Speaker
Description
Large-scale neutrino observatories operate under unavoidable detector deadtime and signal pile-up, leading to systematic inefficiencies in conventional coincidence-based trigger systems. Such triggers typically rely on binary temporal windows and implicitly assume continuous sensor availability, causing correlated event signatures to fragment during non-live intervals. We introduce Recursive Manifold Coherence (RMC), a geometric and state-space framework that reformulates distributed trigger logic as continuous coherence estimation under intermittent observation. The framework represents detector response using compact charge-timing features and propagates a low-dimensional coherence state through a recursive update law.
Instead of treating deadtime as a hard logical zero or veto, RMC treats non-live intervals as missing observations with controlled uncertainty growth. When validated observations are available, the coherence state is reinforced by incoming charge-timing evidence; when observations are unavailable, the state decays smoothly rather than resetting. This enables partially obscured correlated structure to be retained and evaluated even when direct coincidence chains are temporarily broken.
Using simulation studies representative of large optical detector arrays, we show that RMC preserves event-level coherence more robustly than standard binary coincidence logic under increasing deadtime probability. The framework remains stable across a practical range of persistence parameters and is compatible with software-defined trigger pipelines operating on compact feature streams. These results suggest that recursive coherence estimation provides a detector-agnostic foundation for deadtime-aware trigger strategies in future distributed detector systems.