activity
20182026
most citedMachine Learning in High Energy Physics Community White Paper

30 citations · 33 across the 5 of their papers we have counts for

collaborators

5 papers

physics.acc-ph2026

AI-Ready Control System for the Fermilab Accelerator Complex

Tia Miceli, Erik Gottschalk, Donovan Tooke +15

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. W…

physics.acc-ph2025

Twinac: A Universal Framework for Virtual Accelerator Controls

Tia Miceli, Abhishek Pathak, Aaron Sauers

We propose a universal framework for a system of virtual accelerator controls (Twinac), a standard toolkit for research institutions to design, maintain, and use a real-time, end-t…

physics.soc-ph2022

Programs Enabling Deep Technology Transfer from National Labs

asou Arai, Farah Fahim, Ryosuke Furubayashi +6

To maximize the technology transfer potential, it is important to create an ecosystem for the inventors to adapt the technologies developed for basic science to successful commerci…

physics.acc-ph2021★ 3 cited

Design of a medium energy, high average power superconducting e-beam accelerator for environmental applications

R. C. Dhuley, I. Gonin, K. Zeller +10

We present the technical and engineering design of a medium energy (10 MeV) and high average power (1 MW) electron beam accelerator intended for irradiation treatment of high volum…

physics.comp-ph2018★ 30 cited

Machine Learning in High Energy Physics Community White Paper

Kim Albertsson, Piero Altoe, Dustin Anderson +125

Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by a…