Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

Efficacy and safety of pregabalin in alcohol dependence

INTRODUCTION: Pregabalin is a new anxiolytic that selectively binds to the alpha2-delta subunit of voltage-gated calcium channels, inhibiting release of excessive levels of excitatory neurotransmitters. In this open-label trial we aimed to investigate the efficacy of pregabalin on alcoholism indices in detoxified alcohol-dependent subjects. Reduction of cravings, psychiatric symptom improvements, and the evaluation of safety parameters were the secondary endpoints. METHODS: Thirty-one alcohol-dependent patients were consecutively recruited and screened for the study. Twenty detoxified patients received pregabalin starting at 50 mg/day (orally) in the first week, gradually increasing to a flexible dose of 150-450 mg/day. Subjects were assessed at the beginning of the treatment, and after 2, 8 and 16 weeks. Craving (visual analogue scale, Obsessive and Compulsive Drinking Scale [OCDS]) and withdrawal (Clinical Institute Withdrawal Assessment for Alcohol [CIWA-Ar]) rating scales were applied; psychiatric symptoms were evaluated through the Symptom Check List-90-Revised (SCL-90-R). RESULTS: Out of the twenty patients who received the study drug, 15 completed the study procedures: 10 remained totally alcohol-free for the duration of the study, five relapsed. An additional four patients dropped out during the study, and one stopped taking medication due to adverse events. A significant progressive reduction of both craving and withdrawal symptomatology were observed. Safety parameters did not show any significant variation during treatment. CONCLUSION: Pregabalin shows promise as a treatment for alcohol dependence. Although limited by a low number of participants and by the open design, this is the first study concerning the efficacy and safety of pregabalin in current alcoholics. In these patients pregabalin was effective and well tolerated. Additional research is needed to explore the clinical relevance of these findings

Constraining the magnitude of the Chiral Magnetic Effect with Event Shape Engineering in Pb–Pb collisions at sNN=2.76 TeV

In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb–Pb collisions at sNN=2.76 TeV. The two-particle correlator 〈cos⁡(φα−φβ)〉 calculated for different combinations of charges α and β is almost independent of v2 (for a given centrality), while the three-particle correlator 〈cos⁡(φα+φβ−2Ψ2)〉 scales almost linearly both with the event v2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10–50% centrality interval is found to be 26–33% at 95% confidence level. © 2017 The Author(s

Measuring KS 0K± interactions using Pb–Pb collisions at sNN=2.76 TeV

We present the first ever measurements of femtoscopic correlations between the KS 0 and K± particles. The analysis was performed on the data from Pb–Pb collisions at sNN=2.76 TeV measured by the ALICE experiment. The observed femtoscopic correlations are consistent with final-state interactions proceeding via the a0(980) resonance. The extracted kaon source radius and correlation strength parameters for KS 0K− are found to be equal within the experimental uncertainties to those for KS 0K+. Comparing the results of the present study with those from published identical-kaon femtoscopic studies by ALICE, mass and coupling parameters for the a0 resonance are tested. Our results are also compatible with the interpretation of the a0 having a tetraquark structure instead of that of a diquark. © 2017 The Autho

Longitudinal asymmetry and its effect on pseudorapidity distributions in Pb–Pb collisions at sNN=2.76 TeV

First results on the longitudinal asymmetry and its effect on the pseudorapidity distributions in Pb–Pb collisions at sNN = 2.76 TeV at the Large Hadron Collider are obtained with the ALICE detector. The longitudinal asymmetry arises because of an unequal number of participating nucleons from the two colliding nuclei, and is estimated for each event by measuring the energy in the forward neutron-Zero-Degree-Calorimeters (ZNs). The effect of the longitudinal asymmetry is measured on the pseudorapidity distributions of charged particles in the regions |η|<0.9, 2.8<η<5.1 and −3.7<η<−1.7 by taking the ratio of the pseudorapidity distributions from events corresponding to different regions of asymmetry. The coefficients of a polynomial fit to the ratio characterise the effect of the asymmetry. A Monte Carlo simulation using a Glauber model for the colliding nuclei is tuned to reproduce the spectrum in the ZNs and provides a relation between the measurable longitudinal asymmetry and the shift in the rapidity (y0) of the participant zone formed by the unequal number of participating nucleons. The dependence of the coefficient of the linear term in the polynomial expansion, c1, on the mean value of y0 is investigated. © 2018 The Author(s