4 papers
Toward a Fully Autonomous, AI-Native Particle Accelerator
Chris Tennant
This position paper presents a vision for self-driving particle accelerators that operate autonomously with minimal human intervention. We propose that future facilities be designe…
From Natural Language to Control Signals: A Conceptual Framework for Semantic Channel Finding in Complex Experimental Infrastructure
Thorsten Hellert, Nikolay Agladze, Alex Giovannone +5
Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and…
A Core Ontology for Particle Accelerators: Interoperable Data and Workflows Across Facilities
Chris Tennant
We propose a small, shared core ontology for particle accelerators that provides a semantic backbone for interoperable data and workflows across facilities. The ontology names key…
eLog analysis for accelerators: status and future outlook
Antonin Sulc, Thorsten Hellert, Aaron Reed +11
This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, La…