arXiv subjects

Alberto Stabilini

Publications and source records attributed to Alberto Stabilini.

3 recordsLinked to original sources

arXiv2025

Quantitative mobile gamma-ray spectrometry through Bayesian inference

Accurate quantitative mapping of gamma-ray emitters is critical for applications ranging from radiological emergency response and environmental monitoring to nuclear security and deep space exploration. Here, we show that such mapping can be achieved by combining mobile gamma-ray spectrometry with high-fidelity Monte Carlo simulations and full-spectrum Bayesian inference. Using 6 s of single-pass mobile spectrometry data benchmarked against independent in-situ and laboratory assays, we demonstrate decisive source mixture identification ($>\!\!5\sigma$), meter-scale source localization, and recovery of source activities with percent-level accuracy. The developed method marks a critical advance in quantitative gamma-ray sensing, enabling improved radiological situational awareness, enhanced terrestrial geophysical and geochemical mapping, as well as more robust constraints on radionuclide abundances on extraterrestrial bodies across the Solar System.

physics.ins-det↗

arXiv2025

Full-spectrum modeling of mobile gamma-ray spectrometry systems in scattering media

Mobile gamma-ray spectrometry (MGRS) systems are essential for localizing, identifying, and quantifying gamma-ray sources in complex environments. Full-spectrum template matching offers the highest accuracy and sensitivity for these tasks but is limited by the computational cost of generating the required spectral templates. Here, we present a generalized full-spectrum modeling framework for MGRS systems in scattering media, enabling near-real-time template generation through dynamic, anisotropic instrument response functions. Benchmarked against high-fidelity brute-force Monte Carlo simulations, our method yields a computational speedup by a factor of $\mathcal{O}(10^7)$, while achieving comparable accuracy with median spectral deviations below 6%. The methodology presented is platform-agnostic and applicable across marine, terrestrial, and airborne domains, unlocking new capabilities for MGRS in a variety of applications, such as environmental monitoring, geophysical exploration, nuclear safeguards, and radiological emergency response.

physics.ins-det↗

arXiv2025

Development and validation of a high-fidelity full-spectrum Monte Carlo model for the Swiss airborne gamma-ray spectrometry system

Airborne Gamma-Ray Spectrometry (AGRS) is a critical tool for radiological emergency response, enabling the rapid identification and quantification of hazardous terrestrial radionuclides over large areas. However, existing calibration methods are limited to a few gamma-ray sources, excluding most radionuclides released in severe nuclear accidents and nuclear weapon detonations, compromising effective response and risk assessment. Here, we present a high-fidelity Monte Carlo model that overcomes these limitations, offering full-spectrum calibration for any gamma-ray source. Unlike previous approaches, our model integrates a detailed mass model of the aircraft and a calibrated non-proportional scintillation model, enabling accurate event-by-event predictions of the spectrometer's response to arbitrarily complex gamma-ray fields. Validation in near-, mid-, and far-field scenarios demonstrates that the model not only addresses major deficiencies of previous approaches but also achieves the accuracy required to supersede empirical calibration methods. This advancement enables high-fidelity spectral signature generation for any gamma-ray source, reduces calibration time and costs, minimizes reliance on high-intensity sources, and eliminates related radioactive waste. The approach presented here is a critical step toward integrating advanced full-spectrum data reduction methods for AGRS, unlocking new capabilities beyond emergency response, such as atmospheric cosmic-ray flux quantification for geophysics and trace-level airborne radionuclide identification for nuclear security.

physics.ins-det↗