Zobrazeno 1 - 10
of 196
pro vyhledávání: '"Sun Shaojun"'
Publikováno v:
EPJ Web of Conferences, Vol 245, p 03027 (2020)
ATLAS@Home is a volunteer computing project which enables members of the public to contribute computing power to run simulations of the ATLAS experiment at CERN’s Large Hadron Collider. The computing resources provided to ATLAS@Home increasingly co
Externí odkaz:
https://doaj.org/article/132e22d79a8f4d71b0242efee44ba523
Autor:
Lee Christopher Jon, Di Girolamo Alessandro, Elmsheuser Johannes, Buzykaev Alexey, Obreshkov Emil, Glushkov Ivan, Sun Shaojun
Publikováno v:
EPJ Web of Conferences, Vol 214, p 03061 (2019)
The ATLAS Distributed Computing (ADC) Project is responsible for the off-line processing of data produced by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. It facilitates data and workload management for ATLAS computing on the World
Externí odkaz:
https://doaj.org/article/9d2d0de26c454a37aec48748a1b78ed3
Autor:
Sun, Shaojun, Zhang, Chunyan, Ran, Mingxin, Zheng, Yujie, Li, Chuanhua, Jiang, Yu, Yan, Xuemin
Publikováno v:
In International Journal of Hydrogen Energy 18 April 2024 63:133-141
Autor:
Wu, Sau Lan, Sun, Shaojun, Guan, Wen, Zhou, Chen, Chan, Jay, Cheng, Chi Lung, Pham, Tuan, Qian, Yan, Wang, Alex Zeng, Zhang, Rui, Livny, Miron, Glick, Jennifer, Barkoutsos, Panagiotis Kl., Woerner, Stefan, Tavernelli, Ivano, Carminati, Federico, Di Meglio, Alberto, Li, Andy C. Y., Lykken, Joseph, Spentzouris, Panagiotis, Chen, Samuel Yen-Chi, Yoo, Shinjae, Wei, Tzu-Chieh
Publikováno v:
Phys. Rev. Research 3, 033221 (2021)
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In this study, we employ a support vector machine with a quantum kernel e
Externí odkaz:
http://arxiv.org/abs/2104.05059
Autor:
Wu, Sau Lan, Chan, Jay, Guan, Wen, Sun, Shaojun, Wang, Alex, Zhou, Chen, Livny, Miron, Carminati, Federico, Di Meglio, Alberto, Li, Andy C. Y., Lykken, Joseph, Spentzouris, Panagiotis, Chen, Samuel Yen-Chi, Yoo, Shinjae, Wei, Tzu-Chieh
One of the major objectives of the experimental programs at the LHC is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using machine learning algorithms greatly enhances our ability to achieve th
Externí odkaz:
http://arxiv.org/abs/2012.11560
Autor:
Ahn Natalie, Kurgan Lukasz, Sun Shaojun, Gehrke Allison, Resing Katheryn, Kafadar Karen, Cios Krzysztof
Publikováno v:
BMC Bioinformatics, Vol 9, Iss 1, p 515 (2008)
Abstract Background Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived spec
Externí odkaz:
https://doaj.org/article/0b54a6db880549f794352acbe23cc3a2
Publikováno v:
In Journal of Energy Storage 30 August 2023 66
Akademický článek
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Publikováno v:
In Microvascular Research September 2022 143
Publikováno v:
In Biomedicine & Pharmacotherapy August 2018 104:832-840