Self-calibrating programmable photonic integrated circuits

Researchers demonstrate a self-calibrating programmable photonic integrated circuit. The findings may be useful for the accurate control of large-scale photonic integrated circuits in applications such as light-based machine learning. Programmable photonic integrated circuits (PICs) are dense assemblies of tunable elements that provide flexible reconfigurability to enable different functions to be selected; however, due to manufacturing variations and thermal gradients that affect the optical phases of the elements, it is difficult to guarantee a stable correspondence between the electrical commands to the chip, and the function that it provides. Here we demonstrate a self-calibrating programmable PIC with full control over its complex impulse response, in the presence of thermal cross-talk between phase-tuning elements. Self-calibration is achieved by: (1) incorporating an optical reference path into the PIC; (2) using the Kramers-Kronig relationship to recover the phase response from amplitude measurements; and (3) applying a fast-converging self-calibration algorithm. We demonstrate dial-up signal processing functions with complex impulse responses using only 25 training iterations. This approach offers stable and accurate control of large-scale PICs, for demanding applications such as communications network reconfiguration, neuromorphic hardware accelerators and quantum computers.

Automated summary

Researchers demonstrate a self-calibrating programmable photonic integrated circuit with full control over its complex impulse response, even in the presence of thermal cross-talk. This self-calibration is achieved by incorporating an optical reference path, using the Kramers-Kronig relationship, and applying a fast-converging self-calibration algorithm.