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Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques
The European Physical Journal A ( IF 2.7 ) Pub Date : 2021-06-17 , DOI: 10.1140/epja/s10050-021-00507-7
V. Babiano-Suárez , J. Lerendegui-Marco , J. Balibrea-Correa , L. Caballero , D. Calvo , I. Ladarescu , D. Real , C. Domingo-Pardo , F. Calviño , A. Casanovas , A. Tarifeño-Saldivia , V. Alcayne , C. Guerrero , M. A. Millán-Callado , 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. Fernández-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

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, the \(^{197}\)Au(\(n,\gamma \)) and \(^{56}\)Fe(\(n, \gamma \)) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C\(_6\)D\(_6\) 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 C\(_6\)D\(_6\) 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.



中文翻译:

成像中子捕获横截面:基于机器学习技术的 i-TED 概念验证和未来前景

i-TED 是一种创新的检测系统,它利用康普顿成像技术,使用飞行时间技术在 ( \(n,\gamma\) ) 横截面测量中实现卓越的信背景比。这项工作首次对 i-TED 设备进行高分辨率飞行时间实验进行了实验验证,并首次展示了提出的背景抑制概念。为此,在 CERN n_TOF 研究了\(^{197}\) Au( \(n,\gamma \) ) 和\(^{56}\) Fe( \(n, \gamma \) ) 反应使用基于三个位置敏感探测器的 i-TED 演示器。两个 C \(_6\) D \(_6\)检测器也被用来对 i-TED 的性能进行基准测试。第i-TED原型用于该研究显示了内置的因子\(\ SIM \) 3更高的检测比状态的最技术的C灵敏度\(_ 6 \) d \(_ 6 \)在检测器的10千电子伏中子天体物理学感兴趣的能量区域。本文还探讨了通过由 20 个位置敏感探测器和基于机器学习技术的新分析方法组成的最终 i-TED 阵列进一步提高性能的前景。

更新日期:2021-06-18
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