DOE OSTI · 3022291
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Abstract
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.
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Gonski, Julia [SLAC], Ott, Jenni, Abbaszadeh, Shiva [UC, Santa Cruz], Addepalli, Sagar [SLAC], Cremonesi, Matteo [Carnegie Mellon U.], Dickinson, Jennet [Cornell U., LNS], Di Guglielmo, Giuseppe [Fermilab; Northwestern U.], Ertorer, Erdem Yigit [Carnegie Mellon U.], Gray, Lindsey [Fermilab], Herbst, Ryan [SLAC], Herwig, Christian [Michigan U.], Hong, Tae Min [Pittsburgh U.], Maier, Benedikt [DESY; University Coll. London], Makou, Maryam Bayat [Southern Methodist U.], Miller, David [Illinois U., Chicago], Neubauer, Mark S. [Illinois U., Urbana (main)], Peña, Cristián [Fermilab], Rankin, Dylan [Pennsylvania U.], Seon-Hee, Seon-Hee, Seo, Seon-Hee [Fermilab], Stark, Giordon [UC, Santa Cruz], Tapper, Alexander [DESY; University Coll. London], Therrien, Audrey Corbeil [Sherbrooke U.], Xiotidis, Ioannis [CERN], Yoshihara, Keisuke [Hawaii U.], Abarajithan, G. [UC, San Diego], Akchurin, Nural [Texas Tech.], Argüelles, Carlos [Harvard U.], Bhattacharya, Saptaparna [Southern Methodist U.], Borella, Lorenzo [INFN, Padua], Boutan, Christian [PNL, Richland], Braine, Tom [PNL, Richland], Brau, James [Oregon U.], Breidenbach, Martin [SLAC], Chahine, Antonio [DESY; University Coll. London], Chowdhury, Talal Ahmed [Kansas U.], Chou, Yuan-Tang [Washington U., Seattle], Chung, Seokju [Unlisted], Coppi, Alberto [INFN, Padua], D'Alfonso, Mariarosaria [MIT, Cambridge, CTP], Dave, Abhilasha [SLAC], Desmet, Chance [PNL, Richland], Di Fulvio, Angela [Pisa U.], DiPetrillo, Karri [Illinois U., Chicago], Duarte, Javier [UC, San Diego], Edelen, Auralee [SLAC], Eysermans, Jan [MIT, Cambridge, CTP], Feng, Yongbin [Texas Tech.], Forrestel, Emmett [Brown U.], Garcia, Dolores [CERN], Gastaldo, Loredana [Heidelberg U.], García Pardiñas, Julián [MIT, Cambridge, CTP], Gerlach, Lino [KEK, Tsukuba], Gouskos, Loukas [Brown U.], Govorkova, Katya [MIT, Cambridge, CTP], Grace, Carl [UC, Berkeley], Grant, Christopher [Boston U.] (ORCID:0000000223281728), Harris, Philip [MIT, Cambridge, CTP], Hasnip, Ciaran [CERN], Heim, Timon [UC, Berkeley], Holtermann, Abraham [MIT, Cambridge, CTP], Innocenti, Gian Michele [MIT, Cambridge, CTP], Ishidoshiro, Koji [Tohoku U. (main)], Jin, Miaochen [Harvard U.], Johnson, Jyothisraj [UC, Berkeley], Jones, Stephen [PNL, Richland], Jung, Andreas [Purdue U.], Karagiorgi, Georgia [Unlisted], Kastner, Ryan [UC, San Diego], Kamp, Nicholas [Harvard U.], Kim, Doojin [South Dakota U.], Kong, Kyoungchul [Kansas U.], Kudela, Katie [MIT, Cambridge, CTP], Lalic, Jelena [MIT, Cambridge, CTP], Lai, Bo-Cheng [NYCU, Hsinchu], Lai, Yun-Tsung [KEK, Tsukuba], Lam, Tommy [Virginia Tech.] (ORCID:0000000191286806), Lazar, Jeffrey [Louvain U., CP3], Li, Aobo [UC, San Diego], Li, Zepeng [Hawaii U.], Liu, Haoyun [DESY; University Coll. London], Lončar, Vladimir [MIT, Cambridge, CTP], Macchiarulo, Luca [Hawaii U.], Madrid, Christopher [Texas Tech.], Ma, Zhenghua [UC, San Diego], Mukim, Prashansa [Brookhaven Natl. Lab.], Nguyen, Victoria [MIT, Cambridge, CTP], Oh, Sungbin [Fermilab], Ojalvo, Isobel [Princeton U.], Ozaki, Hideyoshi [Tokyo U. of Sci.], Griso, Simone Pagan [UC, Berkeley], Park, Myeonghun [Seoul Natl. U. (main)], Paus, Christoph [MIT, Cambridge, CTP], Parajuli, Santosh [Illinois U., Urbana (main)], Parpillon, Benjamin [Fermilab], Pozzi, Sara [Michigan U.], Puljak, Ema [CERN], Ramhorst, Benjamin [Zurich, ETH], Roberts, Amy [Denver U.], Ruckman, Larry [SLAC]. 2026-02-24. Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP). https://www.osti.gov/biblio/3022291
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