Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Bhavin J Shastri"'
Autor:
Matěj Hejda, Eli A Doris, Simon Bilodeau, Joshua Robertson, Dafydd Owen-Newns, Bhavin J Shastri, Paul R Prucnal, Antonio Hurtado
Publikováno v:
Neuromorphic Computing and Engineering, Vol 4, Iss 2, p 024011 (2024)
Spiking neurons and neural networks constitute a fundamental building block for brain-inspired computing, which is poised to benefit significantly from photonic hardware implementations. In this work, we experimentally investigate an interconnected o
Externí odkaz:
https://doaj.org/article/72d3b5a2041344fbbe1c558d426e1f2c
Publikováno v:
Communications Physics, Vol 7, Iss 1, Pp 1-7 (2024)
Abstract Increasingly, artificial intelligent systems look to neuromorphic photonics for its speed and its low loss, high bandwidth interconnects. Silicon photonics has shown promise to enable the creation of large scale neural networks. Here, we pro
Externí odkaz:
https://doaj.org/article/c68f8e88b0ef43bc8e5939466f8c7c86
Autor:
Joshua C. Lederman, Simon Bilodeau, Eli Doris, Eric C. Blow, Weipeng Zhang, Yusuf Jimoh, Bhavin J. Shastri, Paul R. Prucnal
Publikováno v:
APL Photonics, Vol 9, Iss 7, Pp 076117-076117-10 (2024)
Analog photonic information processing can be implemented with low chip area using wavelength-division multiplexed systems, which typically manipulate light using micro-ring resonators. Micro-rings are uniquely susceptible to thermal crosstalk, with
Externí odkaz:
https://doaj.org/article/0b5b98e6bf004965bb706d949e3dbd1c
Autor:
Jagmeet Singh, Hugh Morison, Zhimu Guo, Bicky A. Marquez, Omid Esmaeeli, Paul R. Prucnal, Lukas Chrostowski, Sudip Shekhar, Bhavin J. Shastri
Publikováno v:
APL Photonics, Vol 7, Iss 4, Pp 046103-046103-14 (2022)
One of the significant challenges in neuromorphic photonic architectures is the lack of good tools to simulate large-scale photonic integrated circuits. It is crucial to perform simulations on a single platform to capture the circuit’s behavior in
Externí odkaz:
https://doaj.org/article/8242f8490b0349ddae03f81957f51b44
Autor:
Chaoran Huang, Volker J. Sorger, Mario Miscuglio, Mohammed Al-Qadasi, Avilash Mukherjee, Lutz Lampe, Mitchell Nichols, Alexander N. Tait, Thomas Ferreira de Lima, Bicky A. Marquez, Jiahui Wang, Lukas Chrostowski, Mable P. Fok, Daniel Brunner, Shanhui Fan, Sudip Shekhar, Paul R. Prucnal, Bhavin J. Shastri
Publikováno v:
Advances in Physics: X, Vol 7, Iss 1 (2022)
Neural networks have enabled applications in artificial intelligence through machine learning, and neuromorphic computing. Software implementations of neural networks on conventional computers that have separate memory and processor (and that operate
Externí odkaz:
https://doaj.org/article/b3c47388277c4f63929bcfe87ddd1369
Publikováno v:
IEEE Journal of Selected Topics in Quantum Electronics. 29:1-8
Autor:
Mohammadreza Sanadgol Nezami, Thomas Ferreira de Lima, Matthew Mitchell, Shangxuan Yu, Jing Wang, Simon Bilodeau, Weipeng Zhang, Mohammed Al-Qadasi, Iman Taghavi, Alexander Tofini, Stephen Lin, Bhavin J. Shastri, Paul R. Prucnal, Lukas Chrostowski, Sudip Shekhar
Publikováno v:
IEEE Journal of Selected Topics in Quantum Electronics. 29:1-11
Publikováno v:
IEEE Journal of Selected Topics in Quantum Electronics. 29:1-12
Publikováno v:
Nanophotonics. 12:833-845
Emerging neuromorphic hardware promises to solve certain problems faster and with higher energy efficiency than traditional computing by using physical processes that take place at the device level as the computational primitives in neural networks.
Publikováno v:
Journal of Lightwave Technology. :1-14
The explosion of artificial intelligence and machine-learning algorithms, connected to the exponential growth of the exchanged data, is driving a search for novel application-specific hardware accelerators. Among the many, the photonics field appears