Title: | Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques |
Authors: | Babiano-Suárez, V. Lerendegui-Marco, J. Balibrea-Correa, J. Caballero, L. Calvo, D. Ladarescu, I. Real, D. Domingo-Pardo, C. Calviño, F. Casanovas, A. Tarifeño-Saldivia, A. Knapova, I. Kokkoris, M. Kopatch, Y. Krtička, M. Kurtulgil, D. Lederer-Woods, C. Leeb, H. Lonsdale, S. J. Macina, D. Manna, A. Quesada, J. M. Martinez, T. Masi, A. Massimi, C. Mastinu, P. Mastromarco, M. Maugeri, E. A. Mazzone, A. Mendoza, E. Mengoni, A. Michalopoulou, V. Ramos-Doval, D. Milazzo, P. M. Mingrone, F. Moreno-Soto, J. Musumarra, A. Negret, A. Ogállar, F. Oprea, A. Patronis, N. Pavlik, A. Perkowski, J. Rauscher, T. Persanti, L. Petrone, C. Pirovano, E. Porras, I. Praena, J. Reifarth, R. Rochman, D. Rubbia, C. Sabaté-Gilarte, M. SAXENA, AAYUSH Schillebeeckx, P. Schumann, D. Alcayne, V. 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. Guerrero, C. Tsinganis, A. Ulrich, J. Urlass, S. Valenta, S. Vannini, G. Variale, V. Vaz, P. Ventura, A. VESCOVI, Diego Vlachoudis, V. Millán-Callado, M. A. Vlastou, R. Wallner, A. Woods, P. J. Wright, T. Žugec, P. Rodríguez-González, T. 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, Sergio Damone, L. A. Davies, P. J. Diakaki, M. Dietz, M. Dressler, R. Ducasse, Q. Dupont, E. Durán, I. Eleme, Z. Fernández-Domínguez, B. 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. |
Issue Date: | 2021 |
Journal: | THE EUROPEAN PHYSICAL JOURNAL. A, HADRONS AND NUCLEI |
Number: | 57 |
Issue: | 6 |
First Page: | 197 |
Abstract: | i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (n ,γ ) 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, the 19<SUP>7</SUP>Au(n ,γ ) and 5<SUP>6</SUP>Fe(n ,γ ) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C<SUB>6</SUB>D<SUB>6</SUB> detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of ∼3 higher detection sensitivity than state-of-the-art C<SUB>6</SUB>D<SUB>6</SUB> detectors in the 10 keV neutron-energy region 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. |
URI: | http://hdl.handle.net/20.500.12386/31550 |
URL: | https://link.springer.com/article/10.1140/epja/s10050-021-00507-7 https://api.elsevier.com/content/abstract/scopus_id/85103664089 |
ISSN: | 1434-6001 |
DOI: | 10.1140/epja/s10050-021-00507-7 |
Bibcode ADS: | 2021EPJA...57..197B |
Fulltext: | open |
Appears in Collections: | 1.01 Articoli in rivista
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