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

Autori
Babiano-Suárez, V. ; ... ; Bosnar, Damir ; ... ; Žugec, Petar

Kolaboracija
N_TOF Collaboration

Izvornik
European physical journal A : hadrons and nuclei (1434-6001) 57 (2021); 197, 17

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
i-TED, neutron capture, n_TOF, machine learning

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Fizika

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