Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques
i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (\(n,\gamma\)) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolut...
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Veröffentlicht in: | arXiv.org 2020-12 |
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Sprache: | eng |
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Zusammenfassung: | i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (\(n,\gamma\)) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolution time-of-flight experiments and demonstrates for the first time the concept proposed for background rejection. To this aim both \(^{197}\)Au(\(n,\gamma\)) and \(^{56}\)Fe(\(n, \gamma\)) reactions were measured at CERN n\_TOF using an i-TED demonstrator based on only three position-sensitive detectors. Two \cds detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of \(\sim\)3 higher detection sensitivity than state-of-the-art \cds detectors in the \(\sim\)10~keV neutron energy range of astrophysical interest. This paper explores also the perspectives of further enhancement in performance attainable with the final i-TED array consisting of twenty position-sensitive detectors and new analysis methodologies based on Machine-Learning techniques. |
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ISSN: | 2331-8422 |
DOI: | 10.48550/arxiv.2012.10374 |