7 citations · 12 across the 12 of their papers we have counts for
13 papers
Reconstruction of Multiscale Plasma Dynamics Across Operating Regimes
Maryam Reza, Farbod Faraji
Reconstructing spatially resolved plasma dynamics from few sensors is essential for diagnostics, reduced-order modelling and control, yet remains difficult because the sparse measu…
RECAST: A Machine-Learning Framework for Correction and Super-Resolution of Coarse-Grid PDE Solvers
Maryam Reza, Farbod Faraji
Coarse-grid numerical solvers can substantially reduce the computational cost of time-dependent PDE simulation, but under-resolution often degrades both the trajectory and the spat…
Space-Time Information Interchangeability in Dynamical Systems: Conditions and Bounds for Replacing Spatial Sensors with Temporal Histories
Maryam Reza, Farbod Faraji
Many dynamical-state reconstruction problems seek to infer a high-dimensional spatial state from measurements at only a few locations. Because the governing dynamics couple evoluti…
Machine-Learning-Enabled Full-State Reconstruction of Fusion Plasmas from Minimal Sensor Measurements
Maryam Reza, Farbod Faraji
Plasma in nuclear fusion reactors is only partially observable: diagnostics are constrained by limited access, cost, and the harsh plasma environment, while high-fidelity simulatio…
Benchmark for two-dimensional large scale coherent structures in partially magnetized ExB plasmas -- Community collaboration & lessons learned
Andrew T. Powis, Eduardo Ahedo, Alejandro Álvarez Laguna +38
Low-temperature plasmas are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a…
Investigation of the influence of electrostatic excitation on instabilities and electron transport in ExB plasma configurations
Maryam Reza, Farbod Faraji, Aaron Knoll +1
Partially magnetized plasmas in ExB configurations - where the electric and magnetic fields are mutually perpendicular - exhibit a cross-field transport behavior, which is widely b…
Multiscale autonomous forecasting of plasma systems' dynamics using neural networks
Farbod Faraji, Maryam Reza
Plasma systems exhibit complex multiscale dynamics, resolving which poses significant challenges for conventional numerical simulations. Machine learning (ML) offers an alternative…
Latest progress on the reduced-order particle-in-cell scheme: II. Quasi-3D implementation and verification
Maryam Reza, Farbod Faraji, Aaron Knoll
Across many plasma applications, the underlying phenomena and interactions among the involved processes are known to exhibit three-dimensional characteristics. Furthermore, the glo…
Latest progress on the reduced-order particle-in-cell scheme: I. refining the underlying formulation
Maryam Reza, Farbod Faraji, Aaron Knoll
The particle-in-cell (PIC) method is a well-established and widely used kinetic plasma modelling approach that provides a hybrid Lagrangian-Eulerian approach to solve the plasma ki…
Machine Learning Applications to Computational Plasma Physics and Reduced-Order Plasma Modeling: A Perspective
Farbod Faraji, Maryam Reza
Machine learning (ML) provides a broad spectrum of tools and architectures that enable the transformation of data from simulations and experiments into useful and explainable scien…
Shallow Recurrent Decoder for Reduced Order Modeling of Plasma Dynamics
J. Nathan Kutz, Maryam Reza, Farbod Faraji +1
Reduced order models are becoming increasingly important for rendering complex and multiscale spatio-temporal dynamics computationally tractable. The computational efficiency of su…
Data-driven local operator finding for reduced-order modelling of plasma systems: II. Application to parametric dynamics
Farbod Faraji, Maryam Reza, Aaron Knoll +1
Real-world systems often exhibit dynamics influenced by various parameters, either inherent or externally controllable, necessitating models capable of reliably capturing these par…
Data-driven local operator finding for reduced-order modelling of plasma systems: I. Concept and verifications
Farbod Faraji, Maryam Reza, Aaron Knoll +1
Reduced-order plasma models that can efficiently predict plasma behavior across various settings and configurations are highly sought after yet elusive. The demand for such models…