Zobrazeno 1 - 10
of 349
pro vyhledávání: '"Kilian, D."'
Autor:
Youel, Harry, Prestwood, Daniel, Lee, Oscar, Wei, Tianyi, Stenning, Kilian D., Gartside, Jack C., Branford, Will R., Everschor-Sitte, Karin, Kurebayashi, Hidekazu
Physical reservoir computing (PRC) is a computing framework that harnesses the intrinsic dynamics of physical systems for computation. It offers a promising energy-efficient alternative to traditional von Neumann computing for certain tasks, particul
Externí odkaz:
http://arxiv.org/abs/2410.18356
Autor:
Manneschi, Luca, Vidamour, Ian T., Stenning, Kilian D., Swindells, Charles, Venkat, Guru, Griffin, David, Gui, Lai, Sonawala, Daanish, Donskikh, Denis, Hariga, Dana, Stepney, Susan, Branford, Will R., Gartside, Jack C., Hayward, Thomas, Ellis, Matthew O. A., Vasilaki, Eleni
Physical computing has the potential to enable widespread embodied intelligence by leveraging the intrinsic dynamics of complex systems for efficient sensing, processing, and interaction. While individual devices provide basic data processing capabil
Externí odkaz:
http://arxiv.org/abs/2401.07387
Autor:
Dion, Troy, Stenning, Kilian D., Vanstone, Alex, Holder, Holly H., Sultana, Rawnak, Alatteili, Ghanem, Martinez, Victoria, Kaffash, Mojtaba Taghipour, Kimura, Takashi, Oulton, Rupert, Kurebayashi, Hidekazu, Branford, Will R., Iacocca, Ezio, Jungfleisch, Benjamin M., Gartside, Jack C.
Publikováno v:
Nature Communications 15.1 (2024): 4077
Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems may be b
Externí odkaz:
http://arxiv.org/abs/2306.16159
Autor:
Kilian D. Stenning, Jack C. Gartside, Luca Manneschi, Christopher T. S. Cheung, Tony Chen, Alex Vanstone, Jake Love, Holly Holder, Francesco Caravelli, Hidekazu Kurebayashi, Karin Everschor-Sitte, Eleni Vasilaki, Will R. Branford
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to i
Externí odkaz:
https://doaj.org/article/1b9a5b0ed0ff4844bcb8ea4ebed5879d
Autor:
Stenning, Kilian D., Gartside, Jack C., Manneschi, Luca, Cheung, Christopher T. S., Chen, Tony, Vanstone, Alex, Love, Jake, Holder, Holly H., Caravelli, Francesco, Kurebayashi, Hidekazu, Everschor-Sitte, Karin, Vasilaki, Eleni, Branford, Will R.
Publikováno v:
Nature Communications 2024
Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its relian
Externí odkaz:
http://arxiv.org/abs/2211.06373
Autor:
Beaudin, Gabrielle, Désilets-Benoit, Alexandre, Bianchi, Andrea Daniele, Arnold, Robert, Samothrakitis, Stavros, Stenning, Kilian D., Laver, Mark, Gerber, Simon, Leo, Nikola Anna Galvan, Gavilano, Jorge L., Kenzelmann, Michel, Nicklas, Michael
We conducted a small-angle neutron scattering experiments (SANS) on the ferromagnetic semi-metal EuB$_6$, where we observed direct evidence for the presence of magnetic polarons. We carried out SANS experiments over a large range of scattering vector
Externí odkaz:
http://arxiv.org/abs/2210.12210
Autor:
Lee, Oscar, Wei, Tianyi, Stenning, Kilian D., Gartside, Jack C., Prestwood, Dan, Seki, Shinichiro, Aqeel, Aisha, Karube, Kosuke, Kanazawa, Naoya, Taguchi, Yasujiro, Back, Christian, Tokura, Yoshinori, Branford, Will R., Kurebayashi, Hidekazu
Reservoir computing is a neuromorphic architecture that potentially offers viable solutions to the growing energy costs of machine learning. In software-based machine learning, neural network properties and performance can be readily reconfigured to
Externí odkaz:
http://arxiv.org/abs/2209.06962
Autor:
Troy Dion, Kilian D. Stenning, Alex Vanstone, Holly H. Holder, Rawnak Sultana, Ghanem Alatteili, Victoria Martinez, Mojtaba Taghipour Kaffash, Takashi Kimura, Rupert F. Oulton, Will R. Branford, Hidekazu Kurebayashi, Ezio Iacocca, M. Benjamin Jungfleisch, Jack C. Gartside
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Strongly-interacting nanomagnetic arrays are ideal systems for exploring reconfigurable magnonics. They provide huge microstate spaces and integrated solutions for storage and neuromorphic computing alongside GHz functionality. These systems
Externí odkaz:
https://doaj.org/article/5541a8dd1a6341e182d00fd0bdbf46a3
Autor:
Saccone, Michael, Gartside, Jack C., Stenning, Kilian D., Branford, Will R., Caravelli, Francesco
Publikováno v:
Featured article in Physics of Fluids (2023)
Recent studies in magnetic nanolithography show that a variety of complex magnetic states emerge as a function of a single magnetic island's aspect ratio. We propose a model which, in addition to fitting experiments, predicts magnetic states with con
Externí odkaz:
http://arxiv.org/abs/2208.06391
Autor:
Stenning, Kilian D., Xiao, Xiaofei, Holder, Holly H., Gartside, Jack C., Vanstone, Alex, Kennedy, Oscar W., Oulton, Rupert F., Branford, Will R.
All-optical magnetic switching promises ultrafast, high-resolution magnetisation control with the technological attraction of requiring no magnetic field. Existing all-optical switching schemes are driven by ultrafast transient effects, typically req
Externí odkaz:
http://arxiv.org/abs/2112.00697