:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Thun, Timo, Conlin, Rory, Panici, Dario, Böckenhoff, Daniel
Format:	Preprint
Published:	2025
Subjects:	Plasma Physics Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2510.13521
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving ideal MHD equilibrium accuracy with physics-informed neural networks
by: Thun, Timo, et al.
Published: (2025)

Stellarator Optimization with Constraints
by: Conlin, Rory, et al.
Published: (2024)

Deflation Techniques for Stellarator Equilibrium and Optimization
by: Panici, Dario, et al.
Published: (2026)

High Order Free Boundary MHD Equilibria in DESC
by: Conlin, Rory, et al.
Published: (2024)

Extending near-axis equilibria in DESC
by: Panici, Dario, et al.
Published: (2025)

Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications
by: Unalmis, Kaya E., et al.
Published: (2024)

Magnetic Fields with General Omnigenity
by: Dudt, Daniel W., et al.
Published: (2023)

Optimization of Nonlinear Turbulence in Stellarators
by: Kim, Patrick, et al.
Published: (2023)

Hybrid Fourier Neural Operator-Plasma Fluid Model for Fast and Accurate Multiscale Simulations of High Power Microwave Breakdown
by: Pandya, Kalp, et al.
Published: (2025)

Surface Current Optimization and Coil-Cutting Algorithms for Stage-Two Stellarator Optimization
by: Panici, Dario, et al.
Published: (2025)

Exponential Spectral Scaling: Robust and Efficient Stellarator Boundary Optimization via Mode-Dependent Scaling
by: Jang, Byoungchan, et al.
Published: (2025)

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning
by: Landreman, Matt, et al.
Published: (2025)

Plasma Surrogate Modelling using Fourier Neural Operators
by: Gopakumar, Vignesh, et al.
Published: (2023)

Omnigenous stellarator equilibria with enhanced stability
by: Gaur, Rahul, et al.
Published: (2024)

TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics
by: Boschi, Tobia, et al.
Published: (2026)

Uncertainty Guided Online Ensemble for Non-stationary Data Streams in Fusion Science
by: Rajput, Kishansingh, et al.
Published: (2025)

5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence
by: Galletti, Gianluca, et al.
Published: (2025)

GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations
by: Paischer, Fabian, et al.
Published: (2025)

Towards Transparent and Accurate Plasma State Monitoring at JET
by: Bürli, Andrin, et al.
Published: (2025)

Design Optimization of Nuclear Fusion Reactor through Deep Reinforcement Learning
by: Kim, Jinsu, et al.
Published: (2024)

IDP-PGFE: An Interpretable Disruption Predictor based on Physics-Guided Feature Extraction
by: Shen, Chengshuo, et al.
Published: (2022)

Human-in-the-Loop Meta Bayesian Optimization for Fusion Energy and Scientific Applications
by: Gutierrez, Ricardo Luna, et al.
Published: (2026)

Conditional Denoising Model as a Physical Surrogate Model
by: Afonso, José, et al.
Published: (2026)

Deep Learning assisted microwave-plasma interaction based technique for plasma density estimation
by: Ghosh, Pratik, et al.
Published: (2023)

Numerical asymptotics of near-axis expansions of quasisymmetric magnetohydrostatic equilibria with anisotropic pressure
by: Fu, Lanke, et al.
Published: (2025)

Deep Wave Network for Modeling Multi-Scale Physical Dynamics
by: Khrabry, Alexander I., et al.
Published: (2026)

Learning Plasma Dynamics and Robust Rampdown Trajectories with Predict-First Experiments at TCV
by: Wang, Allen M., et al.
Published: (2025)

Physics-consistent machine learning: output projection onto physical manifolds
by: Valente, Matilde, et al.
Published: (2025)

AI-Driven Autonomous Control of Proton-Boron Fusion Reactors Using Backpropagation Neural Networks
by: Laurelli, Michele
Published: (2024)

Diffusion for Fusion: Designing Stellarators with Generative AI
by: Padidar, Misha, et al.
Published: (2025)

Stochastic hierarchical data-driven optimization: application to plasma-surface kinetics
by: Afonso, José, et al.
Published: (2026)

Generative Neural Reparameterization for Differentiable PDE-constrained Optimization
by: Joglekar, Archis S.
Published: (2024)

ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks
by: Cadena, Santiago A., et al.
Published: (2025)

Omnigenous umbilic stellarators
by: Gaur, R., et al.
Published: (2025)

A flexible and differentiable coil proxy for stellarator equilibrium optimization
by: Fu, Lanke, et al.
Published: (2025)

Designing A Buildable Optimized Stellarator to Confine Electron-Positron Plasmas
by: Gil, Pedro F., et al.
Published: (2026)

Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation
by: Ding, Siqi, et al.
Published: (2025)

An Interpretable Operator-Learning Model for Electric Field Profile Reconstruction in Discharges Based on the EFISH Method
by: Yang, Zhijian, et al.
Published: (2025)

Energetic Particle Tracing in Optimized Quasisymmetric Stellarator Equilibria
by: Figueiredo, P. A., et al.
Published: (2023)

ZERNIPAX: A Fast and Accurate Zernike Polynomial Calculator in Python
by: Elmacioglu, Yigit Gunsur, et al.
Published: (2024)