The Neutrino Mediterranean Observatory Laser Beacon: Design and Qualification

This research was funded by the Ministerio de Ciencia e Innovación: Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia (refs. PID2021-124591NB-B-C41) (MCIU/FEDER); the Programa de Planes Complementarios I+D+I (refs. ASFAE/2022/023); Generalitat Valenciana: Prometeo (PROMETEO/2020/019); the Grisolía (ref. GRISOLIAP/2021/192) and GenT (refs. CIDEGENT/2018/034, /2020/049, /2021/23) programs; and the EU: MSC program (ref. 101025085), Spain.This paper encapsulates details of the NEMO laser beacon's design, offering a profound contribution to the field of the time calibration of underwater neutrino telescopes. The mechanical design of the laser beacon, which operates at a depth of 3500 m, is presented, together with the design of the antibiofouling system employed to endure the operational pressure and optimize the operational range, enhancing its functionality and enabling time calibration among multiple towers. A noteworthy innovation central to this development lies in the battery system. This configuration enhances the device's portability, a crucial aspect in underwater operations. The comprehensive design of the laser beacon, encompassing the container housing, the requisite battery system for operation, electronics, and an effective antibiofouling system, is described in this paper. Additionally, this paper presents the findings of the laser beacon's qualification process.Ministerio de Ciencia e Innovación: Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia PID2021-124591NB-B-C41Programa de Planes Complementarios I+D+I ASFAE/2022/023Center for Forestry Research & Experimentation (CIEF) PROMETEO/2020/019Grisolia GRISOLIAP/2021/192GenT CIDEGENT/2018/034, CIDEGENT/2020/049, CIDEGENT/2021/23EU: MSC program, Spain 10102508

Memory management unit for hardware-assisted dynamic relocation in on-board satellite systems

Satellite on-board systems spend their lives in hostile environments, where radiation can cause critical hardware failures. One of the most radiation-sensitive elements is memory. The so-called single event effects (SEEs) can corrupt or even irretrievably damage the cells that store the data and program instructions. When one of these cells is corrupted, the program must not use it again during execution. In order to avoid rebuilding and uploading the code, a memory management unit can be used to transparently relocate the program to an error-free memory region. This article presents the design and implementation of a memory management unit that allows the dynamic relocation of on-board software. This unit provides a hardware mechanism that allows the automatic relocation of sections of code or data at run-time, only requiring software intervention for initialization and configuration. The unit has been implemented on the LEON architecture, a reference for the European Space Agency (ESA) missions. The proposed solution has been validated using the boot and application software (ASW) of the instrument control unit of the Energetic Particle Detector of the Solar Orbiter Mission as a base. Processor synthesis on different FPGAs has shown resource usage and power consumption similar to that of a conventional memory management unit. The results vary between ± 1?15% in resource usage and ± 1?7% in power consumption, depending on the number of inputs assigned to the unit and the FPGA used. When comparing performance, both the proposed and conventional memory management units show the same results.Universidad de Alcal

Science with Neutrino Telescopes in Spain

[EN] The primary scientific goal of neutrino telescopes is the detection and study of cosmic neutrino signals. However, the range of physics topics that these instruments can tackle is exceedingly wide and diverse. Neutrinos coming from outside the Earth, in association with othermessengers, can contribute to clarify the question of the mechanisms that power the astrophysical accelerators which are known to exist from the observation of high-energy cosmic and gamma rays. Cosmic neutrinos can also be used to bring relevant information about the nature of dark matter, to study the intrinsic properties of neutrinos and to look for physics beyond the Standard Model. Likewise, atmospheric neutrinos can be used to study an ample variety of particle physics issues, such as neutrino oscillation phenomena, the determination of the neutrino mass ordering, non-standard neutrino interactions, neutrino decays and a diversity of other physics topics. In this article, we review a selected number of these topics, chosen on the basis of their scientific relevance and the involvement in their study of the Spanish physics community working in the KM3NeT and ANTARES neutrino telescopes.The authors gratefully acknowledge the funding support from the following Spanish programs: Ministerio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER); Generalitat Valenciana: Prometeo (PROMETEO/2020/019) and GenT (refs. CIDEGENT/2018/034, /2020/049, /2021/023); Junta de Andalucia (ref. A-FQM-053-UGR18).Hernández-Rey, JJ.; Ardid Ramírez, M.; Bou Cabo, M.; Calvo, D.; Díaz, AF.; Gozzini, SR.; Martínez Mora, JA.... (2022). Science with Neutrino Telescopes in Spain. Universe. 8(2):1-25. https://doi.org/10.3390/universe80200891258

