  The inverse design of photonic integrated circuits (PICs) presents
distinctive computational challenges, including their large memory
requirements. Advancements in the two-photon polymerization (2PP) fabrication
process introduce additional complexity, necessitating the development of more
flexible optimization algorithms to enable the creation of multi-material 3D
structures with unique properties. This paper presents an efficient
reverse-mode automatic differentiation framework for finite-difference
timedomain (FDTD) simulations that is able to handle several constraints
arising from novel fabrication methods. Our method is based on straight-through
gradient estimation that enables non-differentiable shape parametrizations. We
demonstrate the effectiveness of our approach by creating increasingly complex
structures to solve the coupling problem in integrated photonic circuits. The
results highlight the potential of our method for future PIC design and
practical applications.
