Quantitative mobile gamma-ray spectrometry through Bayesian inference (Dataset)

## Description This dataset contains experimental and numerical gamma-ray spectroscopy data used in the study: Title: Quantitative mobile gamma-ray spectrometry through Bayesian inference Authors: David Breitenmoser [1,2], Alberto Stabilini [1], Malgorzata Magdalena Kasprzak [1], Sabine Mayer [1] Affiliations: [1] Paul Scherrer Institute (PSI), Department of Radiation Safety and Security, Villigen PSI, Switzerland [2] University of Michigan, Department of Nuclear Engineering and Radiological Sciences, Ann Arbor, USA Journal: arXiv DOI: 10.48550/arXiv.2512.18769 ## Structure data_v1_1_0.zip/ Each subfolder corresponds to one measurement case:<Mode>_<Sources> * HF = hover-flight mode * SP = single-pass mode Each case contains:* Data/ - measured spectra * Templates/ - simulated spectral templates for radionuclide sources {Cs: Cs-137, Ba: Ba-133, K: K-nat, Th: Th-nat, U: U-nat, Rn: Rn-nat} ## Measurement Types * HF (hover-flight): * background.csv - background spectra * gross_<t>.csv - gross spectra with source, where acquisition time t in {1s, 5s, all} * SP (single-pass): * background.csv - background spectra * gross.csv - gross spectra with source(s) (1 s acquisitions) ## Data Format All files are CSV with columns:* Energy_keV - energy bin centers (keV) * Counts<unit> - counts (scaled in <unit>) Header (first line in Data/ files):* # live_time_s = <value> - measurement live time in seconds (per counts column) ## Versions * v1.1.0 - Added single-pass data and spectral templates (2026-05-05) * v1.0.0 - Initial release (2025-12-20) ## Citation Please cite both the dataset and the associated publication: [1] D. Breitenmoser, A. Stabilini, M. M. Kasprzak, S. Mayer, "Quantitative mobile gamma-ray spectrometry through Bayesian inference (Dataset)," Zenodo, 2025. doi: 10.5281/zenodo.18004441 [2] D. Breitenmoser, A. Stabilini, M. M. Kasprzak, S. Mayer, "Quantitative mobile gamma-ray spectrometry through Bayesian inference," arXiv:2512.18769, 2025. doi: 10.48550/arXiv.2512.18769