Constraining the contribution of Gamma-Ray Bursts to the high-energy diffuse neutrino flux with 10 yr of ANTARES data

Addressing the origin of the astrophysical neutrino flux observed by IceCube is of paramount importance. Gamma-Ray Bursts (GRBs) are among the few astrophysical sources capable of achieving the required energy to contribute to such neutrino flux through pγ interactions. In this work, ANTARES data have been used to search for upward going muon neutrinos in spatial and temporal coincidence with 784 GRBs occurred from 2007 to 2017. For each GRB, the expected neutrino flux has been calculated in the framework of the internal shock model and the impact of the lack of knowledge on the majority of source redshifts and on other intrinsic parameters of the emission mechanism has been quantified. It is found that the model parameters that set the radial distance where shock collisions occur have the largest impact on neutrino flux expectations. In particular, the bulk Lorentz factor of the source ejecta and the minimum variability time-scale are found to contribute significantly to the GRB-neutrino flux uncertainty. For the selected sources, ANTARES data have been analysed by maximizing the discovery probability of the stacking sample through an extended maximum-likelihood strategy. Since no neutrino event passed the quality cuts set by the optimization procedure, 90 per cent confidence level upper limits (with their uncertainty) on the total expected diffuse neutrino flux have been derived, according to the model. The GRB contribution to the observed diffuse astrophysical neutrino flux around 100 TeV is constrained to be less than 10 per cent

Architecture and performance of the KM3NeT front-end firmware

The KM3NeT infrastructure consists of two deep-sea neutrino telescopes being deployed in the Mediterranean Sea. The telescopes will detect extraterrestrial and atmospheric neutrinos by means of the incident photons induced by the passage of relativistic charged particles through the seawater as a consequence of a neutrino interaction. The telescopes are configured in a three-dimensional grid of digital optical modules, each hosting 31 photomultipliers. The photomultiplier signals produced by the incident Cherenkov photons are converted into digital information consisting of the integrated pulse duration and the time at which it surpasses a chosen threshold. The digitization is done by means of time to digital converters (TDCs) embedded in the field programmable gate array of the central logic board. Subsequently, a state machine formats the acquired data for its transmission to shore. We present the architecture and performance of the front-end firmware consisting of the TDCs and the state machine

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

Search for dark matter towards the Galactic Centre with 11 years of ANTARES data

Neutrino detectors participate in the indirect search for the fundamental constituents of dark matter (DM) in form of weakly interacting massive particles (WIMPs). In WIMP scenarios, candidate DM particles can pair-annihilate into Standard Model products, yielding considerable fluxes of high-energy neutrinos. A detector like ANTARES, located in the Northern Hemisphere, is able to perform a complementary search looking towards the Galactic Centre, where a high density of dark matter is thought to accumulate. Both this directional information and the spectral features of annihilating DM pairs are entered into an unbinned likelihood method to scan the data set in search for DM-like signals in ANTARES data. Results obtained upon unblinding 3170 days of data reconstructed with updated methods are presented, which provides a larger, and more accurate, data set than a previously published result using 2101 days. A non-observation of dark matter is converted into limits on the velocity-averaged cross section for WIMP pair annihilation

Determining the Neutrino Mass Ordering and Oscillation Parameters with KM3NeT/ORCA

The KM3NeT/ORCA sensitivity to atmospheric neutrino oscillation is presented. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4 σ if the true ordering is normal and 2.3 σ if inverted, after three years of data taking. The precision to measure Δm232 and θ23 were also estimated and found to be 85⋅10−6 eV2 and (+1.9−3.1)∘ for normal neutrino mass ordering and, 75⋅10−6 eV2 and (+2.0−7.0)∘ for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude ντ and ν¯τ event rate variations larger than 20% at 3σ level

