Zobrazeno 1 - 10
of 2 331
pro vyhledávání: '"Cerati Giuseppe"'
Autor:
Cerati Giuseppe, Elmer Peter, Gartung Patrick, Giannini Leonardo, Kortelainen Matti, Krutelyov Vyacheslav, Lantz Steven, Masciovecchio Mario, Reid Tres, Reinsvold Hall Allison, Riley Daniel, Tadel Matevž, Vourliotis Emmanouil, Wittich Peter, Yagil Avi
Publikováno v:
EPJ Web of Conferences, Vol 295, p 03019 (2024)
mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both threadand data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of
Externí odkaz:
https://doaj.org/article/0992a8c531284e728766cd6a7c346298
Autor:
Cerati Giuseppe
Publikováno v:
EPJ Web of Conferences, Vol 295, p 08012 (2024)
Among liquid argon time projection chamber (LArTPC) experiments MicroBooNE is the one that continually took physics data for the longest time (2015-2021), and represents the state of the art for reconstruction and analysis with this detector. Recentl
Externí odkaz:
https://doaj.org/article/27cea8fea0a74a32a16c13db3132ade2
Autor:
Kwok Ka Hei Martin, Kortelainen Matti, Cerati Giuseppe, Strelchenko Alexei, Gutsche Oliver, Reinsvold Hall Allison, Lantz Steve, Reid Michael, Riley Daniel, Berkman Sophie, Lee Seyong, Ather Hammad, Norris Boyana, Wang Cong
Publikováno v:
EPJ Web of Conferences, Vol 295, p 11003 (2024)
Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the ne
Externí odkaz:
https://doaj.org/article/90294617e7674b33a7736f41bb784ea1
Autor:
Hewes, V, Aurisano, Adam, Cerati, Giuseppe, Kowalkowski, Jim, Lee, Claire, Liao, Wei-keng, Grzenda, Daniel, Gumpula, Kaushal, Zhang, Xiaohe
Liquid Argon Time Projection Chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction technique
Externí odkaz:
http://arxiv.org/abs/2403.11872
Autor:
Kwok, Ka Hei Martin, Kortelainen, Matti, Cerati, Giuseppe, Strelchenko, Alexei, Gutsche, Oliver, Hall, Allison Reinsvold, Lantz, Steve, Reid, Michael, Riley, Daniel, Berkman, Sophie, Lee, Seyong, Ather, Hammad, Norris, Boyana, Wang, Cong
Next generation High-Energy Physics (HEP) experiments are presented with significant computational challenges, both in terms of data volume and processing power. Using compute accelerators, such as GPUs, is one of the promising ways to provide the ne
Externí odkaz:
http://arxiv.org/abs/2401.14221
Autor:
Cerati, Giuseppe, Elmer, Peter, Gartung, Patrick, Giannini, Leonardo, Kortelainen, Matti, Krutelyov, Vyacheslav, Lantz, Steven, Masciovecchio, Mario, Reid, Tres, Hall, Allison Reinsvold, Riley, Daniel, Tadel, Matevz, Vourliotis, Emmanouil, Wittich, Peter, Yagil, Avi
mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow
Externí odkaz:
http://arxiv.org/abs/2312.11728
Autor:
Cerati, Giuseppe
Among liquid argon time projection chamber (LArTPC) experiments MicroBooNE is the one that continually took physics data for the longest time (2015-2021), and represents the state of the art for reconstruction and analysis with this detector. Recentl
Externí odkaz:
http://arxiv.org/abs/2309.15362
Autor:
Hewes Jeremy, Aurisano Adam, Cerati Giuseppe, Kowalkowski Jim, Lee Claire, Liao Wei-keng, Day Alexandra, Agrawal Ankit, Spiropulu Maria, Vlimant Jean-Roch, Gray Lindsey, Klijnsma Thomas, Calafiura Paolo, Conlon Sean, Farrell Steve, Ju Xiangyang, Murnane Daniel
Publikováno v:
EPJ Web of Conferences, Vol 251, p 03054 (2021)
This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar
Externí odkaz:
https://doaj.org/article/c67ce5e63cd34f69b730ef8fededbcd9
Autor:
Berkman Sophie, Cerati Giuseppe, Gravelle Brian, Norris Boyana, Reinsvold Hall Allison, Wang Michael
Publikováno v:
EPJ Web of Conferences, Vol 245, p 02012 (2020)
Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is becoming more difficult as the detectors increase in size to reach their
Externí odkaz:
https://doaj.org/article/1655f3a050c9421bba639fc862022d96
Autor:
Cerati Giuseppe, Elmer Peter, Gravelle Brian, Kortelainen Matti, Krutelyov Vyacheslav, Lantz Steven, Masciovecchio Mario, McDermott Kevin, Norris Boyana, Reid Michael, Reinsvold Hall Allison, Riley Daniel, Tadel Matevž, Wittich Peter, Wang Bei, Würthwein Frank, Yagil Avraham
Publikováno v:
EPJ Web of Conferences, Vol 245, p 02013 (2020)
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which
Externí odkaz:
https://doaj.org/article/0784d197ad844f998617f206fb739c8a