Robust global optimization of plasmonic filter based on Q factor analysis using graded index

Abstract

Abstract To reduce the impact of uncertainties in various manufacturing processes while maintaining satisfactory performance level, we propose a robust global optimization approach for plasmonic filters based on extraordinary optical transmission by use of Q factor analysis with reasonable computational cost. The gradient index is employed as a metric for robustness, and the multiobjective genetic algorithm is selected as a global optimization tool. The figures of merit and gradient index are chosen as two objective functions with the design variables being the slit width, slit height, and period of the slit array, respectively. The finite element method is employed to investigate a variety of optical properties rigorously. The numerical optimization results demonstrate that the proposed approach provides improved effectiveness and efficiency in designing plasmonic filters under fabrication uncertainties by using Q factor analysis. The method proposed in this study enables systematic robust optimization while accounting for manufacturing uncertainties, which would be infeasible under typical time constraints. Specifically, within the proposed optimization framework, Q factor analysis can be employed due to a 20.60-times reduction in computational time. To the best of our knowledge, this represents the first robust optimization design for enhanced filter performance based on Q factor analysis in EOT, necessitating comprehensive spectrum calculations alongside fabrication tolerance considerations.