Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing

Emulator-based Bayesian inference on non-proportional scintillation models by compton-edge probing

Blog Article

Abstract Scintillator detector response modeling has become an essential tool in various research fields such as particle and nuclear physics, astronomy or geophysics.Yet, due to the system complexity and the requirement for accurate electron response wella color touch 77 45 measurements, model inference and calibration remains a challenge.Here, we propose Compton edge probing to perform non-proportional scintillation model (NPSM) inference for inorganic scintillators.

We use laboratory-based gamma-ray radiation measurements with a NaI(Tl) scintillator to perform Bayesian inference on a NPSM.Further, we apply machine learning to emulate the detector response obtained by Monte Carlo simulations.We show that the proposed methodology successfully constrains the NPSM and hereby quantifies the intrinsic resolution.

Moreover, using the trained emulators, we can predict the orange zinger tomato spectral Compton edge dynamics as a function of the parameterized scintillation mechanisms.The presented framework offers a simple way to infer NPSMs for any inorganic scintillator without the need for additional electron response measurements.