SELF-ADJOINT S-PARAMETER SENSITIVITY ANALYSIS WITH FINITE-DIFFERENCE TIME-DOMAIN (FDTD) METHOD

Abstract

<p> This thesis contributes to the development of a novel electromagnetic (EM) time-domain computational approach, the self-adjoint variable method, for the scattering parameter (S-parameter) sensitivity analysis of high frequency problems. </p> <p> The design sensitivity analysis provides sensitivity information in the form of the response gradient (response Jacobian). For that, various techniques are used, ranging from finite-difference approximations to quadratic and spline interpolations. However, when the number of design parameters becomes large, the simulation time would become unaffordable, which is especially the case with EM simulations. The proposed self-adjoint sensitivity analysis (SASA) approach aims at providing sensitivity information efficiently without sacrificing the accuracy. Its efficiency lies in the fact that regardless of the number of design parameters, only one simulation of the original structure is required- the one used to compute the S-parameters. Thus, the sensitivity computation has negligible overhead. At the same time, it has second-order accuracy. </p> <p> Currently, commercial EM simulators provide only specific engineering responses, such as Z- or S-parameters. No sensitivity information is actually made available. With the SASA approach, the only requirement for the EM solver is the ability to access the field solution at the perturbation grid points. This feature is generally available with all time-domain EM simulators. The manipulation of the field solutions in this approach is simple and it adds practically negligible overhead to the -simulation time. </p> <p> We confirm the validity of this approach for both the shape and constitutive parameters of the design structures. 2-D examples including metallic and dielectric details are presented, using the field solutions from an in-house time-domain solver. We also explore the feasibility of implementing this approach with one of the commercial solvers, XFDTD v. 6.3. </p> <p> Suggestions for future research are provided. </P>