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Boosting background suppression in the NEXT experiment through Richardson-Lucy deconvolution
Journal of High Energy Physics ( IF 5.4 ) Pub Date : 2021-07-21 , DOI: 10.1007/jhep07(2021)146
J. Hauptman 1 , A. A. Denisenko 2 , F. Foss 2 , C. Newhouse 2 , P. Thapa 2 , T. T. Vuong 2 , N. Byrnes 3 , B. J. P. Jones 3 , A. Laing 3 , A. D. McDonald 3 , D. R. Nygren 3 , L. Rogers 3 , K. Woodruff 3 , C. D. R Azevedo 4 , A. L. Ferreira 4 , J. F. C. A. Veloso 4 , P. Lebrun 5 , A. Para 5 , A. Simón 6 , Y. Ifergan 6, 7 , A. B. Redwine 6 , R. Weiss-Babai 6 , L. Arazi 6 , R. Felkai 6, 8 , G. Martínez-Lema 6 , A. Goldschmidt 9 , F. P. Cossío 10, 11 , P. Ferrario 10, 12 , Z. Freixa 10, 13 , J. J. Gómez-Cadenas 10, 12 , F. Monrabal 10, 12 , I. Rivilla 10, 12 , R. M. Gutiérrez 14 , M. Losada 14 , Y. Rodríguez García 14 , T. Contreras 15 , S. Gosh 15 , R. Guenette 15 , J. Haefner 15 , J. Ho 15 , J. Martín-Albo 8, 15 , C. Stanford 15 , J. Pérez 16 , B. Romeo 12, 16 , L. M. P. Fernandes 17 , E. D. C. Freitas 17 , C. A. O. Henriques 17 , R. D. P. Mano 17 , C. M. B. Monteiro 17 , J. M. F. dos Santos 17 , J. M. R. Teixeira 17 , F. I. G. M. Borges 18 , C. A. N. Conde 18 , J. Escada 18 , F. P. Santos 18 , R. Webb 19 , J. T. White 19 , P. Herrero 12, 20 , C. Rogero 20 , H. Almazán 12 , J. M. Benlloch-Rodríguez 12 , J. Generowicz 12 , R. González 12 , M. Martínez-Vara 8, 12 , E. Oblak 12 , M. Odriozola-Gimeno 12 , J. Torrent 12 , B. Aparicio 11 , A. I. Aranburu 11 , L. Ripoll 21 , C. Adams 22 , K. Bailey 22 , K. Hafidi 22 , Z.-E. Meziani 22 , L. Labarga 23 , S. Cárcel 8 , J. V. Carrión 8 , J. Díaz 8 , N. López-March 8 , A. Martínez 8 , J. Muñoz Vidal 8 , P. Novella 8 , B. Palmeiro 8, 24 , M. Querol 8 , J. Renner 8 , C. Romo-Luque 8 , M. Sorel 8 , A. Usón 8 , N. Yahlali 8 , I. J. Arnquist 25 , E. Church 25 , G. Díaz 24 , D. González-Díaz 24 , J. A. Hernando Morata 24 , M. Kekic 24 , V. Álvarez 26 , F. Ballester 26 , R. Esteve 26 , V. Herrero 26 , F. J. Mora 26 , J. Rodríguez 26 , J. F. Toledo 26 , S. Cebrián 27
Affiliation  

Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of ∼ 1027 yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of ∼ 5 when reconstructing electron-positron pairs in the 208Tl 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterráneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of ∼ 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV ee+ pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.

A preprint version of the article is available at ArXiv.


中文翻译:

通过 Richardson-Lucy 反卷积增强 NEXT 实验中的背景抑制

下一代无中微子双 β 衰变实验的目标是将半衰期灵敏度提高到 10 27年,需要将背景抑制到<1 个/吨/年。为此,除了出色的能量分辨率和使用极其辐射纯的材料之外,任何额外的背景抑制处理都至关重要。NEXT 实验利用双 β 衰变和单电子事件的空间电离模式的差异来区分信号与背景。前者在轨道的两端显示两个布拉格峰密集电离区域,而后者通常只有一个这样的特征。因此,比较轨道极值处的能量提供了额外的拒绝工具。基于拓扑的背景识别和出色的能量分辨率(衰减 Q 值处为 1% FWHM)的独特组合是 NEXT 的显着特征。208 Tl 1.6 MeV 双逃逸峰(以康普顿事件为背景),记录在 Labatorio Subterraneo de Canfranc 的 NEXT-White 演示器中,信号效率为 72%。最近通过使用深度卷积神经网络对此进行了改进,以产生 ~ 10 的背景抑制因子和 65% 的信号效率。在这里,我们提出了一种基于 Richardson-Lucy 反卷积算法的新重建方法,该方法可以逆转 NEXT TPC 中由电子扩散和电致发光产生的模糊。新方法产生了重建事件的高度精细的 3D 图像,因此,显着改善了拓扑背景区分。应用于真实数据时 1.6 MeV e e + 对,它在 57% 的信号效率下导致 27 的背景抑制因子。

该文章的预印版可在 ArXiv 上获得。
更新日期:2021-07-22
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