Gradient-Informed Bayesian and Interior Point Optimization for Efficient Inverse Design in Nanophotonics

ArXi:2602.18148v2 Announce Type: replace-cross Inverse design, particularly geometric shape optimization, provides a systematic approach for developing high-performance nanophotonic devices. While numerous optimization algorithms exist, previous global approaches exhibit slow convergence and conversely local search strategies frequently become trapped in local optima. To address the limitations inherent to both local and global approaches, we