A two-network pipeline infers equation-of-state parameters and initial perturbations from synthetic radiographs, then reconstructs hydrodynamically consistent density fields by running the inferred parameters through a hydrodynamics code.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.comp-ph 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions
A two-network pipeline infers equation-of-state parameters and initial perturbations from synthetic radiographs, then reconstructs hydrodynamically consistent density fields by running the inferred parameters through a hydrodynamics code.