Implementation and first results of the KM3NeT real-time core-collapse supernova neutrino search

The KM3NeT research infrastructure is unconstruction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at GeV–PeV neutrinos. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems, are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given.Acknowledgements The authors acknowledge the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Européenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Île-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-18-1268), Georgia; Deutsche Forschungsgemeinschaft (DFG), Germany; The General Secretariat of Research and Technology (GSRT), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell’Università e della Ricerca (MIUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education Scientific Research and Professional Training, ICTP through Grant AF-13, Morocco; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2015/18/E/ST2/00758); National Authority for Scientific Research (ANCS), Romania; Ministerio de Ciencia, Innovación, Investigación y Universidades (MCIU): Programa Estatal de Generación de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Generalitat Valenciana: Prometeo (PROMETEO/2020/019), Grisolía (ref. GRISOLIA/2018/119) and GenT (refs. CIDEGENT/2018/034, /2019/043, /2020/049) programs, Junta de Andalucía (ref. A-FQM-053-UGR18), La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 101025085), Spain

Responding to the challenges of Water and Global Warming: Environmental Hydrogeology and Global Change Research Group (HYGLO-Lab)

[EN] The current Global Warming of planet Earth is probably the most important geological phenomenon in the last 20,000 years of its history and for human race. This process is having nowadays notable effects on the climate, ecosystems and natural resources. Possibly the most important renewable geological resource is water. One of the most strategic phases of the water cycle is groundwater. Despite its low visibility, quantitatively (and qualitatively too) it is essential for life on Planet Earth. Foreseeable consequences on groundwater due to climate change and sea level rise will be very significant. Hydrogeology can provide answers to many of the questions that are beginning to be raised in relation to these impacts and their effects. Environmental hydrogeology is a way of understanding the set of disciplines mixed in Hydrogeology as a Science of Nature. The HYGLO-Lab Research Group of the IGME-CSIC National Center attempts, through its lines of research, with a double global and local component, to provide answers to some of these questions.Peer reviewe

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Results from the ANTARES neutrino telescope

The ANTARES detector is an underwater neutrino telescope, the largest in the Northern Hemisphere and the first one ever built under the sea, located in the Mediterranean Sea 40 km off the Southern coast of France, at a depth of 2.5 km. It comprises 885 photomultiplier tubes distributed along twelve detection lines. The signal due to neutrinos is searched by reconstructing the tracks of secondary particles produced in the surroundings of the detector. The detector is in data taking with its final configuration since 2008. It is aimed at identifying the sources, either steady or flaring, of cosmic neutrinos, and is also suitable for detection of dark matter within the Sun and/or Galactic Centre. ANTARES can contribute in the confirmation of the cosmic neutrino flux observed by IceCube, being particularly competitive for the Galactic Centre, and in general for galactic sources, due its latitude and at lower energies and softer spectra due its configuration. Several multi-messenger analyses have been also attempted, including the search of coincidence signals of neutrinos with gravitational-waves. Additional topics include neutrino oscillations or the search of exotic particles, like nuclearites and magnetic monopoles. Results from the latest analyses are presented

Multimessenger Astronomy with Neutrinos

Multimessenger astronomy is arguably the branch of the astroparticle physics field that has seen the most significant developments in recent years. In this manuscript, we will review the state-of-the-art, the recent observations, and the prospects and challenges for the near future. We will give special emphasis to the observation carried out with neutrino telescopes