Resumen:
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[EN] We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the ...[+]
[EN] We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the unique opportunity to infer information on bioluminescent organisms without actively interfering with them. We propose a statistical method that allows us to reconstruct the light emission of individual organisms, as well as their location and movement. A mathematical model is built to describe the measurement process of underwater neutrino telescopes and the signal generation of the biological organisms. The Metric Gaussian Variational Inference algorithm is used to reconstruct the model parameters using photon counts recorded by photomultiplier tubes. We apply this method to synthetic data sets and data collected by the ANTARES neutrino telescope. The telescope is located 40 km off the French coast and fixed to the sea floor at a depth of 2475 m. The runs with synthetic data reveal that we can model the emitted bioluminescent flashes of the organisms. Furthermore, we find that the spatial resolution of the localization of light sources highly depends on the configuration of the telescope. Precise measurements of the efficiencies of the detectors and the attenuation length of the water are crucial to reconstruct the light emission. Finally, the application to ANTARES data reveals the first localizations of bioluminescent organisms using neutrino telescope data.
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Código del Proyecto:
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-A-C42/ES/CARACTERIZACION DEL FONDO ACUSTICO EN EL OBSERVATORIO SUBMARINO KM3NET/
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-A-C42/ES/CARACTERIZACION DEL FONDO ACUSTICO EN EL OBSERVATORIO SUBMARINO KM3NET/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-B-C41/ES/FISICA FUNDAMENTAL Y ASTRONOMIA MULTIMENSAJERO CON TELESCOPIOS DE NEUTRINOS/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-B-C43/ES/FISICA FUNDAMENTAL, DETECCION ACUSTICA Y ASTRONOMIA MULTI-MENSAJERO CON TELESCOPIOS DE NEUTRINOS EN LA UPV/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-B-C44/ES/FISICA FUNDAMENTAL Y ASTRONOMIA MULTI-MENSAJERO CON TELESCOPIOS DE NEUTRINOS EN LA UGR/
info:eu-repo/grantAgreement/ANR//ANR-10-LABX-0023/FR/Universe: observation, modeling, transfer/
info:eu-repo/grantAgreement/ANR//ANR-18-IDEX-0001/FR/Université de Paris/
info:eu-repo/grantAgreement/EC/H2020/101025085/EU/Unifying Neutrino Observatories Searches/
info:eu-repo/grantAgreement/EC/H2020/772663/EU/The MAgnetic field in the GALaxy, using Optical Polarization of Stars/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//CIDEGENT%2F2019%2F043//AYUDA CONTRATACION CIDEGENT INVESTIGADORES DE EXCELENCIA-ARDID RAMIREZ, JOAN/
info:eu-repo/grantAgreement/GENERALITAT VALENCIANA//GRISOLIAP%2F2018%2F119//AYUDA SANTIAGO GRISOLIA PROYECTO: ACUSTICA EN DETECTORES DE PARTICULAS/
info:eu-repo/grantAgreement/Junta de Andalucía//A-FQM-053-UGR18 /
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2020%2F019/
info:eu-repo/grantAgreement/GVA//CIDEGENT%2F2018%2F034 /
info:eu-repo/grantAgreement/GVA//CIDEGENT%2F2020%2F049 /
info:eu-repo/grantAgreement/Fundació Bancària Caixa d'Estalvis i Pensions de Barcelona//LCF%2FBQ%2FIN17%2F11620019 /
info:eu-repo/grantAgreement/Conseil Régional d'Alsace//CPER/
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Agradecimientos:
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We thank our colleagues of the Information Field Theory Group who provided insight and expertise on the NIFTy framework and Statistical Inference. We would also like to show our gratitude to Thomas Eberl for sharing his ...[+]
We thank our colleagues of the Information Field Theory Group who provided insight and expertise on the NIFTy framework and Statistical Inference. We would also like to show our gratitude to Thomas Eberl for sharing his expertise on the ANTARES experiment and the data set. SH acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 772663). The authors acknowledge the financial support of the funding agencies: Centre National de la Recherche Scientifique (CNRS), Commissariat a l'energie atomique et aux energies alternatives (CEA), Commission Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Region Ile-de-France (DIM-ACAV), Region Alsace (contrat CPER), Region Provence-Alpes-Cote d'Azur, Departement du Var and Ville de La Seyne-sur-Mer, France; Bundesministerium fur Bildung und Forschung (BMBF), Germany; Istituto Nazionale di Fisica Nucleare (INFN), Italy; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; Council of the President of the Russian Federation for young scientists and leading scientific schools supporting grants, Russia; Executive Unit for Financing Higher Education, Research, Development and Innovation (UEFISCDI), Romania; Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, PGC2018-096663-A-C42, PGC2018-096663-B-C43, PGC2018-096663-B-C44) (MCIU/FEDER), Generalitat Valenciana: Prometeo (PROMETEO/2020/019), Grisolia (ref. GRISOLIA/2018/119), and GenT (refs. CIDEGENT/2018/034, CIDEGENT//2019/043, CIDEGENT//2020/049) programs, Junta de Andalucia (ref. A-FQM-053-UGR18), La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 101025085), Spain; Ministry of Higher Education, Scientific Research and Professional Training, Morocco. We also acknowledge the technical support of Ifremer, AIM, and Foselev Marine for the sea operation and the CC-IN2P3 for the computing facilities. Open Access funding enabled and organized by Projekt DEAL.
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