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Experimental demonstration of reservoir computing on a silicon photonics chip

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Abstract
In today's age, companies employ machine learning to extract information from large quantities of data. One of those techniques, reservoir computing (RC), is a decade old and has achieved state-of-the-art performance for processing sequential data. Dedicated hardware realizations of RC could enable speed gains and power savings. Here we propose the first integrated passive silicon photonics reservoir. We demonstrate experimentally and through simulations that, thanks to the RC paradigm, this generic chip can be used to perform arbitrary Boolean logic operations with memory as well as 5-bit header recognition up to 12.5 Gbit s(-1), without power consumption in the reservoir. It can also perform isolated spoken digit recognition. Our realization exploits optical phase for computing. It is scalable to larger networks and much higher bitrates, up to speeds >100 Gbit s(-1). These results pave the way for the application of integrated photonic RC for a wide range of applications.
Keywords
SPEECH RECOGNITION, PATTERN-RECOGNITION, CIRCUITS, SYSTEM, STATES, NODE

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MLA
Vandoorne, Kristof, Pauline Mechet, Thomas Van Vaerenbergh, et al. “Experimental Demonstration of Reservoir Computing on a Silicon Photonics Chip.” NATURE COMMUNICATIONS 5 (2014): n. pag. Print.
APA
Vandoorne, K., Mechet, P., Van Vaerenbergh, T., Fiers, M., Morthier, G., Verstraeten, D., Schrauwen, B., et al. (2014). Experimental demonstration of reservoir computing on a silicon photonics chip. NATURE COMMUNICATIONS, 5.
Chicago author-date
Vandoorne, Kristof, Pauline Mechet, Thomas Van Vaerenbergh, Martin Fiers, Geert Morthier, David Verstraeten, Benjamin Schrauwen, Joni Dambre, and Peter Bienstman. 2014. “Experimental Demonstration of Reservoir Computing on a Silicon Photonics Chip.” Nature Communications 5.
Chicago author-date (all authors)
Vandoorne, Kristof, Pauline Mechet, Thomas Van Vaerenbergh, Martin Fiers, Geert Morthier, David Verstraeten, Benjamin Schrauwen, Joni Dambre, and Peter Bienstman. 2014. “Experimental Demonstration of Reservoir Computing on a Silicon Photonics Chip.” Nature Communications 5.
Vancouver
1.
Vandoorne K, Mechet P, Van Vaerenbergh T, Fiers M, Morthier G, Verstraeten D, et al. Experimental demonstration of reservoir computing on a silicon photonics chip. NATURE COMMUNICATIONS. 2014;5.
IEEE
[1]
K. Vandoorne et al., “Experimental demonstration of reservoir computing on a silicon photonics chip,” NATURE COMMUNICATIONS, vol. 5, 2014.
@article{5757115,
  abstract     = {{In today's age, companies employ machine learning to extract information from large quantities of data. One of those techniques, reservoir computing (RC), is a decade old and has achieved state-of-the-art performance for processing sequential data. Dedicated hardware realizations of RC could enable speed gains and power savings. Here we propose the first integrated passive silicon photonics reservoir. We demonstrate experimentally and through simulations that, thanks to the RC paradigm, this generic chip can be used to perform arbitrary Boolean logic operations with memory as well as 5-bit header recognition up to 12.5 Gbit s(-1), without power consumption in the reservoir. It can also perform isolated spoken digit recognition. Our realization exploits optical phase for computing. It is scalable to larger networks and much higher bitrates, up to speeds >100 Gbit s(-1). These results pave the way for the application of integrated photonic RC for a wide range of applications.}},
  articleno    = {{3541}},
  author       = {{Vandoorne, Kristof and Mechet, Pauline and Van Vaerenbergh, Thomas and Fiers, Martin and Morthier, Geert and Verstraeten, David and Schrauwen, Benjamin and Dambre, Joni and Bienstman, Peter}},
  issn         = {{2041-1723}},
  journal      = {{NATURE COMMUNICATIONS}},
  keywords     = {{SPEECH RECOGNITION,PATTERN-RECOGNITION,CIRCUITS,SYSTEM,STATES,NODE}},
  language     = {{eng}},
  pages        = {{6}},
  title        = {{Experimental demonstration of reservoir computing on a silicon photonics chip}},
  url          = {{http://dx.doi.org/10.1038/ncomms4541}},
  volume       = {{5}},
  year         = {{2014}},
}

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