Bi-Level Optimization Accelerated DRC-Aware Physical Design Automation for Photonic Devices

Photonic integrated circuits (PICs) design has been challenged by the complex physics behind various integrated photonic devices. Inverse design offers an effective design automation solution for obtaining high-performance and compact pho-tonic devices using computational algorithms and electromagnetic (EM) simulations. However, the challenge lies in transforming the fabrication-infeasible device geometries obtained from computational algorithms into reliable while optimal physical design. In-corporating fabrication constraints into the optimization iterations can extend running time and lead to performance compromise. In this work, we proposed a novel DRC-aware photonic inverse design framework, leveraging the bi-level optimization to enable end-to-end gradient-based device optimization. Our method can guarantee all intermediate devices on the optimization trajectory adhere to fabrication requirements and rules. The proposed workflow eliminates the need for a binarization process and fabrication constraint adaption, thus enabling a fast and efficient search for high-performance and reliable integrated photonic devices. Experimental results demonstrate the benefits of our proposed method, including improved device performance and reduced EM simulations and running time.