Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques

Babiano-Suarez, V. and Lerendegui-Marco, J. and Balibrea-Correa, J. and Caballero, L. and Calvo, D. and Ladarescu, I. and Real, D. and Domingo-Pardo, C. and Calvino, F. and Casanovas, A. and Tarifeno-Saldivia, A. and Alcayne, V. and Guerrero, C. and Millan-Callado, M. A. and Rodriguez-Gonzalez, T. and Barbagallo, M. and Aberle, O. and Amaducci, S. and Andrzejewski, J. and Audouin, L. and Bacak, M. and Bennett, S. and Berthoumieux, E. and Billowes, J. and Bosnar, D. and Brown, A. and Busso, M. and Caamano, M. and Calviani, M. and Cano-Ott, D. and Cerutti, F. and Chiaveri, E. and Colonna, N. and Cortes, G. and Cortes-Giraldo, M. A. and Cosentino, L. and Cristallo, S. and Damone, L. A. and Davies, P. J. and Diakaki, M. and Dietz, M. and Dressler, R. and Ducasse, Q. and Dupont, E. and Duran, I. and Eleme, Z. and Fernandez-Dominguez, B. and Ferrari, A. and Finocchiaro, P. and Furman, V. and Goebel, K. and Garg, R. and Gawlik, A. and Gilardoni, S. and Goncalves, I. F. and Gonzalez-Romero, E. and Gunsing, F. and Harada, H. and Heinitz, S. and Heyse, J. and Jenkins, D. G. and Junghans, A. and Kaeppeler, F. and Kadi, Y. and Kimura, A. and Knapova, I. and Kokkoris, M. and Kopatch, Y. and Krticka, M. and Kurtulgil, D. and Lederer-Woods, C. and Leeb, H. and Lonsdale, S. J. and Macina, D. and Manna, A. and Martinez, T. and Masi, A. and Massimi, C. and Mastinu, P. and Mastromarco, M. and Maugeri, E. A. and Mazzone, A. and Mendoza, E. and Mengoni, A. and Michalopoulou, V. and Milazzo, P. M. and Mingrone, F. and Moreno-Soto, J. and Musumarra, A. and Negret, A. and Ogallar, F. and Oprea, A. and Patronis, N. and Pavlik, A. and Perkowski, J. and Persanti, L. and Petrone, C. and Pirovano, E. and Porras, I. and Praena, J. and Quesada, J. M. and Ramos-Doval, D. and Rauscher, T. and Reifarth, R. and Rochman, D. and Rubbia, C. and Sabate-Gilarte, M. and Saxena, A. and Schillebeeckx, P. and Schumann, D. and Sekhar, A. and Smith, A. G. and Sosnin, N. and Sprung, P. and Stamatopoulos, A. and Tagliente, G. and Tain, J. L. and Tassan-Got, L. and Thomas, Th and Torres-Sanchez, P. and Tsinganis, A. and Ulrich, J. and Urlass, S. and Valenta, S. and Vannini, G. and Variale, V. and Vaz, P. and Ventura, A. and Vescovi, D. and Vlachoudis, V. and Vlastou, R. and Wallner, A. and Woods, P. J. and Wright, T. and Zugec, P.. (2021) Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques. European Physical Journal A: Hadrons and Nuclei , 57 (6). p. 197.

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Official URL: https://edoc.unibas.ch/84210/

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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 197Au(n,γ) and 56Fe(n,γ) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C6D6 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 C6D6 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.
Faculties and Departments:05 Faculty of Science > Departement Physik > Former Organization Units Physics > Theoretische Physik Astrophysik (Thielemann)
UniBasel Contributors:Rauscher, Thomas
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:EDP Sciences with Springer and Società Italiana di Fisica
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:09 Aug 2021 15:07
Deposited On:09 Aug 2021 15:07

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