Angularly parameterized macromodel extraction for microstructures with a large number of terminals

In this paper, we report a novel method for extracting the angular parameterized macromodels of the microstructures with a large number of input terminals. First, the macromodels are extracted by combining the block Arnoldi approach with the superposition theory of linear systems. Then, the angular parameterization for the macromodels is achieved by applying the equivalent matrix coordinate transformation. A pitch-tunable micro programmable grating is used to demonstrate the proposed macromodeling method. Numerical simulation results show that the macromodels can dramatically reduce the computation cost while capturing the device behavior faithfully. Compared with the FEM results, the relative error is less than 1.1%, and the efficiency for transient analysis improves about 45 times.