Abstract: The ordering of the neutrino masses is a crucial input for a deep understanding of flavor physics, and its determination may provide the key to establish the relationship among the lepton masses and mixings and their analogous properties in the quark sector. The extraction of the neutrino mass ordering is a data-driven field expected to evolve very rapidly in the next decade. In this review, we both analyse the present status and describe the physics of subsequent prospects. Firstly, the different current available tools to measure the neutrino mass ordering are described. Namely, reactor, long-baseline (accelerator and atmospheric) neutrino beams, laboratory searches for beta and neutrinoless double beta decays and observations of the cosmic background radiation and the large scale structure of the universe are carefully reviewed. Secondly, the results from an up-to-date comprehensive global fit are reported: the Bayesian analysis to the 2018 publicly available oscillation and cosmological data sets provides strong evidence for the normal neutrino mass ordering vs. the inverted scenario, with a significance of 3.5 standard deviations. This preference for the normal neutrino mass ordering is mostly due to neutrino oscillation measurements. Finally, we shall also emphasize the future perspectives for unveiling the neutrinomass ordering. In this regard, apart from describing the expectations from the aforementioned probes, we also focus on those arising from alternative and novel methods, as 21 cm cosmology, core-collapse supernova neutrinos and the direct detection of relic neutrinos.

Abstract: The observation by the IceCube Collaboration of a high-energy (E greater than or similar to 200 TeV) neutrino from the direction of the blazar TXS 0506+056 and the coincident observations of enhanced gamma-ray emissions from the same object by MAGIC and other experiments can be used to set stringent constraints on Lorentz violation in the propagation of neutrinos that is linear in the neutrino energy: Delta v = -E/M-1, where Delta v is the deviation from the velocity of light, and M-1 is an unknown high energy scale to be constrained by experiment. Allowing for a difference in neutrino and photon propagation times of similar to 10 days, we find that M-1 greater than or similar to 3 x 10(16) GeV. This improves on previous limits on linear Lorentz violation in neutrino propagation by many orders of magnitude, and the same is true for quadratic Lorentz violation.

Abstract: The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented.

Abstract: Xe-136 is used as the target medium for many experiments searching for 0 nu beta beta. Despite underground operation, cosmic muons that reach the laboratory can produce spallation neutrons causing activation of detector materials. A potential background that is difficult to veto using muon tagging comes in the form of Xe-137 created by the capture of neutrons on Xe-136. This isotope decays via beta decay with a half-life of 3.8 min and a Q(beta) of similar to 4.16 MeV. This work proposes and explores the concept of adding a small percentage of He-3 to xenon as a means to capture thermal neutrons and reduce the number of activations in the detector volume. When using this technique we find the contamination from Xe-137 activation can be reduced to negligible levels in tonne and multi-tonne scale high pressure gas xenon neutrinoless double beta decay experiments running at any depth in an underground laboratory.

Abstract: The performance of the ATLAS muon trigger system is evaluated with proton-proton (pp) and heavy-ion (HI) collision data collected in Run 2 during 2015-2018 at the Large Hadron Collider. It is primarily evaluated using events containing a pair of muons from the decay of Z bosons to cover the intermediate momentum range between 26 GeV and 100 GeV. Overall, the efficiency of the single-muon triggers is about 68% in the barrel region and 85% in the endcap region. The p(T) range for efficiency determination is extended by using muons from decays of J/psi mesons, W bosons, and top quarks. The performance in HI collision data is measured and shows good agreement with the results obtained in pp collisions. The muon trigger shows uniform and stable performance in good agreement with the prediction of a detailed simulation. Dedicated multi-muon triggers with kinematic selections provide the backbone to beauty, quarkonia, and low-mass physics studies. The design, evolution and performance of these triggers are discussed in detail.