Multi-Objective Optimization of Chiral Metasurface for Sensing Based on a Distributed Algorithm

We propose a distributed multi-objective optimization (DMO) method for designing chiral plasmonic metasurface that satisfies multiple objectives simultaneously. We aim to improve the refractive index sensitivity of the archetypical Born-Kuhn type chiral plasmonic metasurface while ensuring that circular dichroism (CD) is as pronounced as possible at a designated resonance wavelength. By leveraging distributed technology, the proposed method significantly improves the time efficiency of the optimization process. The simulation results demonstrate approximately 33% enhancement in sensitivity by DMO, as well as greater than 100% boost in time efficiency compared to stand-alone optimization approaches. These findings highlight the potential of the proposed method to guide the design of chiral plasmonic metasurface sensors, enabling the simultaneous optimization of multiple objectives and facilitating advancements in chiral optics and sensing applications.