Neuromorphic Photonics Circuits: Contemporary Review
Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Nanomaterials |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-4991/13/24/3139 |
| _version_ | 1797379856100491264 |
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| author | Ruslan V. Kutluyarov Aida G. Zakoyan Grigory S. Voronkov Elizaveta P. Grakhova Muhammad A. Butt |
| author_facet | Ruslan V. Kutluyarov Aida G. Zakoyan Grigory S. Voronkov Elizaveta P. Grakhova Muhammad A. Butt |
| author_sort | Ruslan V. Kutluyarov |
| collection | DOAJ |
| description | Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain. Using optics and photonics principles, neuromorphic devices can execute intricate computations swiftly and with impressive energy efficiency. This innovation holds promise for advancing artificial intelligence and machine learning while addressing the limitations of traditional silicon-based computing. Neuromorphic photonics could herald a new era of computing that is more potent and draws inspiration from cognitive processes, leading to advancements in robotics, pattern recognition, and advanced data processing. This paper reviews the recent developments in neuromorphic photonic integrated circuits, applications, and current challenges. |
| first_indexed | 2024-03-08T20:29:04Z |
| format | Article |
| id | doaj.art-82d6a8ebd24a4f038bfe3d71eb26f90f |
| institution | Directory Open Access Journal |
| issn | 2079-4991 |
| language | English |
| last_indexed | 2024-03-08T20:29:04Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nanomaterials |
| spelling | doaj.art-82d6a8ebd24a4f038bfe3d71eb26f90f2023-12-22T14:29:14ZengMDPI AGNanomaterials2079-49912023-12-011324313910.3390/nano13243139Neuromorphic Photonics Circuits: Contemporary ReviewRuslan V. Kutluyarov0Aida G. Zakoyan1Grigory S. Voronkov2Elizaveta P. Grakhova3Muhammad A. Butt4School of Photonics Engineering and Research Advances (SPhERA), Ufa University of Science and Technology, 32, Z. Validi St., 450076 Ufa, RussiaSchool of Photonics Engineering and Research Advances (SPhERA), Ufa University of Science and Technology, 32, Z. Validi St., 450076 Ufa, RussiaSchool of Photonics Engineering and Research Advances (SPhERA), Ufa University of Science and Technology, 32, Z. Validi St., 450076 Ufa, RussiaSchool of Photonics Engineering and Research Advances (SPhERA), Ufa University of Science and Technology, 32, Z. Validi St., 450076 Ufa, RussiaSamara National Research University, 443086 Samara, RussiaNeuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain. Using optics and photonics principles, neuromorphic devices can execute intricate computations swiftly and with impressive energy efficiency. This innovation holds promise for advancing artificial intelligence and machine learning while addressing the limitations of traditional silicon-based computing. Neuromorphic photonics could herald a new era of computing that is more potent and draws inspiration from cognitive processes, leading to advancements in robotics, pattern recognition, and advanced data processing. This paper reviews the recent developments in neuromorphic photonic integrated circuits, applications, and current challenges.https://www.mdpi.com/2079-4991/13/24/3139neuromorphic computingphotonic integrated circuitimagingartificial intelligencemachine learning |
| spellingShingle | Ruslan V. Kutluyarov Aida G. Zakoyan Grigory S. Voronkov Elizaveta P. Grakhova Muhammad A. Butt Neuromorphic Photonics Circuits: Contemporary Review Nanomaterials neuromorphic computing photonic integrated circuit imaging artificial intelligence machine learning |
| title | Neuromorphic Photonics Circuits: Contemporary Review |
| title_full | Neuromorphic Photonics Circuits: Contemporary Review |
| title_fullStr | Neuromorphic Photonics Circuits: Contemporary Review |
| title_full_unstemmed | Neuromorphic Photonics Circuits: Contemporary Review |
| title_short | Neuromorphic Photonics Circuits: Contemporary Review |
| title_sort | neuromorphic photonics circuits contemporary review |
| topic | neuromorphic computing photonic integrated circuit imaging artificial intelligence machine learning |
| url | https://www.mdpi.com/2079-4991/13/24/3139 |
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