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Design automation of photonic resonator weights.

Authors :
Ferreira de Lima, Thomas
Doris, Eli A.
Bilodeau, Simon
Zhang, Weipeng
Jha, Aashu
Peng, Hsuan-Tung
Blow, Eric C.
Huang, Chaoran
Tait, Alexander N.
Shastri, Bhavin J.
Prucnal, Paul R.
Source :
Nanophotonics (21928606); Sep2022, Vol. 11 Issue 17, p3805-3822, 18p
Publication Year :
2022

Abstract

Neuromorphic photonic processors based on resonator weight banks are an emerging candidate technology for enabling modern artificial intelligence (AI) in high speed analog systems. These purpose-built analog devices implement vector multiplications with the physics of resonator devices, offering efficiency, latency, and throughput advantages over equivalent electronic circuits. Along with these advantages, however, often come the difficult challenges of compensation for fabrication variations and environmental disturbances. In this paper, we review sources of variation and disturbances from our experiments, as well as mathematically define quantities that model them. Then, we introduce how the physics of resonators can be exploited to weight and sum multiwavelength signals. Finally, we outline automated design and control methodologies necessary to create practical, manufacturable, and high accuracy/precision resonator weight banks that can withstand operating conditions in the field. This represents a road map for unlocking the potential of resonator weight banks in practical deployment scenarios. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21928606
Volume :
11
Issue :
17
Database :
Complementary Index
Journal :
Nanophotonics (21928606)
Publication Type :
Academic Journal
Accession number :
158647780
Full Text :
https://doi.org/10.1515/nanoph-2022-0049