Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization

Excerpt

arXiv:2607.07682v2 Announce Type: replace Abstract: The inverse design of physical systems governed by partial differential equations is computationally demanding due to the high dimensionality and non-convexity of design spaces. Generative models for inverse design often lack robustness and transferability, whereas evolutionary strategies are robust but struggle in high-dimensional spaces. This paper introduces a Neural Operator-enabled Topology-informed Evolutionary Strategy (NOTES) that integ