Speaker
Description
Large-scale neutrino observatories operate under unavoidable detector deadtime arising from photomultiplier saturation, digitizer limits, and front-end readout constraints. Conventional coincidence-based trigger logic implicitly assumes continuous sensor availability and therefore suffers systematic efficiency loss when channels become temporarily non-live. This work presents a liveness-aware trigger architecture for distributed optical arrays, targeting low-latency FPGA-compatible implementation. The proposed method introduces a recursive Infinite Impulse Response (IIR) update law that constructs a continuity-preserving effective observable at each sensor node. Rather than collapsing during non-liveness intervals, the observable decays smoothly, preserving trigger-relevant temporal and amplitude information for network-level coherence estimation. By explicitly separating continuous measurement construction from discrete trigger decision logic, the architecture enables graceful degradation under partial channel non-liveness.
Performance is evaluated using a hybrid validation framework that combines event topologies derived from IceCube Open Data with a hardware-informed parametric signal and readout model incorporating PMT response, saturation, digitizer limits, and controlled deadtime injection. Simulation results show that the proposed trigger sustains above 90% event recovery efficiency at 20% deadtime probability, while conventional coincidence logic degrades below 40% under the same conditions. The continuity-preserving observable also improves effective Signal-to-Noise Ratio (SNR) by up to approximately two orders of magnitude in stressed deadtime regimes, indicating improved robustness under saturation and intermittent channel availability. These results suggest that liveness-aware recursive triggering provides a practical foundation for next-generation firmware-level trigger strategies in distributed optical detector arrays.