Topology optimization of planar Integrated Lightwave circuits

The following PhD thesis research has been conducted under the instruction of the Marie Curie Actions research centre at the Numerical Method Laboratory(LMN) program at the "POLITEHNICA" University of Bucharest (PUB), Faculty of Electrical Engineering, Romania. The Electrical Engineering program culminates with the PhD thesis project, which is closely guided by PUB faculty members associated with the Electrical Engineering research centre. This study describes the concept and the result of initial experiments to optimize the topology of a planar lightwave circuit using an Evolutionary Algorithm (evolutionary strategy) with Covariance Matrix Adaptation (CMA-ES), an (search) algorithm for difficult non-linear, non convex optimization problems in a continuous domain. CMA-ES decouples the population size from the problem dimension and hence needs only small populations and relative few fitness function evaluation. The CMA-ES can be described as a randomized black box search algorithm. We use three levels of a sophisticated representation scheme (geometry, functional description and netlist) in combination with scattering approach and driven by an evolutionary algorithm allowing very fast, and accurate simulation of geometrically defined lightwave circuits. Semantic analysis is use to make the transition between the geometry and the functional description by detecting and extracting elements such as, different shapes of directional couplers. Based on this representation scheme a Mixtrinsic Evolvable Hardware (MEHW) method with CMA-ES is proposed, which allows the optimization of the given topology using different operators (mutation, recombination and selection), and with which should be able to search possibilities for evolving into new topologies and solve the portability and scalability problem. The excellent results confirm that the proposed approach concept is an adequate solving method for optimization of planar lightwave circuit structure, whereas the identified weak points of the algorithm indicate possible directions in the future work.