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Scintillator detector response modelling has become an essential tool invarious research fields such as particle and nuclear physics, astronomy orgeophysics. Yet, due to the system complexity and the requirement for accurateelectron response measurements, model inference and calibration remains achallenge. Here, we propose Compton edge probing to perform non-proportionalscintillation model (NPSM) inference for inorganic scintillators. We uselaboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillatorto perform Bayesian inference on a NPSM. Further, we apply machine learning toemulate the detector response obtained by Monte Carlo simulations. We show thatthe proposed methodology successfully constrains the NPSM and hereby quantifiesthe intrinsic resolution. Moreover, using the trained emulators, we can predictthe spectral Compton edge dynamics as a function of the parameterizedscintillation mechanisms. The presented framework offers a novel way to inferNPSMs for any inorganic scintillator without the need for additional electronresponse measurements.

Emulator-based Bayesian Inference on Non-Proportional Scintillation Models by Compton-Edge Probing