Speaker
Description
Recent advances in Artificial Intelligence (AI) have accelerated the development of high-performance Large Language Models (LLMs), with leading global companies releasing new generations every few months. Since the introduction of Gemini 3 Pro, AI systems have progressed beyond the hallucination-dominated stage and are approaching human-level reasoning performance. This rapid evolution is reshaping the scientific research landscape, enabling tasks that previously required large, specialized teams to be carried out by a single expert working in collaboration with an intelligent AI scientist. In accelerator science, Agentic AI and Physical AI are increasingly being applied to accelerator design, diagnostics, autonomous operation, fault detection, and predictive maintenance. In this paper, we describe an Agentic AI for Start-to-End (S2E) simulations using the ASTRA and ELEGANT codes to estimate error tolerances from an injector linac to a storage ring for a Multi-Bend Achromat (MBA)–based fourth-generation synchrotron light source.
| In which format do you inted to submit your paper? | LaTeX |
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