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