandre Caboussat

We present a finite elements-neural network approach for the numerical approximation of parametric partial differential equations. The algorithm generates training data from finite element simulations, and uses a data -driven (supervised) feedforward neura ...

Elsevier Science Sa2024