Thermal Crosstalk Modelling and Compensation Methods for Programmable Photonic Integrated Circuits
This work addresses a critical bottleneck in optical computing by improving the accuracy and reliability of photonic chips, though it is incremental as it builds on existing modeling approaches.
The paper tackled the problem of thermal crosstalk in programmable photonic integrated circuits, which hinders precise programming, by training and evaluating three models to predict and compensate for its effects, achieving modeling errors below 0.5 pm and root-mean-square-errors under 2.0 pm in generalization tests.
Photonic integrated circuits play an important role in the field of optical computing, promising faster and more energy-efficient operations compared to their digital counterparts. This advantage stems from the inherent suitability of optical signals to carry out matrix multiplication. However, even deterministic phenomena such as thermal crosstalk make precise programming of photonic chips a challenging task. Here, we train and experimentally evaluate three models incorporating varying degrees of physics intuition to predict the effect of thermal crosstalk in different locations of an integrated programmable photonic mesh. We quantify the effect of thermal crosstalk by the resonance wavelength shift in the power spectrum of a microring resonator implemented in the chip, achieving modelling errors <0.5 pm. We experimentally validate the models through compensation of the crosstalk-induced wavelength shift. Finally, we evaluate the generalization capabilities of one of the models by employing it to predict and compensate for the effect of thermal crosstalk for parts of the chip it was not trained on, revealing root-mean-square-errors of <2.0 pm.