Neural-Operator Evolutionary Strategy Speeds PDE-Constrained Inverse Design

arXiv·low signal

This paper couples neural operators with a topology-informed evolutionary strategy to tackle PDE-constrained optimization, where inverse design of physical systems is computationally demanding due to high dimensionality and non-convexity. It is a scientific-computing technique with limited crossover to mainstream AI/ML engineering work.