Ultrafast neuromorphic photonic image processing with a VCSEL neuron
Abstract The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-08703-1 |
| _version_ | 1811335426650144768 |
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| author | Joshua Robertson Paul Kirkland Juan Arturo Alanis Matěj Hejda Julián Bueno Gaetano Di Caterina Antonio Hurtado |
| author_facet | Joshua Robertson Paul Kirkland Juan Arturo Alanis Matěj Hejda Julián Bueno Gaetano Di Caterina Antonio Hurtado |
| author_sort | Joshua Robertson |
| collection | DOAJ |
| description | Abstract The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon vertical cavity surface emitting lasers (VCSELs) are attracting interest given their favourable attributes and mature technology. Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor, using a single VCSEL, for all-optical image edge-feature detection. This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100 ps-long) optical spikes upon detecting desired image features. Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. This work therefore highlights the potential of VCSEL-based platforms for novel, ultrafast, all-optical neuromorphic processors interfacing with current computation and communication systems for use in future light-enabled AI and computer vision functionalities. |
| first_indexed | 2024-04-13T17:24:03Z |
| format | Article |
| id | doaj.art-5208e76956e649bfb9d7d3d372411e24 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T17:24:03Z |
| publishDate | 2022-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-5208e76956e649bfb9d7d3d372411e242022-12-22T02:37:51ZengNature PortfolioScientific Reports2045-23222022-03-0112111010.1038/s41598-022-08703-1Ultrafast neuromorphic photonic image processing with a VCSEL neuronJoshua Robertson0Paul Kirkland1Juan Arturo Alanis2Matěj Hejda3Julián Bueno4Gaetano Di Caterina5Antonio Hurtado6SUPA Department of Physics, Institute of Photonics, TIC Centre, University of StrathclydeDepartment of Electronic and Electrical Engineering, University of StrathclydeSUPA Department of Physics, Institute of Photonics, TIC Centre, University of StrathclydeSUPA Department of Physics, Institute of Photonics, TIC Centre, University of StrathclydeSUPA Department of Physics, Institute of Photonics, TIC Centre, University of StrathclydeDepartment of Electronic and Electrical Engineering, University of StrathclydeSUPA Department of Physics, Institute of Photonics, TIC Centre, University of StrathclydeAbstract The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon vertical cavity surface emitting lasers (VCSELs) are attracting interest given their favourable attributes and mature technology. Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor, using a single VCSEL, for all-optical image edge-feature detection. This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100 ps-long) optical spikes upon detecting desired image features. Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. This work therefore highlights the potential of VCSEL-based platforms for novel, ultrafast, all-optical neuromorphic processors interfacing with current computation and communication systems for use in future light-enabled AI and computer vision functionalities.https://doi.org/10.1038/s41598-022-08703-1 |
| spellingShingle | Joshua Robertson Paul Kirkland Juan Arturo Alanis Matěj Hejda Julián Bueno Gaetano Di Caterina Antonio Hurtado Ultrafast neuromorphic photonic image processing with a VCSEL neuron Scientific Reports |
| title | Ultrafast neuromorphic photonic image processing with a VCSEL neuron |
| title_full | Ultrafast neuromorphic photonic image processing with a VCSEL neuron |
| title_fullStr | Ultrafast neuromorphic photonic image processing with a VCSEL neuron |
| title_full_unstemmed | Ultrafast neuromorphic photonic image processing with a VCSEL neuron |
| title_short | Ultrafast neuromorphic photonic image processing with a VCSEL neuron |
| title_sort | ultrafast neuromorphic photonic image processing with a vcsel neuron |
| url | https://doi.org/10.1038/s41598-022-08703-1 |
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