Passive device modeling methodology using nonlinear optimization

In this paper we describe a method of accurately modeling new passive devices by deembedding the many building blocks from which they are built from just a few test structures. We use a nonlinear optimizer to find the optimal models for the building blocks by fitting extensive high frequency measurements of the test structures behavior. Key results are: the number of test structures needed is much less than the number of parameters and building blocks to be extracted; the extracted models of the building blocks are very predictive of the behavior of new devices built from them; and this methodology is much faster than other finite element like methods.