Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Martin Sevior"'
Publikováno v:
PRX Quantum, Vol 5, Iss 3, p 030320 (2024)
Exploiting the power of quantum computation to realize superior machine learning algorithms has been a major research focus of recent years, but the prospects of quantum machine learning (QML) remain dampened by considerable technical challenges. A p
Externí odkaz:
https://doaj.org/article/8f062f32ce8b4a8491c81c4b59bd15c2
Autor:
Maxwell T. West, Azar C. Nakhl, Jamie Heredge, Floyd M. Creevey, Lloyd C. L. Hollenberg, Martin Sevior, Muhammad Usman
Publikováno v:
Intelligent Computing, Vol 3 (2024)
Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realization for practical applications remains impeded by challenges. Among these, a key barrier is the computa
Externí odkaz:
https://doaj.org/article/f03692d5358a4a4ebe6e38d209b03a5f
Autor:
Maxwell T. West, Sarah M. Erfani, Christopher Leckie, Martin Sevior, Lloyd C. L. Hollenberg, Muhammad Usman
Publikováno v:
Physical Review Research, Vol 5, Iss 2, p 023186 (2023)
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology, and industry. Despite their accuracy and sophistication, neural networks can be easily fooled by carefully designed malici
Externí odkaz:
https://doaj.org/article/5a4293add51c45b8a72693e77d943aa8
Publikováno v:
Machine Learning: Science and Technology, Vol 4, Iss 3, p 035027 (2023)
Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding its scale up. In particular, there is an emerging body of work which
Externí odkaz:
https://doaj.org/article/e64effd493ec4c15b23defd76f91f414
Autor:
Thomas E Browder, Kenkichi Miyabayashi, Tadeas Bilka, Saurabh Sandilya, Shawn Dubey, Lu Cao, Jan Strube, Lopamudra Nayak, Raynette Van Tonder, Michel Enrique Hernández Villanueva, Bruce Yabsley, Evgeniy Kovalenko, Andrii Natochii, Sam Cunliffe, Thanh Dong, Marcello Campajola, Masako Iwasaki, Florian Bernlochner, Hiroaki Ono, Martin Sevior, Tianping Gu, Sourav Patra, Valentina Zhukova, Giacomo De Pietro, Konstantin Belous, Felix Metzner, Sven Vahsen, Chia-Ling Hsu, Elena Solovieva, Kirill Chilikin
Publikováno v:
Physical Review Letters. 127
Autor:
Thomas E Browder, Kenkichi Miyabayashi, Tadeas Bilka, Saurabh Sandilya, Andrzej Bożek, Lopamudra Nayak, Evgeniy Kovalenko, Anna Vinokurova, Andrii Natochii, Sam Cunliffe, Thanh Dong, Marcello Campajola, Masako Iwasaki, Alexander Bondar, Jens Sören Lange, Hiroaki Ono, Martin Sevior, Sourav Patra, Valentina Zhukova, Felix Metzner, Makoto Takizawa, Chia-Ling Hsu, Elena Solovieva, Kirill Chilikin
Publikováno v:
Physical Review D. 104
Autor:
Minakshi Nayak, Thomas E Browder, Kenkichi Miyabayashi, Tadeas Bilka, Saurabh Sandilya, Andrzej Bożek, Shawn Dubey, Lopamudra Nayak, Bruce Yabsley, Evgeniy Kovalenko, Anna Vinokurova, Andrii Natochii, Sam Cunliffe, Thanh Dong, Marcello Campajola, Masako Iwasaki, Zbigniew Natkaniec, Jens Sören Lange, Hiroaki Ono, Martin Sevior, Tianping Gu, BIPUL BHUYAN, Valentina Zhukova, Giacomo De Pietro, Konstantin Belous, Felix Metzner, Sven Vahsen, Chia-Ling Hsu, Elena Solovieva, Kirill Chilikin
Publikováno v:
Physical Review D. 104
Autor:
Kenkichi Miyabayashi, Tadeas Bilka, Saurabh Sandilya, Andrzej Bożek, Lopamudra Nayak, Shohei Nishida, Bruce Yabsley, Evgeniy Kovalenko, Anna Vinokurova, Andrii Natochii, Sam Cunliffe, Thanh Dong, Marcello Campajola, Chengping Shen, Masako Iwasaki, Zbigniew Natkaniec, Jens Sören Lange, Hiroaki Ono, Martin Sevior, Tianping Gu, BIPUL BHUYAN, Takanori HARA, Valentina Zhukova, Giacomo De Pietro, Konstantin Belous, Felix Metzner, Makoto Takizawa, Sven Vahsen, Chia-Ling Hsu, Elena Solovieva, Kirill Chilikin
Publikováno v:
Physical Review D. 104
We thanktheKEKBgroup for the excellentoperation of the accelerator; the KEK cryogenics group for the efficient operation of the solenoid; and the KEK computer group, and the Pacific Northwest National Laboratory (PNNL) EnvironmentalMolecular Sciences
Autor:
Tadeas Bilka, Saurabh Sandilya, Jan Strube, Armine Rostomyan, Shohei Nishida, Sam Cunliffe, Thanh Dong, Marcello Campajola, Masako Iwasaki, Hiroaki Ono, Martin Sevior, Torben Ferber, Valentina Zhukova, Guido Russo, Elena Solovieva, Kirill Chilikin
Publikováno v:
Physical Review D. 103
We acknowledge support from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan, the Japan Society for the Promotion of Science (JSPS), and the Tau-Lepton Physics Research Center of Nagoya University; the Australian Re
Quantum computers have the potential to speed up certain computational tasks. A possibility this opens up within the field of machine learning is the use of quantum techniques that may be inefficient to simulate classically but could provide superior
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2165c342599fa7819031dcb763d127e8
http://arxiv.org/abs/2103.12257
http://arxiv.org/abs/2103.12257