A Generalized Domain-Decomposition Stochastic FDTD Technique for Complex Nanomaterial and Graphene Structures

The systematic and accurate design process of realistic nanocomposite applications and finite-sized graphene setups with arbitrary media uncertainties is presented in this paper by a 3-D covariant/contravariant stochastic finite-difference time-domain method. The new technique uses extra nodes pertinent to a convex combination of all obtainable spatial increments and introduces a robust domain-decomposition formulation combined with Lagrange multipliers to considerably decrease the system overhead. In this way, the mean value and the standard deviation of field components are evaluated in a single run. The performance of the proposed algorithm is validated by various statistically varying nanoscale applications.