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Applications of non-negative iterative deconvolution method in the analysis of alpha-particle spectra

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Abstract

Different from the regular method with peak-shape function fitting, in this work, the idea of alpha-spectra analysis using non-negative iterative deconvolution method is proposed. Two non-negative iterative algorithms, the Boosted Gold and the Boosted Richardson–Lucy, were applied to unfold and analyze alpha-particle spectra. The detector response matrix was constructed with the AASI, which is a Monte Carlo simulation software specifically for alpha-particle spectra. A \(^{244}\)Cm alpha-particle source was measured and tested for peak-position deconvolution. A \(^{238+239+240}\)Pu alpha-particle spectrum was used to prove the validity of quantitative analysis by deconvolution algorithms. Both the Boosted Gold and the Boosted Richardson–Lucy can get accurate results for peak positions and content ratios. In terms of running speed, the Boosted Gold was faster than the Boosted Richardson–Lucy.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 41874213, 41604154, and U19A2086) and the Opening Project of Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things (Grant No. 2019WZJ01). The authors would like to thank Dr. Hurtado Santiago (Servicio de Radioisotopos, CITIUS, Universidad de Sevilla, Spain) for providing the EUROMET-5535 reference spectrum.

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Correspondence to Xianguo Tuo.

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Shi, R., Tuo, X., Cheng, Y. et al. Applications of non-negative iterative deconvolution method in the analysis of alpha-particle spectra. Eur. Phys. J. Plus 135, 225 (2020). https://doi.org/10.1140/epjp/s13360-020-00100-9

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  • DOI: https://doi.org/10.1140/epjp/s13360-020-00100-9

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