학술논문
Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques
Document Type
Working Paper
Author
Babiano-Suárez, V.; Lerendegui-Marco, J.; Balibrea-Correa, J.; Caballero, L.; Calvo, D.; Ladarescu, I.; Domingo-Pardo, C.; Calviño, F.; Casanovas, A.; Tarifeño-Saldivia, A.; Alcayne, V.; Guerrero, C.; Millán-Callado, M. A.; González, M. T. Rodríguez; Barbagallo, M.; Aberle, O.; Amaducci, S.; Andrzejewski, J.; Audouin, L.; Bacak, M.; Bennett, S.; Berthoumieux, E.; Billowes, J.; Bosnar, D.; Brown, A.; Busso, M.; Caamaño, M.; Calviani, M.; Cano-Ott, D.; Cerutti, F.; Chiaveri, E.; Colonna, N.; Cortés, G.; Cortés-Giraldo, M. A.; Cosentino, L.; Cristallo, S.; Damone, L. A.; Davies, P. J.; Diakaki, M.; Dietz, M.; Dressler, R.; Ducasse, Q.; Dupont, E.; Durán, I.; Eleme, Z.; Fern\', B.; ez-Domínguez; Ferrari, A.; Finocchiaro, P.; Furman, V.; Göbel, K.; Garg, R.; Gawlik, A.; Gilardoni, S.; Gonçalves, I. F.; González-Romero, E.; Gunsing, F.; Harada, H.; Heinitz, S.; Heyse, J.; Jenkins, D. G.; Junghans, A.; Käppeler, F.; Kadi, Y.; Kimura, A.; Knapova, I.; Kokkoris, M.; Kopatch, Y.; Krtička, M.; Kurtulgil, D.; Lederer-Woods, C.; Leeb, H.; Lonsdale, S. J.; Macina, D.; Manna, A.; Martinez, T.; Masi, A.; Massimi, C.; Mastinu, P.; Mastromarco, M.; Maugeri, E. A.; Mazzone, A.; Mendoza, E.; Mengoni, A.; Michalopoulou, V.; Milazzo, P. M.; Mingrone, F.; Moreno-Soto, J.; Musumarra, A.; Negret, A.; Ogállar, F.; Oprea, A.; Patronis, N.; Pavlik, A.; Perkowski, J.; Persanti, L.; Petrone, C.; Pirovano, E.; Porras, I.; Praena, J.; Quesada, J. M.; Ramos-Doval, D.; Rauscher, T.; Reifarth, R.; Rochman, D.; Rubbia, C.; Sabaté-Gilarte, M.; Saxena, A.; Schillebeeckx, P.; Schumann, D.; Sekhar, A.; Smith, A. G.; Sosnin, N. V.; Sprung, P.; Stamatopoulos, A.; Tagliente, G.; Tain, J. L.; Tassan-Got, L.; Thomas, Th.; Torres-Sánchez, P.; Tsinganis, A.; Ulrich, J.; Urlass, S.; Valenta, S.; Vannini, G.; Variale, V.; Vaz, P.; Ventura, A.; Vescovi, D.; Vlachoudis, V.; Vlastou, R.; Wallner, A.; Woods, P. J.; Wright, T.; Žugec, P.
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Subject
Language
Abstract
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.
Comment: 16 pages, 16 figures
Comment: 16 pages, 16 figures