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arXiv 2012.10374physics.ins-detastro-ph.IMnucl-ex
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中子俘获截面成像:i-TED概念验证及基于机器学习技术的未来前景

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

V. Babiano-Suárez, J. Lerendegui-Marco, J. Balibrea-Correa, L. Caballero, D. Calvo, I. Ladarescu, C. Domingo-Pardo, F. Calviño, A. Casanovas, A. Tarifeño-Saldiv… 展开作者

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

AI总结:

本研究验证了i-TED探测系统利用康普顿成像技术在飞行时间中子俘获截面测量中实现卓越背景剔除的能力,其原型机在10 keV能区灵敏度较Cds探测器高约3倍,并展望了基于机器学习的性能提升前景。

摘要:

i-TED是一种创新的探测系统,它利用康普顿成像技术,在使用飞行时间技术进行的($n,γ$)截面测量中实现卓越的信噪比。本研究首次对i-TED装置进行了高分辨率飞行时间实验的实验验证,并首次展示了所提出的背景剔除概念。为此,在CERN n_TOF上使用仅基于三个位置灵敏探测器的i-TED演示器,测量了$^{197}$Au($n,γ$)和$^{56}$Fe($n, γ$)反应。还使用了两个\cds探测器来基准测试i-TED的性能。为本研究构建的i-TED原型机在具有天体物理学意义的$\sim$10 keV中子能区,显示出比最先进的\cds探测器高约3倍的探测灵敏度。本文还探讨了通过由二十个位置灵敏探测器组成的最终i-TED阵列以及基于机器学习技术的新分析方法可实现的性能进一步提升前景。

英文摘要:

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 both $^{197}$Au($n,γ$) and $^{56}$Fe($n, γ$) 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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