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The efficient investigation of integrated photonic and superconducting circuitry relies on the flexible design of masks for the lithography steps. While commercial software packages for high-end design are commonly employed, for scientific users, such software systems are often financially exclusive and thus custom solutions are needed. Here we present a flexible open source Python framework that allows mask generation of integrated circuitry by easy-to-learn Python scripting. The framework is designed to facilitate the design of new photonic building blocks, since it allows defining the geometry by reusing existing parts or direct design using geometric objects. Through the use of existing and user-defined building blocks, complex integrated circuits can be created in a convenient fashion. We illustrate the capabilities of the framework by realizing hybrid nanophotonic-superconducting circuits, as well as hybrid 2D-3D nanophotonic circuits through multi-step nanofabrication. Because all design parameters can be defined by the user, the framework is not limited to a particular platform and can rapidly be adapted for new applications.
Gehring et al. (Mon,) studied this question.