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Guerrero, M., Olmo, G. J., & Rubiera-Garcia, D. (2023). Geodesic completeness of effective null geodesics in regular space-times with non-linear electrodynamics. Eur. Phys. J. C, 83(9), 785–8pp.
Abstract: We study the completeness of light trajectories in certain spherically symmetric regular geometries found in Palatini theories of gravity threaded by non-linear (electromagnetic) fields, which makes their propagation to happen along geodesics of an effective metric. Two types of geodesic restoration mechanisms are employed: by pushing the focal point to infinite affine distance, thus unreachable in finite time by any sets of geodesics, or by the presence of a defocusing surface associated to the development of a wormhole throat. We discuss several examples of such geometries to conclude the completeness of all such effective paths. Our results are of interest both for the finding of singularity-free solutions and for the analysis of their optical appearances e.g. in shadow observations.
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T2K Collaboration(Abe, K. et al), Antonova, M., Cervera-Villanueva, A., Molina Bueno, L., & Novella, P. (2023). Measurements of neutrino oscillation parameters from the T2K experiment using 3.6 x 10^21 protons on target. Eur. Phys. J. C, 83(9), 782–50pp.
Abstract: The T2K experiment presents new measurements of neutrino oscillation parameters using 19.7(16.3) x 10(20) protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional 4.7 x 10(20) POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on sin(2) theta(13) and the impact of priors on the delta(CP) measurement. Both analyses prefer the normal mass ordering and upper octant of sin(2) theta(23) with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on sin(2) theta(13) from reactors, sin(2) theta(23) = 0.561(-0.032)(+0.021) using Feldman-Cousins corrected intervals, and Delta m(32)(2) = 2.494(-0.058)(+0.041) x 10(-3) eV(2) using constant Delta chi(2) intervals. The CP-violating phase is constrained to delta(CP) = -1.97(-0.70)(+0.97) using Feldman-Cousins corrected intervals, and delta(CP) = 0, pi is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than 2 sigma credible level using a flat prior in delta(CP), and just below 2 sigma using a flat prior in sin delta(CP). When the external constraint on sin(2) nu(13) is removed, sin(2) theta(13) = 28.0(-6.5)(+2.8) x 10(-3), in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.
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Albandea, D., Del Debbio, L., Hernandez, P., Kenway, R., Marsh Rossney, J., & Ramos, A. (2023). Learning trivializing flows. Eur. Phys. J. C, 83(7), 676–14pp.
Abstract: The recent introduction of machine learning techniques, especially normalizing flows, for the sampling of lattice gauge theories has shed some hope on improving the sampling efficiency of the traditional hybrid Monte Carlo (HMC) algorithm. In this work we study a modified HMC algorithm that draws on the seminal work on trivializing flows by L & uuml;scher. Autocorrelations are reduced by sampling from a simpler action that is related to the original action by an invertible mapping realised through Normalizing Flows models with a minimal set of training parameters. We test the algorithm in a f(4) theory in 2D where we observe reduced autocorrelation times compared with HMC, and demonstrate that the training can be done at small unphysical volumes and used in physical conditions. We also study the scaling of the algorithm towards the continuum limit under various assumptions on the network architecture.
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Radics, B., Molina-Bueno, L., Fields, L., Sieber, H., & Crivelli, P. (2023). Sensitivity potential to a light flavor-changing scalar boson with DUNE and NA64 mu. Eur. Phys. J. C, 83(9), 775–7pp.
Abstract: In this work, we report on the sensitivity potential of complementary muon-on-target experiments to new physics using a scalar boson benchmark model associated with charged lepton flavor violation. The NA64 μexperiment at CERN uses a 160-GeV energy muon beam with an active target to search for excess events with missing energy and momentum as a probe of new physics. At the same time, the proton beam at Fermilab, which is used to produce the neutrino beam for the Deep Underground Neutrino Experiment (DUNE), will also produce a high-intensity muon beam dumped in an absorber. Combined with the liquid argon near detector, the system could be used to search for similar scalar boson particles with a lower-energy but higher-intensity beam. We find that both NA64 μand DUNE could cover new, unexplored parts of the parameter space of the same benchmarkmodel, providing a complementaryway to search for new physics.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., Cabrera Urban, S., et al. (2023). ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset. Eur. Phys. J. C, 83(7), 681–37pp.
Abstract: The flavour-tagging algorithms developed by the AvTLAS Collaboration and used to analyse its dataset of root s = 13 TeV pp collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% b-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model t (t) over bar events; similarly, at a c-jet identification efficiency of 30%, a light-jet (b-jet) rejection factor of 70 (9) is obtained.
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