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Reconfigurable application-specific photonic integrated circuit for solving partial differential equations

Authors :
Ye Jiachi
Shen Chen
Peserico Nicola
Meng Jiawei
Ma Xiaoxuan
Nouri Behrouz Movahhed
Popescu Cosmin-Constantin
Hu Juejun
Kang Haoyan
Wang Hao
El-Ghazawi Tarek
Dalir Hamed
Sorger Volker J.
Source :
Nanophotonics, Vol 13, Iss 12, Pp 2231-2239 (2024)
Publication Year :
2024
Publisher :
De Gruyter, 2024.

Abstract

Solving mathematical equations faster and more efficiently has been a Holy Grail for centuries for scientists and engineers across all disciplines. While electronic digital circuits have revolutionized equation solving in recent decades, it has become apparent that performance gains from brute-force approaches of compute-solvers are quickly saturating over time. Instead, paradigms that leverage the universes’ natural tendency to minimize a system’s free energy, such as annealers or Ising Machines, are being sought after due to favorable complexity scaling. Here, we introduce a programmable analog solver leveraging the formal mathematical equivalence between Maxwell’s equations and photonic circuitry. It features a mesh network of nanophotonic beams to find solutions to partial differential equations. As an example, we designed, fabricated, and demonstrated a novel application-specific photonic integrated circuit comprised of electro-optically reconfigurable nodes and experimentally validated 90 % accuracy with respect to a commercial solver. Finally, we tested this photonic integrated chip performance by simulating thermal diffusion on a spacecraft’s heat shield during re-entry to a planet’s atmosphere. The programmable light-circuitry presented herein offers a facile route for solving complex problems and thus will have profound potential applications across many scientific and engineering fields.

Details

Language :
English
ISSN :
21928614
Volume :
13
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Nanophotonics
Publication Type :
Academic Journal
Accession number :
edsdoj.1b928bb1c794435a8f16af7c1958ce59
Document Type :
article
Full Text :
https://doi.org/10.1515/nanoph-2023-0732