Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment

Kekic, M.; Adams, C.; Woodruff, K.; Renner, J.; Church, E.; Del Tutto, M.; Hernando Morata, J. A.; Gomez-Cadenas, J. J.; Álvarez-Puerta, Vicente; Arazi, L.; Arnquist, I.J.; Azevedo, C. D. R.; Bailey, K.; Ballester Merelo, Francisco José; Benlloch-Rodriguez, J. M.; Esteve Bosch, Raul; Herrero Bosch, Vicente; Mora Mas, Francisco José; Rodriguez-Samaniego, Javier; Toledo Alarcón, José Francisco

doi:10.1007/JHEP01(2021)189

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Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment

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Kekic, M.; Adams, C.; Woodruff, K.; Renner, J.; Church, E.; Del Tutto, M.; Hernando Morata, JA.... (2021). Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment. Journal of High Energy Physics (Online). (1):1-22. https://doi.org/10.1007/JHEP01(2021)189

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Título:

Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment

Autor:

Kekic, M. Adams, C. Woodruff, K. Renner, J. Church, E. Del Tutto, M. Hernando Morata, J. A. Gomez-Cadenas, J. J.

Álvarez-Puerta, Vicente Arazi, L. Arnquist, I.J. Azevedo, C. D. R. Bailey, K.

Ballester Merelo, Francisco José Benlloch-Rodriguez, J. M.

Esteve Bosch, Raul

Herrero Bosch, Vicente

Mora Mas, Francisco José Rodriguez-Samaniego, Javier

Toledo Alarcón, José Francisco

Entidad UPV:

Universitat Politècnica de València. Instituto de Instrumentación para Imagen Molecular - Institut d'Instrumentació per a Imatge Molecular
Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica

Fecha difusión:

2021-01-28

Resumen:

[EN] Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high-energy physics. In this paper, we attempt to understand the potential of CNNs ...[+]

Palabras clave:

Dark Matter and Double Beta Decay (experiments)

Derechos de uso:

Reconocimiento (by)

Fuente:

Journal of High Energy Physics (Online). (eissn: 1029-8479 )

DOI:

10.1007/JHEP01(2021)189

Editorial:

Springer-Verlag

Versión del editor:

https://doi.org/10.1007/JHEP01(2021)189

Código del Proyecto:

info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095979-B-C44/ES/CONSTRUCCION Y OPERACION DEL DETECTOR NEXT-100/
...[+]

Agradecimientos:

This study used computing resources from Artemisa, co-funded by the European Union through the 2014-2020 FEDER Operative Programme of the Comunitat Valenciana, project DIFEDER/2018/048. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. The NEXT collaboration acknowledges support from the following agencies and institutions: Xunta de Galicia (Centro singularde investigacion de Galicia accreditation 2019-2022), by European Union ERDF, and by the "Maria de Maeztu" Units of Excellence program MDM-2016-0692 and the Spanish Research State Agency"; the European Research Council (ERC) under the Advanced Grant 339787-NEXT; the European Union's Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Grant Agreements No. 674896, 690575 and 740055; the Ministerio de Economia y Competitividad and the Ministerio de Ciencia, Innovacion y Universidades of Spain under grants FIS2014-53371-C04, RTI2018-095979, the Severo Ochoa Program grants SEV-20140398 and CEX2018-000867-S; the GVA of Spain under grants PROMETEO/2016/120 and SEJI/2017/011; the Portuguese FCT under project PTDC/FIS-NUC/2525/2014 and under projects UID/FIS/04559/2020 to fund the activities of LIBPhys-UC; the U.S. Department of Energy under contracts number DE-AC02-07CH11359 (Fermi National Accelerator Laboratory), DE-FG02-13ER42020 (Texas A&M) and DE-SC0019223/DE SC0019054 (University of Texas at Arlington); and the University of Texas at Arlington. DGD acknowledges Ramon y Cajal program (Spain) under contract number RYC-2015 18820. JMA acknowledges support from Fundacion Bancaria "la Caixa" (ID 100010434), grant code LCF/BQ/PI19/11690012. We also warmly acknowledge the Laboratori Nazionali del Gran Sasso (LNGS) and the Dark Side collaboration for their help with TPB coating of various parts of the NEXT-White TPC. Finally, we are grateful to the Laboratorio Subterraneo de Canfranc for hosting and supporting the NEXT experiment. [-]

Tipo:

Artículo

References

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