Abstract: The ANTARES neutrino telescope, located 40km off the coast of Toulon in the Mediterranean Sea at a mooring depth of about 2475m, consists of twelve detection lines equipped typically with 25 storeys. Every storey carries three optical modules that detect Cherenkov light induced by charged secondary particles (typically muons) coming from neutrino interactions. As these lines are flexible structures fixed to the sea bed and held taut by a buoy, sea currents cause the lines to move and the storeys to rotate. The knowledge of the position of the optical modules with a precision better than 10cm is essential for a good reconstruction of particle tracks. In this paper the ANTARES positioning system is described. It consists of an acoustic positioning system, for distance triangulation, and a compass-tiltmeter system, for the measurement of the orientation and inclination of the storeys. Necessary corrections are discussed and the results of the detector alignment procedure are described.

Abstract: A translation of the penelope physics subroutines to C++, designed as an extension of the Geant4 toolkit, is presented. The Fortran code system penelope performs Monte Carlo simulation of coupled electron-photon transport in arbitrary materials for a wide energy range, nominally from 50 eV up to 1 GeV. Penelope implements the most reliable interaction models that are currently available, limited only by the required generality of the code. In addition, the transport of electrons and positrons is simulated by means of an elaborate class II scheme in which hard interactions (involving deflection angles or energy transfers larger than pre-defined cutoffs) are simulated from the associated restricted differential cross sections. After a brief description of the interaction models adopted for photons and electrons/positrons, we describe the details of the class-II algorithm used for tracking electrons and positrons. The C++ classes are adapted to the specific code structure of Geant4. They provide a complete description of the interactions and transport mechanics of electrons/positrons and photons in arbitrary materials, which can be activated from the G4ProcessManager to produce simulation results equivalent to those from the original penelope programs. The combined code, named PenG4, benefits from the multi-threading capabilities and advanced geometry and statistical tools of Geant4.

Abstract: As part of the European LAGUNA design study on a next-generation neutrino detector, we propose the liquid-scintillator detector LENA (Low Energy Neutrino Astronomy) as a multipurpose neutrino observatory. The outstanding successes of the Borexino and KamLAND experiments demonstrate the large potential of liquid-scintillator detectors in low-energy neutrino physics. Low energy threshold, good energy resolution and efficient background discrimination are inherent to the liquid-scintillator technique. A target mass of 50 kt will offer a substantial increase in detection sensitivity. At low energies, the variety of detection channels available in liquid scintillator will allow for an energy and flavor-resolved analysis of the neutrino burst emitted by a galactic Supernova. Due to target mass and background conditions, LENA will also be sensitive to the faint signal of the Diffuse Supernova Neutrino Background. Solar metallicity, time-variation in the solar neutrino flux and deviations from MSW-LMA survival probabilities can be investigated based on unprecedented statistics. Low background conditions allow to search for dark matter by observing rare annihilation neutrinos. The large number of events expected for geoneutrinos will give valuable information on the abundances of Uranium and Thorium and their relative ratio in the Earth's crust and mantle. Reactor neutrinos enable a high-precision measurement of solar mixing parameters. A strong radioactive or pion decay-at-rest neutrino source can be placed close to the detector to investigate neutrino oscillations for short distances and sub-MeV to MeV energies. At high energies, LENA will provide a new lifetime limit for the SUSY-favored proton decay mode into kaon and antineutrino, surpassing current experimental limits by about one order of magnitude. Recent studies have demonstrated that a reconstruction of momentum and energy of GeV particles is well feasible in liquid scintillator. Monte Carlo studies on the reconstruction of the complex event topologies found for neutrino interactions at multi-GeV energies have shown promising results. If this is confirmed. LENA might serve as far detector in a long-baseline neutrino oscillation experiment currently investigated in LAGUNA-LBNO.

Abstract: At the neutron Lime-of-flight facility n_TOF at CERN a new vertical beam line was constructed in 2014, in order to extend the experimental possibilities at this facility to an even wider range of challenging cross-section measurements of interest in astrophysics, nuclear technology and medical physics. The design of the beam line and the experimental hall was based on FLUKA Monte Carlo simulations, aiming at maximizing the neutron flux, reducing the beam halo and minimizing the background from neutrons interacting with the collimator or back-scattered in the beam dump. The present paper gives an overview on the design of the beam line and the relevant elements and provides an outlook on the expected performance regarding the neutron beam intensity, shape and energy resolution, as well as the neutron and photon backgrounds.

Abstract: A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.