Information–Energetic Limits of Irreversible Decisions in Particle Accelerators

Particle accelerators represent extreme physical systems in which energy flow, information flow, and irreversibility intersect within operational decisions performed over finite time intervals. Beyond beam acceleration itself, critical components of accelerator infrastructure include mea- surement and data selection processes (including real-time event triggering), beam stabilization, and detector control, all of which inherently involve dissipation, noise, and irreversible loss of information. This preprint formulates a conservative description of such processes within Information–Energetic Thermodynamics (IET) as a working physical formalism, enabling a unified representation of the relationship between energetic budget, acquired information, de- cision timescale, and irreversibility. We show that certain practically observed operational limits (e.g. real-time stability and event selection constraints) can be naturally interpreted as information–energetic boundaries of the system rather than as isolated technical limitations of individual subsystems. The resulting framework provides a basis for measurable analysis and optimization of decision-making processes in particle accelerators and related systems of extreme physical metrology.