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🏛️ The physics.plasm-ph Crypt
physics.plasm-ph: Where physics.plasm-ph papers rest without their code.
35
Total Papers
23
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0
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12
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34.3%
Survival Rate
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Plasma Surrogate Modelling using Fourier Neural Operators
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Deep Learning for Plasma Tomography and Disruption Prediction from Bolometer Data
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Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations
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Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers
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Extracting Electron Scattering Cross Sections from Swarm Data using Deep Neural Networks
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Automatic Identification of MHD Modes in Magnetic Fluctuations Spectrograms using Deep Learning Techniques
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Applications of Deep Learning to Nuclear Fusion Research
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GPEC, a real-time capable Tokamak equilibrium code
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Data-driven modeling of Landau damping by physics-informed neural networks
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Identifying Entangled Physics Relationships through Sparse Matrix Decomposition to Inform Plasma Fusion Design
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Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak
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Grad-Shafranov equilibria via data-free physics informed neural networks
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Unsupervised classification of fully kinetic simulations of plasmoid instability using Self-Organizing Maps (SOMs)
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Topological Analysis of Magnetic Reconnection in Kinetic Plasma Simulations
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Characterizing the Performance of the Implicit Massively Parallel Particle-in-Cell iPIC3D Code
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Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers
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A Study of Performance Portability in Plasma Physics Simulations
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Regimes of charged particle dynamics in current sheets: the machine learning approach
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Evaluation and Verification of Physics-Informed Neural Models of the Grad-Shafranov Equation
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Inverse Rendering of Fusion Plasmas: Inferring Plasma Composition from Imaging Systems
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Disruption Prediction in Fusion Devices through Feature Extraction and Logistic Regression
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