Accelerating Photonic Integrated Circuit Design: Traditional, ML and Quantum Methods
Abstract
Photonic Integrated Circuits (PICs) provide superior speed, bandwidth, and energy efficiency, making them ideal for communication, sensing, and quantum computing applications. Despite their potential, PIC design workflows and integration lag behind those in electronics, calling for groundbreaking advancements. This review outlines the state of PIC design, comparing traditional simulation methods with machine learning approaches that enhance scalability and efficiency. It also explores the promise of quantum algorithms and quantum-inspired methods to address design challenges.
Cite
@article{arxiv.2506.18435,
title = {Accelerating Photonic Integrated Circuit Design: Traditional, ML and Quantum Methods},
author = {Alessandro Daniele Genuardi Oquendo and Ali Nadir and Tigers Jonuzi and Siddhartha Patra and Nilotpal Kanti Sinha and Román Orús and Sam Mugel},
journal= {arXiv preprint arXiv:2506.18435},
year = {2025}
}
Comments
We thank the Centro para el Desarrollo Tecnol\'ogico e Industria (CDTI) for their support under the Project INSPIRE via Misiones PERTE Chip 2023. Grant EXP-00162621 / MIG-20231016