Dispersion-Aware Modeling Framework for Parallel Optical Computing

TL;DR

This paper develops a dispersion-aware modeling framework for parallel optical computing using cascaded MZIs, addressing dispersion challenges and proposing an efficient error correction method validated experimentally.

Contribution

It introduces a generalized wavelength-dependent model for MZI systems that incorporates dispersion effects and offers a calibration-based compensation strategy.

Findings

Dispersion significantly affects parallel optical computing accuracy.

The proposed calibration reduces dispersion error from 0.22 to 0.039.

Model validation confirms improved reliability of photonic processors.

Abstract

Optical computing represents a groundbreaking technology that leverages the unique properties of photons, with innate parallelism standing as its most compelling advantage. Parallel optical computing like cascaded Mach-Zehnder interferometers (MZIs) based offers powerful computational capabilities but also introduces new challenges, particularly concerning dispersion due to the introduction of new frequencies. In this work, we extend existing theories of cascaded MZI systems to develop a generalized model tailored for wavelength-multiplexed parallel optical computing. Our comprehensive model incorporates component dispersion characteristics into a wavelength-dependent transfer matrix framework and is experimentally validated. We propose a computationally efficient compensation strategy that reduces global dispersion error within a 40 nm range from 0.22 to 0.039 using edge-spectrum calibration. This work establishes a fundamental framework for dispersion-aware model and error correction in MZI-based parallel optical computing chips, advancing the reliability of multi-wavelength photonic processors.