Zobrazeno 1 - 10
of 2 331
pro vyhledávání: '"Cerati , Giuseppe"'
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:
Berkman, Sophie, Cerati, Giuseppe, Elmer, Peter, Gartung, Patrick, Giannini, Leonardo, Gravelle, Brian, Hall, Allison R., Kortelainen, Matti, Krutelyov, Vyacheslav, Lantz, Steve R., Masciovecchio, Mario, McDermott, Kevin, Norris, Boyana, Reid, Michael, Riley, Daniel S., Tadel, Matevž, Vourliotis, Emmanouil, Wang, Bei, Wittich, Peter, Yagil, Avraham
One of the most challenging computational problems in the Run 3 of the Large Hadron Collider (LHC) and more so in the High-Luminosity LHC (HL-LHC) is expected to be finding and fitting charged-particle tracks during event reconstruction. The methods
Externí odkaz:
http://arxiv.org/abs/2304.05853
Autor:
Cerati, Giuseppe1 MICROBOONE_INFO@fnal.gov
Publikováno v:
EPJ Web of Conferences. 5/6/2024, Vol. 295, p1-8. 8p.
Autor:
Cerati, Giuseppe1, Elmer, Peter2, Gartung, Patrick1, Giannini, Leonardo3, Kortelainen, Matti1, Krutelyov, Vyacheslav3, Lantz, Steven4, Masciovecchio, Mario3, Reid, Tres4, Reinsvold Hall, Allison5, Riley, Daniel4, Tadel, Matevž3 mtadel@ucsd.edu, Vourliotis, Emmanouil3, Wittich, Peter4, Yagil, Avi3
Publikováno v:
EPJ Web of Conferences. 5/6/2024, Vol. 295, p1-8. 8p.
Autor:
Casper, Dave, Monzani, Maria Elena, Nachman, Benjamin, Andreopoulos, Costas, Bailey, Stephen, Bard, Deborah, Bhimji, Wahid, Cerati, Giuseppe, Chachamis, Grigorios, Daughhetee, Jacob, Diamond, Miriam, Elvira, V. Daniel, Fan, Alden, Genser, Krzysztof, Girotti, Paolo, Kravitz, Scott, Kutschke, Robert, Pascuzzi, Vincent R., Perdue, Gabriel N., Snider, Erica, Sexton-Kennedy, Elizabeth, Stewart, Graeme Andrew, Szydagis, Matthew, Torrence, Eric, Tunnell, Christopher
This white paper briefly summarized key conclusions of the recent US Community Study on the Future of Particle Physics (Snowmass 2021) workshop on Software and Computing for Small High Energy Physics Experiments.
Comment: Contribution to Snowmas
Comment: Contribution to Snowmas
Externí odkaz:
http://arxiv.org/abs/2203.07645
Autor:
Wang, Chun-Yi, Ju, Xiangyang, Hsu, Shih-Chieh, Murnane, Daniel, Calafiura, Paolo, Farrell, Steven, Spiropulu, Maria, Vlimant, Jean-Roch, Aurisano, Adam, Hewes, V, Cerati, Giuseppe, Gray, Lindsey, Klijnsma, Thomas, Kowalkowski, Jim, Atkinson, Markus, Neubauer, Mark, DeZoort, Gage, Thais, Savannah, Ballow, Alexandra, Lazar, Alina, Caillou, Sylvain, Rougier, Charline, Stark, Jan, Vallier, Alexis, Sardain, Jad
Particle tracking is a challenging pattern recognition task at the Large Hadron Collider (LHC) and the High Luminosity-LHC. Conventional algorithms, such as those based on the Kalman Filter, achieve excellent performance in reconstructing the prompt
Externí odkaz:
http://arxiv.org/abs/2203.08800
Autor:
Lazar, Alina, Ju, Xiangyang, Murnane, Daniel, Calafiura, Paolo, Farrell, Steven, Xu, Yaoyuan, Spiropulu, Maria, Vlimant, Jean-Roch, Cerati, Giuseppe, Gray, Lindsey, Klijnsma, Thomas, Kowalkowski, Jim, Atkinson, Markus, Neubauer, Mark, DeZoort, Gage, Thais, Savannah, Hsu, Shih-Chieh, Aurisano, Adam, Hewes, V, Ballow, Alexandra, Acharya, Nirajan, Wang, Chun-yi, Liu, Emma, Lucas, Alberto
Recently, graph neural networks (GNNs) have been successfully used for a variety of particle reconstruction problems in high energy physics, including particle tracking. The Exa.TrkX pipeline based on GNNs demonstrated promising performance in recons
Externí odkaz:
http://arxiv.org/abs/2202.06929