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Computing with Integrated Photonic Reservoirs

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Reservoir Computing

Part of the book series: Natural Computing Series ((NCS))

Abstract

The idea of using photonic systems as reservoirs to perform general-purpose computing was first introduced in 2008. Since then, a wide range of systems using either discrete or integrated optical components has been explored. In this chapter, we summarise a decade of research into integrated coherent photonic reservoirs. In these systems, information is carried by the intensity and the phase of light waves. Computations emerge from the way the light propagates inside the system, and the ways in which light that travels along different paths is mixed and transformed. We discuss the computational capabilities of these reservoirs and the trade-offs that can be made to optimise them. We also discuss the technological constraints that are encountered in building such systems and the ways these reflect on their design and training. Finally, we give an overview of recent approaches to combining multiple such reservoirs into larger and computationally more powerful systems.

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Notes

  1. 1.

    Although edge of chaos is the common term in dynamical systems theory, the term edge of stability has always felt like a more appropriate term in this context.

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Author information

Authors and Affiliations

  1. Ghent University and imec, Technologiepark 126, 9052, Zwijnaarde, Ghent, Belgium

    Joni Dambre, Andrew Katumba, Chonghuai Ma, Stijn Sackesyn, Floris Laporte, Matthias Freiberger & Peter Bienstman

Authors
  1. Joni Dambre
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  2. Andrew Katumba
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  3. Chonghuai Ma
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  4. Stijn Sackesyn
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  5. Floris Laporte
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  6. Matthias Freiberger
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  7. Peter Bienstman
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Corresponding author

Correspondence to Joni Dambre .

Editor information

Editors and Affiliations

  1. University of Tokyo, Tokyo, Japan

    Kohei Nakajima

  2. Consejo Superior de Investigaciones Científicas, IFISC (UIB-CSIC), Palma, Spain

    Ingo Fischer

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Dambre, J. et al. (2021). Computing with Integrated Photonic Reservoirs. In: Nakajima, K., Fischer, I. (eds) Reservoir Computing. Natural Computing Series. Springer, Singapore. https://doi.org/10.1007/978-981-13-1687-6_17

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  • DOI: https://doi.org/10.1007/978-981-13-1687-6_17

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