8 papers
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…
Verifier-Guided Model Discovery for Physical Dynamical Systems with Pretrained Symbolic Transformers
Farbod Faraji, Francesco Belardinelli
Reliable forecasting of nonlinear physical systems underpins scientific discovery and engineering decision-making. Yet high-fidelity simulations are prohibitively costly, and machi…
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…
Inferring solar-wind plasma structures from sparse probe trajectories using recurrent reduced-order learning
Maryam Reza, Farbod Faraji
In space plasma studies, spacecraft measurements often provide time histories of the solar-wind plasma. However, many heliospheric plasma processes are organized over spatial scale…
Benchmark for two-dimensional large scale coherent structures in partially magnetized ExB plasmas -- Community collaboration & lessons learned
Andrew T. Powis, Eduardo Ahedo, Alejandro Ãlvarez 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…