Abstract
Atmospheric traces of radioactive xenon, in particular \(^{131m}{\text {Xe}}\), \(^{133}{\text {Xe}}\), \(^{133m}{\text {Xe}}\) and \(^{135}{\text {Xe}}\), can provide “smoking gun” evidence to classify underground nuclear fission reactions. Current software used to quantify isomer concentrations relies on a Region of Interest (ROI) method to sort beta-gamma coincidence counts. This experiences errors when classifying nuclides, especially with metastable nuclides, due to the difficulty of deconvoluting overlapping ROIs and accounting for shifts in detector calibration over time. To address this uncertainty, our technique mathematically models the distinctive peaks in an isomer’s beta-gamma spectrum. The function representations are then fitted to measured spectra to determine the concentrations of the primary isomers in the sample. From this proof-of-concept, we hope to create a more precise and accurate system to detect nuclear fission reactions.
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Notes
We use natural units wherein energy, mass, and momentum all have units of energy.
For Gaussian functions the normalization coefficient is the usual \(N=\frac{1}{\sigma \sqrt{2 \pi }}\). For the beta distributions the functional form is more complicated but can be determined by integration.
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Acknowledgements
We thank members of the Air Force Technical Applications Center, and particularly the 21st Surveillance Squadron to include David Straughn, for providing the experimental data used in this study. We also thank members of the Pacific Northwest National Laboratory for their extensive help and encouragement in this study. In particular, we thank Matthew Cooper and Michael Mayer for their many very thoughtful discussions concerning radioxenon, the beta-gamma detectors used to measure the isomers of interest, and the algorithms used to analyze the detector data. We also thank Justin McIntyre for his help in obtaining the extensive simulated data set used in this study. This work would not have been possible without their efforts; these individuals are true experts in their field and we very much hope to work more extensively with them in the future.
Funding
This study was funded by the Air Force Technical Applications Center.
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Sesler, J., Scoville, J., Carpency, T. et al. 2D peak fitting for the analysis of radioxenon beta gamma spectra. J Radioanal Nucl Chem 327, 445–456 (2021). https://doi.org/10.1007/s10967-020-07518-6
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DOI: https://doi.org/10.1007/s10967-020-07518-6