Robust characterization of photonic integrated circuits

TL;DR

This paper introduces a universal, robust on-chip method for characterizing the frequency response of photonic integrated circuits, including phase response, enabling faster and more accurate PIC reconfiguration for advanced optical applications.

Contribution

A novel on-chip characterization technique using a reference path and Fourier analysis to robustly measure both amplitude and phase responses of PICs.

Findings

Effective in measuring phase response despite low reference power

Demonstrated rapid training of PICs with thermal crosstalk compensation

Applicable to complex signal processing structures like FIR filters

Abstract

Photonic integrated circuits (PICs) offer ultra-broad optical bandwidths that enable unprecedented data throughputs for signal processing applications. Dynamic reconfigurability enables compensation of fabrication flaws and fluctuating external environments, tuning for adaptive equalization and training of optical neural networks. The initial step in PIC reconfiguration entails measuring its dynamic performance, often described by its frequency response. While measuring the amplitude response is straightforward, e.g. using a tunable laser and optical power meter, measuring the phase response presents challenges due to various factors, including phase variations in test connections and instrumentation limitations. To address these challenges, a universal and robust characterization technique is proposed, which uses an on-chip reference path coupled to the signal processing core (SPC), with a delay larger or smaller than the total delay across the signal processing paths. A Fourier transform of the chip's power response reveals the SPC's impulse response. The method is more robust against low reference-path power and imprecise delays. Experiments using a finite-impulse-response (FIR) structure demonstrate rapid SPC training, overcoming thermal crosstalk and device imperfections. This approach offers a promising solution for PIC characterization, facilitating expedited physical parameter training for advanced applications in communications and optical neural networks.