Abstract: 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. 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. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.

Abstract: 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.

Abstract: 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.

Abstract: Since 2015 the LIGO and Virgo interferometers have detected gravitational waves from almost one hundred coalescences of compact objects (black holes and neutron stars). This article presents the results of a search performed with data from the ANTARES telescope to identify neutrino counterparts to the gravitational wave sources detected during the third LIGO/Virgo observing run and reported in the catalogues GWTC-2, GWTC-2.1, and GWTC-3. This search is sensitive to all-sky neutrinos of all flavours and of energies > 100 GeV, thanks to the inclusion of both track-like events (mainly induced by v μcharged -current interactions) and shower-like events (induced by other interaction types). Neutrinos are selected if they are detected within +/- 500 s from the GW merger and with a reconstructed direction compatible with its sky localisation. No significant excess is found for any of the 80 analysed GW events, and upper limits on the neutrino emission are derived. Using the information from the GW catalogues and assuming isotropic emission, upper limits on the total energy Etot,v emitted as neutrinos of all flavours and on the ratio fv = Etot,v/EGW between neutrino and GW emissions are also computed. Finally, a stacked analysis of all the 72 binary black hole mergers (respectively the 7 neutron star-black hole merger candidates) has been performed to constrain the typical neutrino emission within this population, leading to the limits: Etot,v < 4.0 x 1053 erg and fv < 0.15 (respectively, Etot,v < 3.2 x 1053 erg and fv < 0.88) for E-2 spectrum and isotropic emission. Other assumptions including softer spectra and non-isotropic scenarios have also been tested.

Abstract: Solar Atmospheric Neutrinos (SA nu s) are produced by the interaction of cosmic rays with the solar medium. The detection of SA nu s would provide useful information on the composition of primary cosmic rays as well as the solar density. These neutrinos represent an irreducible source of background for indirect searches for dark matter towards the Sun and the measurement of their flux would allow for a better assessment of the uncertainties related to these searches. In this paper we report on the analysis performed, based on an unbinned likelihood maximisation, to search for SA nu s with the ANTARES neutrino telescope. After analysing the data collected over 11 years, no evidence for a solar atmospheric neutrino signal has been found. An upper limit at 90% confidence level on the flux of solar atmospheric neutrinos has been obtained, equal to 7x10(-11) [TeV-1 cm(-2) s(-1)] b at E-nu = 1 TeV for the reference cosmic ray model assumed.