Time calibration of the ANTARES neutrino telescope

The ANTARES deep-sea neutrino telescope comprises a three-dimensional array of photomultipliers to detect the Cherenkov light induced by upgoing relativistic charged particles originating from neutrino interactions in the vicinity of the detector. The large scattering length of light in the deep sea facilitates an angular resolution of a few tenths of a degree for neutrino energies exceeding 10 TeV. In order to achieve this optimal performance, the time calibration procedures should ensure a relative time calibration between the photomultipliers at the level of similar to 1 ns. The methods developed to attain this level of precision are described

Search for a diffuse flux of high-energy νμ\nu_\mu with the ANTARES neutrino telescope

A search for a diffuse flux of astrophysical muon neutrinos, using data collected by the ANTARES neutrino telescope is presented. A $(0.83\times 2\pi)$ sr sky was monitored for a total of 334 days of equivalent live time. The searched signal corresponds to an excess of events, produced by astrophysical sources, over the expected atmospheric neutrino background. The observed number of events is found compatible with the background expectation. Assuming an $E^{-2}$ flux spectrum, a 90% c.l. upper limit on the diffuse $\nu_\mu$ flux of E^2\Phi_{90%} = 5.3 \times 10^{-8} \ \mathrm{GeV\ cm^{-2}\ s^{-1}\ sr^{-1}} in the energy range 20 TeV - 2.5 PeV is obtained. Other signal models with different energy spectra are also tested and some rejected.Comment: 14 pages, 6 figure

gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes

Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrián-Martínez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project.French National Research Agency (ANR) ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS)European Union (EU)Institut Universitaire de France (IUF), FranceIdEx program, FranceUnivEarthS Labex program at Sorbonne Paris Cite ANR-10-LABX-0023 ANR-11-IDEX-000502Paris Ile-de-France Region, FranceShota Rustaveli National Science Foundation of Georgia (SRNSFG), Georgia FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR)PRIN 2017 program Italy NAT-NET 2017W4HA7SMinistry of Higher Education, Scientific Research and Professional Training, MoroccoNetherlands Organization for Scientific Research (NWO) Netherlands GovernmentNational Science Centre, Poland 2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento, Spain (MCIU/FEDER) PGC2018-096663-B-C41 PGC2018-096663-A-C42 PGC2018-096663-BC43 PGC2018-096663-B-C44Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia, Spain SOMM17/6104/UGRGeneralitat Valenciana: Grisolia, Spain GRISOLIA/2018/119GenT, Spain CIDEGENT/2018/034La Caixa Foundation LCF/BQ/IN17/11620019EU: MSC program, Spain 71367

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

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 Europeenne (FEDER fund and Marie Curie Program), Institut Universitaire de France (IUF), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Ile-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'Universita e della Ricerca (MUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education, Scientific Research and Professional Training, 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, Innovacion, Investigacion y Universidades (MCIU): Programa Estatal de Generacion de Conocimiento (refs. PGC2018-096663-B-C41, -A-C42, -B-C43, -B-C44) (MCIU/FEDER), Severo Ochoa Centre of Excellence and MultiDark Consolider (MCIU), Junta de Andalucia (ref. SOMM17/6104/UGR), Generalitat Valenciana: Grisolia (ref. GRISOLIA/2018/119) and GenT (ref. CIDEGENT/2018/034) programs, La Caixa Foundation (ref. LCF/BQ/IN17/11620019), EU: MSC program (ref. 713673), Spain.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.French National Research Agency (ANR) ANR-15-CE31-0020Centre National de la Recherche Scientifique (CNRS), Commission Europeenne (FEDER fund)European Union (EU)Institut Universitaire de France (IUF)LabEx UnivEarthS ANR-10-LABX-0023 ANR-18-IDEX-0001Shota Rustaveli National Science Foundation of Georgia FR-18-1268German Research Foundation (DFG)Greek Ministry of Development-GSRTIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Universities and Research (MIUR) Research Projects of National Relevance (PRIN)Ministry of Higher Education, Scientific Research and Professional Training, MoroccoNetherlands Organization for Scientific Research (NWO)National Science Centre, Poland 2015/18/E/ST2/00758National Authority for Scientific Research (ANCS), RomaniaMinisterio de Ciencia, Innovacion, Investigacion y Universidades PGC2018-096663-B-C41 A-C42 B-C43 B-C44Severo Ochoa Centre of ExcellenceJunta de Andalucia SOMM17/6104/UGRGeneralitat Valenciana: Grisolia GRISOLIA/2018/119 CIDEGENT/2018/034La Caixa Foundation LCF/BQ/IN17/11620019EU: MSC program 71367

ANTARES: the first undersea neutrino telescope

The ANTARES Neutrino Telescope was completed in May 2008 and is the first operational Neutrino Telescope in the Mediterranean Sea. The main purpose of the detector is to perform neutrino astronomy and the apparatus also offers facilities for marine and Earth sciences. This paper describes the design, the construction and the installation of the telescope in the deep sea, offshore from Toulon in France. An illustration of the detector performance is given

Characteristics of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) rRNA genes of Apis mellifera (Insecta: Hymenoptera): structure, organization, and retrotransposable elements

As an accompanying manuscript to the release of the honey bee genome, we report the entire sequence of the nuclear (18S, 5.8S, 28S and 5S) and mitochondrial (12S and 16S) ribosomal RNA (rRNA)-encoding gene sequences (rDNA) and related internally and externally transcribed spacer regions of Apis mellifera (Insecta: Hymenoptera: Apocrita). Additionally, we predict secondary structures for the mature rRNA molecules based on comparative sequence analyses with other arthropod taxa and reference to recently published crystal structures of the ribosome. In general, the structures of honey bee rRNAs are in agreement with previously predicted rRNA models from other arthropods in core regions of the rRNA, with little additional expansion in non-conserved regions. Our multiple sequence alignments are made available on several public databases and provide a preliminary establishment of a global structural model of all rRNAs from the insects. Additionally, we provide conserved stretches of sequences flanking the rDNA cistrons that comprise the externally transcribed spacer regions (ETS) and part of the intergenic spacer region (IGS), including several repetitive motifs. Finally, we report the occurrence of retrotransposition in the nuclear large subunit rDNA, as R2 elements are present in the usual insertion points found in other arthropods. Interestingly, functional R1 elements usually present in the genomes of insects were not detected in the honey bee rRNA genes. The reverse transcriptase products of the R2 elements are deduced from their putative open reading frames and structurally aligned with those from another hymenopteran insect, the jewel wasp Nasonia (Pteromalidae). Stretches of conserved amino acids shared between Apis and Nasonia are illustrated and serve as potential sites for primer design, as target amplicons within these R2 elements may serve as novel phylogenetic markers for Hymenoptera. Given the impending completion of the sequencing of the Nasonia genome, we expect our report eventually to shed light on the evolution of the hymenopteran genome within higher insects, particularly regarding the relative maintenance of conserved rDNA genes, related variable spacer regions and retrotransposable elements

Management of patients with increased risk for familial pancreatic cancer: updated recommendations from the International Cancer of the Pancreas Screening (CAPS) Consortium

Surgical oncolog