Stacked Reconfigurable Optical Cavities for Smart Sensing Pixels

Simon Bilodeau, Thomas Ferreira De Lima, Eli A. Doris, Michael Hack, Paul R. Prucnal

Research output: Contribution to journalArticlepeer-review

Abstract

Photonic systems have seen a recent explosion of investigation for neuromorphic engineering and the execution of machine learning models, owing to the advantages of optics for communications and performing linear operations. Here, we present a novel architecture for executing reconfigurable multiwavelength photonic multiply-accumulate (MAC) operations based on all-solid-state vertically-integrated tunable cavities. We simulate this weighting action through full transfer-matrix calculations of a realistic candidate filter stack. By efficiently leveraging the out-of-plane dimension, we form a conceptual 'smart pixel' device that can achieve higher spectral channel count per area, or equivalently computational density, than comparable subpixel architectures and planar integrated photonic devices. While this technology is of use for neuromorphic photonic information processing, its usefulness extends to applications in sensing and communications by covering, for instance, high spatial resolution hyperspectral filters and reconfigurable routing.

Original languageEnglish (US)
Article number2900212
JournalIEEE Journal of Selected Topics in Quantum Electronics
Volume28
Issue number4
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

Keywords

  • Multiply-accumulate (MAC)
  • neural networks
  • neuromorphic photonics
  • optical resonators
  • optical sensors
  • wavelength-divison multiplexing (WDM)

Fingerprint

Dive into the research topics of 'Stacked Reconfigurable Optical Cavities for Smart Sensing Pixels'. Together they form a unique fingerprint.

Cite this