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. 2017 Aug 7;7:7430. doi: 10.1038/s41598-017-07754-z

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Photonic CTRNN benchmarking against a CPU. (a,b) Phase diagrams of the Lorenz attractor simulated by a conventional CPU (a) and a photonic CTRNN (b). (c,d) Time traces of simulation variables for a conventional CPU (c) and a photonic CTRNN (d). The horizontal axes are labeled in physical real time, and cover equal intervals of virtual simulation time, as benchmarked by γ _CPU and γ _Pho. The ratio of real-time values of γ’s indicates a 294-fold acceleration. (e) Time traces of modulator voltages s _i (minor y-axis) for each modulator neuron i (major y-axis) in the photonic CTRNN. The simulation variables, x, in (d) are linear decodings of physical variables, s, in (e).