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Title: Simulation of charge readout with segmented tiles in nEXO

Journal Article · · Journal of Instrumentation
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nEXO is a proposed experiment to search for the neutrino-less double beta decay (0νββ) of 136Xe in a tonne-scale liquid xenon time projection chamber (TPC). The nEXO TPC will be equipped with charge collection tiles to form the anode. In this work, the charge reconstruction performance of this anode design is studied with a dedicated simulation package. A multi-variate method and a deep neural network are developed to distinguish simulated 0νββ signals from backgrounds arising from trace levels of natural radioactivity in the detector materials. These simulations indicate that the nEXO TPC with charge-collection tiles shows promising capability to discriminate the 0νββ signal from backgrounds. Furthermore, the estimated half-life sensitivity for 0νββ decay is improved by 20 32)% with the multi-variate (deep neural network) methods considered here, e sensitivity estimated in the nEXO pre-conceptual design report.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Leland Stanford Junior Univ., Redwood City, CA (United States); Univ. of Alabama, Tuscaloosa, AL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP); National Science Foundation (NSF); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Nuclear Physics (NP); Natural Sciences and Engineering Research Council of Canada (NSERC); Canada Foundation for Innovation (CFI); Fonds de recherche du Québec – Nature et technologies (FRQNT); National Research Council Canada (NRC); McDonald Institute; Institute for Basic Science (IBS); Russian Foundation for Basic Research (RFBR); Chinese Academy of Sciences (CAS); National Natural Science Foundation of China (NSFC); USDOE Laboratory Directed Research and Development (LDRD) Program
Contributing Organization:
The nEXO collaboration; nEXO Collaboration
Grant/Contract Number:
SC0012704; AC52-07NA27344; SC0017970; FG02-01ER41166
OSTI ID:
1580230
Alternate ID(s):
OSTI ID: 1658689; OSTI ID: 1660461; OSTI ID: 1831057
Report Number(s):
BNL-212465-2019-JAAM; LLNL-JRNL-788038; BNL-211967-2019-JAAM; TRN: US2102199
Journal Information:
Journal of Instrumentation, Vol. 14, Issue 09; ISSN 1748-0221
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 6 works
Citation information provided by
Web of Science

References (15)

Search for Neutrinoless Double-Beta Decay with the Upgraded EXO-200 Detector journal February 2018
Cold electronics for "Giant" Liquid Argon Time Projection Chambers journal July 2011
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Deep Residual Learning for Image Recognition conference June 2016
Geant4 developments and applications journal February 2006
Deep learning journal May 2015
Deep neural networks for energy and position reconstruction in EXO-200 journal August 2018
Positive-hole mobility in liquid xenon as a function of temperature journal November 1994
Charge Transport in Solid and Liquid Ar, Kr, and Xe journal February 1968
Geant4—a simulation toolkit
  • Agostinelli, S.; Allison, J.; Amako, K.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 506, Issue 3 https://doi.org/10.1016/S0168-9002(03)01368-8
journal July 2003
Measurement of the drift velocity and transverse diffusion of electrons in liquid xenon with the EXO-200 detector journal February 2017
Sensitivity and discovery potential of the proposed nEXO experiment to neutrinoless double- β decay journal June 2018
A convolutional neural network neutrino event classifier journal September 2016
The EXO-200 detector, part I: detector design and construction journal May 2012
Recent developments of liquid xenon detectors journal May 1982

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