Recent Developments in Photonic Integration: Reservoir Computing in Photonics using Silicon Microring Nonlinearities

  • Unique Paper ID: 180627
  • PageNo: 1600-1609
  • Abstract:
  • The rapid evolution of integrated photonics is revolutionizing the landscape of high-speed, energy efficient computing. One of the most promising frontiers in this domain is Photonic Reservoir Computing (PRC), a neuromorphic paradigm that leverages the inherent dynamics and parallelism of photonic systems. This paper provides an in-depth exploration of reservoir computing implemented through nonlinear effects in silicon microring resonators (MRRs)—a scalable and CMOS-compatible platform for optical information processing. We examine the fundamental physical processes, such as two-photon absorption, free carrier dispersion, and thermal-optic phenomena, that facilitate nonlinear transformation and short-term memory essential for RC operations. Recent advances in photonic integration are surveyed, highlighting how MRR-based architectures support time-multiplexed virtual node generation and can be effectively deployed for complex signal processing tasks. A simulation framework in MATLAB is presented to model the nonlinear carrier dynamics and evaluate the RC system on a distorted QPSK signal with chromatic dispersion and Kerr nonlinearity. Results demonstrate accurate symbol recovery through a simple linear readout, validating the feasibility of silicon microrings for high-performance PRC. We further discuss emerging applications in AI on-Chip inference engines, fiber-optic communications, and neuromorphic sensor fusion, and outline challenges and opportunities in scaling and enhancing photonic reservoir systems. This work positions silicon microring-based PRC as a compelling solution for next generation integrated photonic computing.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{180627,
        author = {Sanika Atul  Inamdar},
        title = {Recent Developments in Photonic Integration: Reservoir Computing in Photonics using Silicon Microring Nonlinearities},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1600-1609},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180627},
        abstract = {The rapid evolution of integrated photonics 
is revolutionizing the landscape of high-speed, energy
efficient computing. One of the most promising 
frontiers in this domain is Photonic Reservoir 
Computing (PRC), a neuromorphic paradigm that 
leverages the inherent dynamics and parallelism of 
photonic systems. This paper provides an in-depth 
exploration of reservoir computing implemented 
through nonlinear effects in silicon microring 
resonators (MRRs)—a scalable and CMOS-compatible 
platform for optical information processing.  
We examine the fundamental physical processes, such 
as two-photon absorption, free carrier dispersion, and 
thermal-optic phenomena, that facilitate nonlinear 
transformation and short-term memory essential for 
RC operations. Recent advances in photonic integration 
are 
surveyed, 
highlighting 
how 
MRR-based 
architectures support time-multiplexed virtual node 
generation and can be effectively deployed for complex 
signal processing tasks. A simulation framework in 
MATLAB is presented to model the nonlinear carrier 
dynamics and evaluate the RC system on a distorted 
QPSK signal with chromatic dispersion and Kerr 
nonlinearity. Results demonstrate accurate symbol 
recovery through a simple linear readout, validating the 
feasibility of silicon microrings for high-performance 
PRC. We further discuss emerging applications in AI
on-Chip inference engines, fiber-optic communications, 
and neuromorphic sensor fusion, and outline challenges 
and opportunities in scaling and enhancing photonic 
reservoir systems. This work positions silicon 
microring-based PRC as a compelling solution for next
generation integrated photonic computing.},
        keywords = {Photonic Reservoir Computing, Silicon  Microring, Nonlinear Optics, Time-Multiplexing,  Neuromorphic Computing, Integrated Photonics,  QPSK Equalization},
        month = {June},
        }

Cite This Article

Inamdar, S. A. . (2025). Recent Developments in Photonic Integration: Reservoir Computing in Photonics using Silicon Microring Nonlinearities. International Journal of Innovative Research in Technology (IJIRT), 12(1), 1600–1609.

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