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ATLAS Collaboration(Aad, G. et al), Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., Castillo, F. L., et al. (2022). Constraints on Higgs boson properties using WW*(-> e nu μnu)jj production in 36.1 fb(-1) of root s=13 TeV pp collisions with the ATLAS detector. Eur. Phys. J. C, 82(7), 622–33pp.
Abstract: This article presents the results of two studies of Higgs boson properties using the WW*(-> e nu μnu)jj final state, based on a dataset corresponding to 36.1fb(-1) of root s = 13 TeV proton-proton collisions recorded by the ATLAS experiment at the Large Hadron Collider. The first study targets Higgs boson production via gluon-gluon fusion and constrains the CP properties of the effective Higgs-gluon interaction. Using angular distributions and the overall rate, a value of tan (alpha) = 0.0 +/- 0.4(stat.) +/- 0.3(syst.) is obtained for the tangent of the mixing angle for CP-even and CP-odd contributions. The second study exploits the vector-boson fusion production mechanism to probe the Higgs boson couplings to longitudinally and transversely polarised W and Z bosons in both the production and the decay of the Higgs boson; these couplings have not been directly constrained previously. The polarisation-dependent coupling-strength scale factors are defined as the ratios of the measured polarisation-dependent coupling strengths to those predicted by the Standard Model, and are determined using rate and kinematic information to be a(L) = 0.91(-0.18)(+0.10)(stat.)(-0.17)(+0.09)(syst.) and a(T) = 1.2 +/- 0.4(stat.)(-0.3)(+0.2)(syst.). These coupling strengths are translated into pseudo-observables, resulting in kappa(VV) = 0.91(-0.18)(+0.10)(stat.)(-0.17)(+0.09)(syst.) and epsilon(VV) = 0.13(-0.20)(+0.28)(stat.)(-0.10)(+0.08)(syst.). All results are consistent with the Standard Model predictions.
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De Romeri, V., Puerta, M., & Vicente, A. (2022). Dark matter in a charged variant of the Scotogenic model. Eur. Phys. J. C, 82(7), 623–16pp.
Abstract: Scotogenic models are among the most popular possibilities to link dark matter and neutrino masses. In this work we discuss a variant of the Scotogenic model that includes charged fermions and a doublet with hypercharge 3/2. Neutrino masses are induced at the one-loop level thanks to the states belonging to the dark sector. However, in contrast to the standard Scotogenic model, only the scalar dark matter candidate is viable in this version. After presenting the model and explaining some particularities about neutrino mass generation, we concentrate on its dark matter phenomenology. We show that the observed dark matter relic density can be correctly reproduced in the usual parameter space regions found for the standard Scotogenic model or the Inert Doublet model. In addition, the presence of the charged fermions opens up new viable regions, not present in the original scenarios, provided some tuning of the parameters is allowed.
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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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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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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cantero, J., et al. (2023). Search for resonant WZ production in the fully leptonic final state in proton-proton collisions at √s=13 TeV with the ATLAS detector. Eur. Phys. J. C, 83(7), 633–34pp.
Abstract: A search for a WZ resonance, in the fully leptonic final state (electrons or muons), is performed using 139 fb(-1) of data collected at a centre-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The results are interpreted in terms of a singly charged Higgs boson of the Georgi-Machacek model, produced by WZ fusion, and of a Heavy Vector Triplet, with the resonance produced by WZ fusion or the Drell-Yan process. No significant excess over the Standard Model prediction is observed and limits are set on the production cross-section times branching ratio as a function of the resonance mass for these processes.
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