Zobrazeno 1 - 10
of 1 362
pro vyhledávání: '"NEUBAUER, MARK A."'
Autor:
Badea, Anthony, Bean, Alice, Berry, Doug, Dickinson, Jennet, DiPetrillo, Karri, Fahim, Farah, Gray, Lindsey, Di Guglielmo, Giuseppe, Jiang, David, Kovach-Fuentes, Rachel, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Shekar, Danush, Swartz, Morris, Syal, Chinar, Tran, Nhan, Yoo, Jieun
Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. Wit
Externí odkaz:
http://arxiv.org/abs/2410.02945
Autor:
Parpillon, Benjamin, Syal, Chinar, Yoo, Jieun, Dickinson, Jennet, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Douglas, Valentin, Manuel Blanco, DiPetrillo, Karri, Badea, Anthony, Gray, Lindsey, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Pradhan, Gauri, Tran, Nhan, Wen, Dahai, Fahim, Farah
We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-prin
Externí odkaz:
http://arxiv.org/abs/2406.14860
Autor:
Dickinson, Jennet, Kovach-Fuentes, Rachel, Gray, Lindsey, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Doug, Valentin, Manuel Blanco, DiPetrillo, Karri, Fahim, Farah, Hirschauer, James, Kulkarni, Shruti R., Lipton, Ron, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Pradhan, Gauri, Syal, Chinar, Tran, Nhan, Wen, Dahai, Yoo, Jieun, Young, Aaron
The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine
Externí odkaz:
http://arxiv.org/abs/2312.11676
Autor:
Yoo, Jieun, Dickinson, Jennet, Swartz, Morris, Di Guglielmo, Giuseppe, Bean, Alice, Berry, Douglas, Valentin, Manuel Blanco, DiPetrillo, Karri, Fahim, Farah, Gray, Lindsey, Hirschauer, James, Kulkarni, Shruti R., Lipton, Ron, Maksimovic, Petar, Mills, Corrinne, Neubauer, Mark S., Parpillon, Benjamin, Pradhan, Gauri, Syal, Chinar, Tran, Nhan, Wen, Dahai, Young, Aaron
Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the Hi
Externí odkaz:
http://arxiv.org/abs/2310.02474
Autor:
Feickert, Matthew, Katz, Daniel S., Neubauer, Mark S., Sexton-Kennedy, Elizabeth, Stewart, Graeme A.
In November 2022, the HEP Software Foundation and the Institute for Research and Innovation for Software in High-Energy Physics organized a workshop on the topic of Software Citation and Recognition in HEP. The goal of the workshop was to bring toget
Externí odkaz:
http://arxiv.org/abs/2309.14571
Autor:
Huang, Shi-Yu, Yang, Yun-Chen, Su, Yu-Ru, Lai, Bo-Cheng, Duarte, Javier, Hauck, Scott, Hsu, Shih-Chieh, Hu, Jin-Xuan, Neubauer, Mark S.
In-time particle trajectory reconstruction in the Large Hadron Collider is challenging due to the high collision rate and numerous particle hits. Using GNN (Graph Neural Network) on FPGA has enabled superior accuracy with flexible trajectory classifi
Externí odkaz:
http://arxiv.org/abs/2306.11330
Autor:
Agarwal, Manan, Alameda, Jay, Audenaert, Jeroen, Benoit, Will, Beveridge, Damon, Bhattacharya, Meghna, Chatterjee, Chayan, Chatterjee, Deep, Chen, Andy, Cholayil, Muhammed Saleem, Chou, Chia-Jui, Choudhary, Sunil, Coughlin, Michael, Dax, Maximilian, Desai, Aman, Di Luca, Andrea, Duarte, Javier Mauricio, Farrell, Steven, Feng, Yongbin, Goodarzi, Pooyan, Govorkova, Ekaterina, Graham, Matthew, Guiang, Jonathan, Gunny, Alec, Guo, Weichangfeng, Hakenmueller, Janina, Hawks, Ben, Hsu, Shih-Chieh, Jawahar, Pratik, Ju, Xiangyang, Katsavounidis, Erik, Kellis, Manolis, Khoda, Elham E, Lahbabi, Fatima Zahra, Lian, Van Tha Bik, Liu, Mia, Malanchev, Konstantin, Marx, Ethan, McCormack, William Patrick, McLeod, Alistair, Mo, Geoffrey, Moreno, Eric Anton, Muthukrishna, Daniel, Narayan, Gautham, Naylor, Andrew, Neubauer, Mark, Norman, Michael, Omer, Rafia, Pedro, Kevin, Peterson, Joshua, Pürrer, Michael, Raikman, Ryan, Raj, Shivam, Ricker, George, Robbins, Jared, Samani, Batool Safarzadeh, Scholberg, Kate, Schuy, Alex, Skliris, Vasileios, Soni, Siddharth, Sravan, Niharika, Sutton, Patrick, Villar, Victoria Ashley, Wang, Xiwei, Wen, Linqing, Wuerthwein, Frank, Yang, Tingjun, Yeh, Shu-Wei
Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and efficient w
Externí odkaz:
http://arxiv.org/abs/2306.08106
Autor:
Duarte, Javier, Li, Haoyang, Roy, Avik, Zhu, Ruike, Huerta, E. A., Diaz, Daniel, Harris, Philip, Kansal, Raghav, Katz, Daniel S., Kavoori, Ishaan H., Kindratenko, Volodymyr V., Mokhtar, Farouk, Neubauer, Mark S., Park, Sang Eon, Quinnan, Melissa, Rusack, Roger, Zhao, Zhizhen
Publikováno v:
Mach. Learn.: Sci. Technol. 4 (2023) 045062
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and ot
Externí odkaz:
http://arxiv.org/abs/2212.05081
Autor:
Roy, Avik, Neubauer, Mark S.
Multivariate techniques and machine learning models have found numerous applications in High Energy Physics (HEP) research over many years. In recent times, AI models based on deep neural networks are becoming increasingly popular for many of these a
Externí odkaz:
http://arxiv.org/abs/2211.12770
Extracting scientific results from high-energy collider data involves the comparison of data collected from the experiments with synthetic data produced from computationally-intensive simulations. Comparisons of experimental data and predictions from
Externí odkaz:
http://arxiv.org/abs/2211.11910