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Dual-mode semiconductor lasers in reservoir computing. / Harkhoe, Krishan Kumar; Van Der Sande, Guy.

Neuro-inspired Photonic Computing. ed. / Peter Bienstman; Marc Sciamanna. Vol. 10689 SPIE, 2018. p. 10689-10689-7 106890B (NEURO-INSPIRED PHOTONIC COMPUTING).

Research output: Chapter in Book/Report/Conference proceedingConference paper

Harvard

Harkhoe, KK & Van Der Sande, G 2018, Dual-mode semiconductor lasers in reservoir computing. in P Bienstman & M Sciamanna (eds), Neuro-inspired Photonic Computing. vol. 10689, 106890B, NEURO-INSPIRED PHOTONIC COMPUTING, SPIE, pp. 10689-10689-7, SPIE Photonics Europe 2018, Strasbourg, France, 22/04/18. https://doi.org/10.1117/12.2307328

APA

Harkhoe, K. K., & Van Der Sande, G. (2018). Dual-mode semiconductor lasers in reservoir computing. In P. Bienstman, & M. Sciamanna (Eds.), Neuro-inspired Photonic Computing (Vol. 10689, pp. 10689-10689-7). [106890B] (NEURO-INSPIRED PHOTONIC COMPUTING). SPIE. https://doi.org/10.1117/12.2307328

Vancouver

Harkhoe KK, Van Der Sande G. Dual-mode semiconductor lasers in reservoir computing. In Bienstman P, Sciamanna M, editors, Neuro-inspired Photonic Computing. Vol. 10689. SPIE. 2018. p. 10689-10689-7. 106890B. (NEURO-INSPIRED PHOTONIC COMPUTING). https://doi.org/10.1117/12.2307328

Author

Harkhoe, Krishan Kumar ; Van Der Sande, Guy. / Dual-mode semiconductor lasers in reservoir computing. Neuro-inspired Photonic Computing. editor / Peter Bienstman ; Marc Sciamanna. Vol. 10689 SPIE, 2018. pp. 10689-10689-7 (NEURO-INSPIRED PHOTONIC COMPUTING).

BibTeX

@inproceedings{cafbd9cfdda247199b36d8a6490c6e11,
title = "Dual-mode semiconductor lasers in reservoir computing",
abstract = "Delay-based reservoir computing schemes using semiconductor lasers have proven robustness and good performances for a wide range of tasks. These schemes are especially desirable because of their inherent high speed in data processing and the promise of miniaturization. One such scheme is based on a single-mode semiconductor laser subjected to optical feedback, which can be designed for on-chip implementation. However, the feedback line length remains to be a limiting factor in the miniaturization process. We propose to target more than one mode in a semiconductor lasers. In this way, we believe that it would be possible to distribute the computational power over several modes. Also, having more optical modes addressable will allow for a larger variability and parameter space both at the input and output layers of the reservoir computer. The complex interactions between either optical mode and optical mode or optical mode and carrier densities introduce new dynamical features, as well as increase the available nonlinearity in the system. We envision multiple mode reservoir computing as the next crucial step in optical reservoir computing evolution.",
keywords = "Neuromorphic computing, Non-linear dynamics, Reservoir Computing, Semiconductor lasers",
author = "Harkhoe, {Krishan Kumar} and {Van Der Sande}, Guy",
year = "2018",
month = "1",
day = "1",
doi = "10.1117/12.2307328",
language = "English",
isbn = "9781510619043",
volume = "10689",
series = "NEURO-INSPIRED PHOTONIC COMPUTING",
publisher = "SPIE",
pages = "10689--10689--7",
editor = "Peter Bienstman and Marc Sciamanna",
booktitle = "Neuro-inspired Photonic Computing",
address = "United States",

}

RIS

TY - GEN

T1 - Dual-mode semiconductor lasers in reservoir computing

AU - Harkhoe, Krishan Kumar

AU - Van Der Sande, Guy

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Delay-based reservoir computing schemes using semiconductor lasers have proven robustness and good performances for a wide range of tasks. These schemes are especially desirable because of their inherent high speed in data processing and the promise of miniaturization. One such scheme is based on a single-mode semiconductor laser subjected to optical feedback, which can be designed for on-chip implementation. However, the feedback line length remains to be a limiting factor in the miniaturization process. We propose to target more than one mode in a semiconductor lasers. In this way, we believe that it would be possible to distribute the computational power over several modes. Also, having more optical modes addressable will allow for a larger variability and parameter space both at the input and output layers of the reservoir computer. The complex interactions between either optical mode and optical mode or optical mode and carrier densities introduce new dynamical features, as well as increase the available nonlinearity in the system. We envision multiple mode reservoir computing as the next crucial step in optical reservoir computing evolution.

AB - Delay-based reservoir computing schemes using semiconductor lasers have proven robustness and good performances for a wide range of tasks. These schemes are especially desirable because of their inherent high speed in data processing and the promise of miniaturization. One such scheme is based on a single-mode semiconductor laser subjected to optical feedback, which can be designed for on-chip implementation. However, the feedback line length remains to be a limiting factor in the miniaturization process. We propose to target more than one mode in a semiconductor lasers. In this way, we believe that it would be possible to distribute the computational power over several modes. Also, having more optical modes addressable will allow for a larger variability and parameter space both at the input and output layers of the reservoir computer. The complex interactions between either optical mode and optical mode or optical mode and carrier densities introduce new dynamical features, as well as increase the available nonlinearity in the system. We envision multiple mode reservoir computing as the next crucial step in optical reservoir computing evolution.

KW - Neuromorphic computing

KW - Non-linear dynamics

KW - Reservoir Computing

KW - Semiconductor lasers

UR - http://www.scopus.com/inward/record.url?scp=85053483400&partnerID=8YFLogxK

U2 - 10.1117/12.2307328

DO - 10.1117/12.2307328

M3 - Conference paper

SN - 9781510619043

VL - 10689

T3 - NEURO-INSPIRED PHOTONIC COMPUTING

SP - 10689-10689-7

BT - Neuro-inspired Photonic Computing

A2 - Bienstman, Peter

A2 - Sciamanna, Marc

PB - SPIE

ER -

ID: 40462436