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Background rejection in NEXT using deep neural networks

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Background rejection in NEXT using deep neural networks

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Renner, J., Farbin, A., Vidal, J. M., Benlloch-Rodríguez, J. M., Botas, A., Ferrario, P., . . . Yepes-Ramírez, H. (2017). Background rejection in NEXT using deep neural networks. Journal of Instrumentation, 12(1)10.1088/1748-0221/12/01/T01004

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/81409

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Title: Background rejection in NEXT using deep neural networks
Author:
UPV Unit: Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials
Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació
Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia
Issued date:
Abstract:
[EN] We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track ...[+]
Subjects: Analysis and statistical methods , Double-beta decay detectors , Time projection chambers , cluster finding , Pattern recognition , calibration and fitting methods
Copyrigths: Reserva de todos los derechos
Source:
Journal of Instrumentation. (issn: 1748-0221 )
DOI: 10.1088/1748-0221/12/01/T01004
Publisher:
IOP Publishing
Publisher version: http://dx.doi.org/10.1088/1748-0221/12/01/T01004
Project ID: info:eu-repo/grantAgreement/EC/FP7/339787/EU
Thanks:
The NEXT Collaboration acknowledges support from the following agencies and institutions: the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the Ministerio de Economia y Competitividad of Spain and ...[+]
Type: Artículo

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