MasterClasses 2019 @ Colmar IUT

Journées master-classeNational audienceLes journées MasterClasses en physique des particules rassemblent chaque année près de 5000 lycéens autour de 80 centres de recherche dans 23 pays, pour vivre la réalité du métier de chercheur en physique des particules. Ce programme est initié par l’Université Technique de Dresde dans le cadre de l’European Particle Physics Outreach Group, en collaboration avec le CERN (Organisation européenne pour la recherche nucléaire). En France, la coordination est assurée par le CNRS. Le 11 & 18 mars 2019, l’Institut Pluridisciplinaire Hubert Curien de Strasbourg et l'Institut Universitaire Technologique de Colmar participent aux journées internationales MasterClasses et invitent les classes de Première et Terminale scientifiques à prendre part à cette aventure. Il s’agit de la cinquième édition sur Colmar. Les journées MasterClasses ont été initiées sur Colmar pour utiliser et valoriser les ressources de l’IUT. A cet effet, l’accent sera porté sur les défis technologiques du LHC à travers les thématiques de trois départements : GTE (Génie Thermique et Energie), RT (Réseaux Télécommunications) et HSE (Hygiène Sécurité et Environnement). En particulier, les liens entre recherche, milieu professionnel et formation seront exposés. Elles accueilleront une cinquantaine de lycéens par jour : - Le 11 mars, des élèves du lycée Louis Armand (Mulhouse), du lycée Blaise Pascal (Colmar), du lycée Don Bosco (Mulhouse), - Le 18 mars, des élèves du lycée Camille See (Colmar), du lycée Kirschleger (Munster), du lycée Scheurer Kestner (Thann), du lycée Louise Wiess (Sainte-Marie-aux-Mines) Après une introduction à la physique des particules et aux techniques d’investigation scientifique, les jeunes pourront entrer dans la peau d’un chercheur et analyser des données réelles de physique des particules collectées par des expériences auprès de l’accélérateur LHC. Ils devront chercher le boson de Higgs dans les données récoltées par le détecteur ATLAS avec une stratégie différente pour le 11 et le 18 mars. Puis, ils participeront en groupe restreint à 4 ateliers où ils pourront échanger avec des enseignants et des chercheurs des départements GTE, RT et HSE de l’IUT sur les problématiques technologiques et instrumentales de la physique des particules. Après avoir confronté leurs résultats d’analyse localement, ils se réuniront autour d'une visioconférence internationale en anglais, animée depuis Genève, par le CERN, avec des équipes de lycéens d’autres pays participants (Maroc, Italie, Suède, Espagne et France pour le 11 mars et Allemagne, Slovénie, Pologne et France pour le 18 mars) qui auront réalisé en simultané les mêmes analyses sur d’autres données. Les résultats finaux seront comparés avec ceux déjà obtenus par les physiciens

Indirect dark matter searches with the ANTARES and KM3NeT neutrino telescopes

Neutrino telescopes perform an indirect search for dark matter (DM) through its annihilation into standard model channels yielding neutrinos, for a broad range of WIMP masses. The ANTARES detector, anchored to the Mediterranean seabed at a depth of about 2500 m, looks for a DM signal from two promising neutrino sources from WIMP annihilation: the Galactic Center and the Sun. We present the latest results on ANTARES indirect detection in a wide range of WIMP masses and decay channels, and give a future prospect on sensitivities of DM searches with the KM3NeT detector, the next-generation neutrino telescope, currently under deployment in the Mediterranean Sea. These experiments have specific advantages, complementary to other detection strategies, and can provide a smoking-gun signal. The geographical location of ANTARES and KM3NeT is particularly well suited for searches in the Galactic Center, allowing for the world-best sensitivity for WIMP annihilation

Deep-Sea Bioluminescence Blooms after Dense Water Formation at the Ocean Surface

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as “open-sea convection”. It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts

Deep-Sea Bioluminescence Blooms after Dense Water Formation at the Ocean Surface

<p>The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as "open-sea convection". It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts.</p>