Zobrazeno 1 - 10
of 199
pro vyhledávání: '"TUFTE, GUNNAR"'
Autor:
Jensen, Johannes H., Strømberg, Anders, Breivik, Ida, Penty, Arthur, Foerster, Michael, Niño, Miguel Angel, Khaliq, Muhammad Waqas, Tufte, Gunnar, Folven, Erik
Publikováno v:
Nat Commun 15, 964 (2024)
Artificial spin ice (ASI) are nanomagnetic metamaterials exhibiting a wide range of emergent properties, which have recently shown promise for neuromorphic computing. However, the lack of efficient protocols to control the state evolution of these me
Externí odkaz:
http://arxiv.org/abs/2306.07388
In living systems, we often see the emergence of the ingredients necessary for computation -- the capacity for information transmission, storage, and modification -- begging the question of how we may exploit or imitate such biological systems in unc
Externí odkaz:
http://arxiv.org/abs/2009.04518
Autor:
Jensen, Johannes H., Strømberg, Anders, Lykkebø, Odd Rune, Penty, Arthur, Själander, Magnus, Folven, Erik, Tufte, Gunnar
Publikováno v:
Phys. Rev. B 106, 064408 (2022)
We present flatspin, a novel simulator for systems of interacting mesoscopic spins on a lattice, also known as artificial spin ice (ASI). Our magnetic switching criteria enables ASI dynamics to be captured in a dipole model. Through GPU acceleration,
Externí odkaz:
http://arxiv.org/abs/2002.11401
The pursuit of many research questions requires massive computational resources. State-of-the-art research in physical processes using simulations, the training of neural networks for deep learning, or the analysis of big data are all dependent on th
Externí odkaz:
http://arxiv.org/abs/1912.05848
Autor:
Heiney, Kristine, Valderhaug, Vibeke Devold, Sandvig, Ioanna, Sandvig, Axel, Tufte, Gunnar, Hammer, Hugo Lewi, Nichele, Stefano
Novel computing hardwares are necessary to keep up with today's increasing demand for data storage and processing power. In this research project, we turn to the brain for inspiration to develop novel computing substrates that are self-learning, scal
Externí odkaz:
http://arxiv.org/abs/1907.02351
Autor:
Pontes-Filho, Sidney, Yazidi, Anis, Zhang, Jianhua, Hammer, Hugo, Mello, Gustavo B. M., Sandvig, Ioanna, Tufte, Gunnar, Nichele, Stefano
Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural network (ANN). Initially, we implement the simplest dynamical system, a c
Externí odkaz:
http://arxiv.org/abs/1907.01856
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